Sachet, Edward; Shelton, Christopher T.; Harris, Joshua S.; Gaddy, Benjamin E.; Irving, Douglas L.; Curtarolo, Stefano; Donovan, Brian F.; Hopkins, Patrick E.; Sharma, Peter A.; Sharma, Peter A.; Ihlefeld, Jon F.; Franzen, Stefan; Maria, Jon P.
The interest in plasmonic technologies surrounds many emergent optoelectronic applications, such as plasmon lasers, transistors, sensors and information storage. Although plasmonic materials for ultraviolet-visible and near-infrared wavelengths have been found, the mid-infrared range remains a challenge to address: few known systems can achieve subwavelength optical confinement with low loss in this range. With a combination of experiments and ab initio modelling, here we demonstrate an extreme peak of electron mobility in Dy-doped CdO that is achieved through accurate 'defect equilibrium engineering'. In so doing, we create a tunable plasmon host that satisfies the criteria for mid-infrared spectrum plasmonics, and overcomes the losses seen in conventional plasmonic materials. In particular, extrinsic doping pins the CdO Fermi level above the conduction band minimum and it increases the formation energy of native oxygen vacancies, thus reducing their populations by several orders of magnitude. The substitutional lattice strain induced by Dy doping is sufficiently small, allowing mobility values around 500 cm2 V-1 s-1 for carrier densities above 1020 cm-3. Our work shows that CdO:Dy is a model system for intrinsic and extrinsic manipulation of defects affecting electrical, optical and thermal properties, that oxide conductors are ideal candidates for plasmonic devices and that the defect engineering approach for property optimization is generally applicable to other conducting metal oxides.
In the aerospace industry, hail strikes on a structure are an environment that must be considered when qualifying a product. Performing a physical test on a product would require a test setup that would launch a fabricated hail stone at an expensive prototype. This test may be difficult or impossible to execute and destructive to the product. Instead of testing, a finite element model (FEM) may be used to simulate the damage and consequences of a hail strike. In order to use a FEM in this way, an accurate representation of the input force from a hail stone must be known. The purpose of this paper is to calculate the force that a hail stone imparts on an object using the inverse method SWAT-TEEM. This paper discusses the advantages of using SWAT-TEEM over other force identification methods and exercises the algorithm for a test series of hail strikes that include multiple angles of attack and multiple velocities which include speeds that are supersonic.
Hattar, Khalid M.; Cheaito, Ramez; Gorham, Caroline S.; Misra, Amit; Hopkins, Patrick E.
The progressive build up of fission products inside different nuclear reactor components can lead to significant damage of the constituent materials. We demonstrate the use of time-domain thermoreflectance (TDTR), a nondestructive thermal measurement technique, to study the effects of radiation damage on material properties. We use TDTR to report on the thermal conductivity of optimized ZIRLO, a material used as fuel cladding in nuclear reactors. We find that the thermal conductivity of optimized ZIRLO is 10.7 ± 1.8 W m-1 K-1 at room temperature. Furthermore, we find that the thermal conductivities of copper-niobium nanostructured multilayers do not change with helium ion irradiation doses of 1015 cm-2 and ion energy of 200 keV, demonstrating the potential of heterogeneous multilayer materials for radiation tolerant coatings. Finally, we compare the effect of ion doses and ion beam energies on the measured thermal conductivity of bulk silicon. Our results demonstrate that TDTR can be used to quantify depth dependent damage.
Geiger mode detectors fabricated in silicon are used to detect incident photons with high sensitivity. They are operated with large internal electric fields so that a single electron-hole pair can trigger an avalanche breakdown which generates a signal in an external circuit. We have applied a modified version of the ion beam induced charge technique in a nuclear microprobe system to investigate the application of Geiger mode detectors to detect discrete ion impacts. Our detectors are fabricated with an architecture based on the avalanche diode structure and operated with a transient bias voltage that activates the Geiger mode. In this mode avalanche breakdown is triggered by ion impact followed by diffusion of an electron-hole pair into the sensitive volume. The avalanche breakdown is quenched by removal of the transient bias voltage which is synchronized with a beam gate. An alternative operation mode is possible at lower bias voltages where the avalanche process self-quenches and the device exhibits linear charge gain as a consequence. Incorporation of such a device into a silicon substrate potentially allows the exceptional sensitivity of Geiger mode to register an electron-hole pair from sub-10 keV donor atom implants for the deterministic construction of shallow arrays of single atoms in the substrate required for emerging quantum technologies. Our characterization system incorporates a fast electrostatic ion beam switcher gated by the transient device bias, duration 800 ns, with a time delay, duration 500 ns, that allows for both the ion time of flight and the diffusion of the electron-hole pairs in the substrate into the sensitive region of the device following ion impact of a scanned 1 MeV H microbeam. We compare images at the micron scale mapping the response of the device to ion impact operated in both Geiger mode and avalanche (linear) mode for silicon devices engineered with this ultimate-sensitivity detector structure.
Matrix multiplication is a fundamental computation in many scientific disciplines. In this paper, we show that novel fast matrix multiplication algorithms can significantly outperform vendor implementations of the classical algorithm and Strassen's fast algorithm on modest problem sizes and shapes. Furthermore, we show that the best choice of fast algorithm depends not only on the size of the matrices but also the shape. We develop a code generation tool to automatically implement multiple sequential and shared-memory parallel variants of each fast algorithm, including our novel parallelization scheme. This allows us to rapidly benchmark over 20 fast algorithms on several problem sizes. Furthermore, we discuss a number of practical implementation issues for these algorithms on shared-memory machines that can direct further research on making fast algorithms practical.
A series of simulations and experiments to resolve questions about the operation of arrays of closely spaced small aspect ratio rod pinches has been performed. Design and postshot analysis of the experimental results are supported by 3-D particle-in-cell simulations. Both simulations and experiments support these conclusions. Penetration of current to the interior of the array appears to be efficient, as the current on the center rods is essentially equal to the current on the outer rods. Current loss in the feed due to the formation of magnetic nulls was avoided in these experiments by design of the feed surface of the cathode and control of the gap to keep the electric fields on the cathode below the emission threshold. Some asymmetry in the electron flow to the rod was observed, but the flow appeared to symmetrize as it reached the end of the rod. Interaction between the rod pinches can be controlled to allow the stable and consistent operation of arrays of rod pinches.
Following prior experimental evidence of electrostatic charge separation, electric and magnetic fields produced by hypervelocity impact, we have developed a model of electrostatic charge separation based on plasma sheath theory and implemented it into the CTH shock physics code. Preliminary assessment of the model shows good qualitative and quantitative agreement between the model and prior experiments at least in the hypervelocity regime for the porous carbonate material tested. Moreover, the model agrees with the scaling analysis of experimental data performed in the prior work, suggesting that electric charge separation and the resulting electric and magnetic fields can be a substantial effect at larger scales, higher impact velocities, or both.
Occasionally, our well-controlled cookoff experiments with Comp-B give anomalous results when venting conditions are changed. For example, a vented experiment may take longer to ignite than a sealed experiment. In the current work, we show the effect of venting on thermal ignition of Comp-B. We use Sandia's Instrumented Thermal Ignition (SITI) experiment with various headspace volumes in both vented and sealed geometries to study ignition of Comp-B. In some of these experiments, we have used a boroscope to observe Comp-B as it melts and reacts. We propose that the mechanism for ignition involves TNT melting, dissolution of RDX, and complex bubbly liquid flow. High pressure inhibits bubble formation and flow is significantly reduced. At low pressure, a vigorous dispersed bubble flow was observed.
In order to reliably simulate the energy yield of photovoltaic (PV) systems, it is necessary to have an accurate model of how the PV modules perform with respect to irradiance and cell temperature. Building on a previous study that addresses the irradiance dependence, two approaches to fit the temperature dependence of module power in PVsyst have been developed and are applied here to recent multi-irradiance and temperature data for a standard Yingli Solar PV module type. The results demonstrate that it is possible to match the measured irradiance and temperature dependence of PV modules in PVsyst. Improvements in energy yield prediction using the optimized models relative to the PVsyst standard model are considered significant for decisions about project financing.
A notion of material homogeneity is proposed for peridynamic bodies with variable horizon but constant bulk properties. A relation is derived that scales the force state according to the position-dependent horizon while keeping the bulk properties unchanged. Using this scaling relation, if the horizon depends on position, artifacts called ghost forces may arise in a body under a homogeneous deformation. These artifacts depend on the second derivative of the horizon and can be reduced by employing a modified equilibrium equation using a new quantity called the partial stress. Bodies with piecewise constant horizon can be modeled without ghost forces by using a simpler technique called a splice. As a limiting case of zero horizon, both the partial stress and splice techniques can be used to achieve local-nonlocal coupling. Computational examples, including dynamic fracture in a one-dimensional model with local- nonlocal coupling, illustrate the methods.
Occasionally, our well-controlled cookoff experiments with Comp-B give anomalous results when venting conditions are changed. For example, a vented experiment may take longer to ignite than a sealed experiment. In the current work, we show the effect of venting on thermal ignition of Comp-B. We use Sandia's Instrumented Thermal Ignition (SITI) experiment with various headspace volumes in both vented and sealed geometries to study ignition of Comp-B. In some of these experiments, we have used a boroscope to observe Comp-B as it melts and reacts. We propose that the mechanism for ignition involves TNT melting, dissolution of RDX, and complex bubbly liquid flow. High pressure inhibits bubble formation and flow is significantly reduced. At low pressure, a vigorous dispersed bubble flow was observed.
We find for infrared wavelengths that there are broad ranges of particle sizes and refractive indices that represent fog and rain, where circular polarization can persist to longer ranges than linear polarization. Using polarization tracking Monte Carlo simulations for varying particle size, wavelength, and refractive index, we show that, for specific scene parameters, circular polarization outperforms linear polarization in maintaining the illuminating polarization state for large optical depths. This enhancement with circular polarization can be exploited to improve range and target detection in obscurant environments that are important in many critical sensing applications. Initially, researchers employed polarizationdiscriminating schemes, often using linearly polarized active illumination, to further distinguish target signals from the background noise. More recently, researchers have investigated circular polarization as a means to separate signal from noise even more. Specifically, we quantify both linearly and circularly polarized active illumination and show here that circular polarization persists better than linear for radiation fog in the short-wave infrared, for advection fog in the short-wave and long-wave infrared, and large particle sizes of Sahara dust around the 4 μmwavelength. Conversely, we quantify where linear polarization persists better than circular polarization for some limited particle sizes of radiation fog in the long-wave infrared, small particle sizes of Sahara dust for wavelengths of 9-10.5 μm, and large particle sizes of Sahara dust through the 8-11 μm wavelength range in the long-wave infrared.
Hutchins, Margot J.; Bhinge, Raunak; Micali, Maxwell K.; Robinson, Stefanie L.; Sutherland, John W.; Dornfeld, David
Increasing connectivity, use of digital computation, and off-site data storage provide potential for dramatic improvements in manufacturing productivity, quality, and cost. However, there are also risks associated with the increased volume and pervasiveness of data that are generated and potentially accessible to competitors or adversaries. Enterprises have experienced cyber attacks that exfiltrate confidential and/or proprietary data, alter information to cause an unexpected or unwanted effect, and destroy capital assets. Manufacturers need tools to incorporate these risks into their existing risk management processes. This paper establishes a framework that considers the data flows within a manufacturing enterprise and throughout its supply chain. The framework provides several mechanisms for identifying generic and manufacturing-specific vulnerabilities and is illustrated with details pertinent to an automotive manufacturer. In addition to providing manufacturers with insights into their potential data risks, this framework addresses an outcome identified by the NIST Cybersecurity Framework.
Three-dimensional (3D) network structure has been envisioned as a superior architecture for lithium ion battery (LIB) electrodes, which enhances both ion and electron transport to significantly improve battery performance. Herein, a 3D carbon nano-network is fabricated through chemical vapor deposition of carbon on a scalably manufactured 3D porous anodic alumina (PAA) template. As a demonstration on the applicability of 3D carbon nano-network for LIB electrodes, the low conductivity active material, TiO2, is then uniformly coated on the 3D carbon nano-network using atomic layer deposition. High power performance is demonstrated in the 3D C/TiO2 electrodes, where the parallel tubes and gaps in the 3D carbon nano-network facilitates fast Li ion transport. A large areal capacity of ~0.37mAh·cm-2 is achieved due to the large TiO2 mass loading in the 60μm-thick 3D C/TiO2 electrodes. At a test rate of C/5, the 3D C/TiO2 electrode with 18nm-thick TiO2 delivers a high gravimetric capacity of ~240mAhg-1, calculated with the mass of the whole electrode. A long cycle life of over 1000 cycles with a capacity retention of 91% is demonstrated at 1C. The effects of the electrical conductivity of carbon nano-network, ion diffusion, and the electrolyte permeability on the rate performance of these 3D C/TiO2 electrodes are systematically studied.
Benjamin B. Yang shares his views on photovoltaics (PV) failure analysis and reliability. He provides information about common failure mechanisms in the PV industry and the significant overlap with FA techniques and meth?ods in microelectronics. The rapid growth and adoption of this technology means that microelectronics failure analysis and reliabil-ity experts may be called upon to address current and future challenges. These failures can be analyzed and solved by the implementation of FA techniques and meth?ods in microelectronics.
Deep Borehole Disposal (DBD) of radioactive waste has some clear advantages over mined repositories, including incremental construction and loading, enhanced natural barriers provided by deep continental crystalline basement, and reduced site characterization. Unfavorable features for a DBD site include upward vertical fluid potential gradients, presence of economically exploitable natural resources, presence of high permeability connection from the waste disposal zone to the shallow subsurface, and significant probability of future volcanic activity. Site characterization activities would encompass geomechanical (i.e., rock stress state, fluid pressure, and faulting), geological (i.e., both overburden and bedrock lithology), hydrological (i.e., quantity of fluid, fluid convection properties, and solute transport mechanisms), chemical (i.e., rock and fluid interaction), and socioeconomic (i.e., likelihood for human intrusion) aspects. For a planned Deep Borehole Field Test (DBFT), site features and/or physical processes would be evaluated using both direct (i.e., sampling and in-hole testing) and indirect (i.e., surface and borehole geophysical) methods for efficient and effective characterization. Surface-based characterization would be used to guide the exploratory drilling program, once a candidate DBFT site has been selected. Borehole based characterization will be used to determine the variability of system state (i.e., stress, pressure, temperature, petrology, and water chemistry) with depth, and to develop material and system parameters relevant for numerical simulation. While the site design of DBD could involve an array of disposal boreholes, it may not be necessary to characterize each borehole in detail. Characterization strategies will be developed in the DBFT that establish disposal system safety sufficient for licensing a disposal array.
The United States Department of Energy (DOE) is conducting research and development (R&D) activities within the Used Fuel Disposition Campaign to support the implementation of the DOE's 2013 Strategy for the Management and Disposal of Used Nuclear Fuel and High-Level Radioactive Waste. R&D activities focus on storage, transportation, and disposal of used nuclear fuel (UNF) and wastes generated by existing and future nuclear fuel cycles and are ongoing at nine national laboratories. Additional relevant R&D is conducted at multiple universities through the DOE's Nuclear Energy University Program. Within the storage and transportation areas, R&D continues to focus on technical gaps related to extended storage and subsequent transportation of UNF. Primary emphasis for FY15 is on experimental and analysis activities that support the DOE s dry cask demonstration confirmatory data project initiated at the North Anna Nuclear Power Plant in Virginia by the Electric Power Research Institute in collaboration with AREVA and Dominion Power. Within the disposal research area, current planning calls for a significant increase in R&D associated with evaluating the feasibility of deep borehole disposal of some waste forms, in addition to a continued emphasis on confirming the viability of generic mined disposal concepts in multiple geologic media. International collaborations that allow the U.S. program to benefit from experience and opportunities for research in other nations remain a high priority.
An excellent scientific understanding of salt reconsolidation mechanisms has been established from experimental results and observational microscopy. Thermal, mechanical, and fluid transport properties of reconsolidating granular salt are fundamental to the design, analysis, and performance assessment of potential salt repositories for heat-generating nuclear waste. Application of acquired knowledge to construction techniques could potentially achieve high-performance seal properties upon construction or during the repository operational period, which lessens reliance on modeling to argue for evolving engineering characteristics and attainment of sealing functions at some future time. The robust database could be augmented by select reconsolidation experiments with admixtures and analogue studies with appropriate documentation of microprocesses.
Amazon Mechanical Turk (AMT) has become a powerful tool for social scientists due to its inexpensiveness, ease of use, and ability to attract large numbers of workers. While the subject pool is diverse, there are numerous questions regarding the composition of the workers as a function of when the “Human Intelligence Task”(HIT) is posted. Given the “queue” nature of HITs and the disparity in geography of participants, it is natural to wonder whether HIT posting time/day can have an impact on the population that is sampled.We address this question using a panel survey on AMT and show (surprisingly) that except for gender, there is no statistically significant difference in terms of demographics characteristics as a function of HIT posting time.
The Navigation, Guidance, and Control (NGC) Department at Sandia National Laboratories conducts flight test programs where rapid proto- typing is essential. To successfully maintain schedule it is critical to have high confidence in the NGC hardware and software prior to integration testing. The NGC Department has developed a V-Model diagram approach to ensure high confidence with hardware and software prior to in- tegration testing within a rapid prototyping environment. The V-Model detailed design process flow describes a design approach for testing hard- ware and software early and often using hardware-in-the-loop (HWIL) and software-in-the-loop (SWIL) simulations.
Sandia’s Hypersonic Wind Tunnel (HWT) became operational in 1962, providing a test capability for the nation’s nuclear weapons complex. The first modernization program was completed in 1977. A blowdown facility with a 0.46-m diameter test section, the HWT operates at Mach 5, 8, and 14 with stagnation pressures to 21 MPa and temperatures to 1400K. Minimal further alteration to the facility occurred until 2008, but in recent years the HWT has received considerable investment to ensure its viability for at least the next 25 years. This has included reconditioning of the vacuum spheres, replacement of the high-pressure air tanks for Mach 5, new compressors to provide the high-pressure air, upgrades to the cryogenic nitrogen source for Mach 8 and 14, an efficient high-pressure water cooling system for the nozzle throats, and refurbishment of the electric-resistance heaters. The HWT is now returning to operation following the largest of the modernization projects, in which the old variable transformer for the 3-MW electrical system powering the heaters was replaced with a silicon-controlled rectifier power system. The final planned upgrade is a complete redesign of the control console and much of the gas-handling equipment.
The majority of state-of-the-art speaker recognition systems (SR) utilize speaker models that are derived from an adapted universal background model (UBM) in the form of a Gaussian mixture model (GMM). This is true for GMM supervector systems, joint factor analysis systems, and most recently i-vector systems. In all of these systems, the posterior probabilities and sufficient statistics calculations represent a computational bottleneck in both enrollment and testing. We propose a multi-layered hash system, employing a tree-structured GMM-UBM which uses Runnalls' Gaussian mixture reduction technique, in order to reduce the number of these calculations. With this tree-structured hash, we can trade-off reduction in computation with a corresponding degradation of equal error rate (EER). As an example, we reduce this computation by a factor of 15 × while incurring less than 10% relative degradation of EER (or 0.3% absolute EER) when evaluated with NIST 2010 speaker recognition evaluation (SRE) telephone data.
This work examines simulation requirements for ensuring accurate predictions of compressible cavity flows. Lessons learned from this study will be used in the future to study the effects of complex geometric features, representative of those found on real weapons bays, on compressible flow past open cavities. A hybrid RANS/LES simulation method is applied to a rectangular cavity with length-to-depth ratio of 7, in order to first validate the model for this class of flows. Detailed studies of mesh resolution, absorbing boundary condition formulation, and boundary zone extent are included and guidelines are developed for ensuring accurate prediction of cavity pressure fluctuations.
In this paper, a series of algorithms are proposed to address the problems in the NASA Langley Research Center Multidisciplinary Uncertainty Quantification Challenge. A Bayesian approach is employed to characterize and calibrate the epistemic parameters based on the available data, whereas a variance-based global sensitivity analysis is used to rank the epistemic and aleatory model parameters. A nested sampling of the aleatory-epistemic space is proposed to propagate uncertainties from model parameters to output quantities of interest.
The primary problem in property testing is to decide whether a given function satisfies a certain property, or is far from any function satisfying it. This crucially requires a notion of distance between functions. The most prevalent notion is the Hamming distance over the uniform distribution on the domain. This restriction to uniformity is rather limiting, and it is important to investigate distances induced by more general distributions. In this paper, we give simple and optimal testers for bounded derivative properties over arbitrary product distributions. Bounded derivative properties include fundamental properties such as monotonicity and Lipschitz continuity. Our results subsume almost all known results (upper and lower bounds) on monotonicity and Lipschitz testing. We prove an intimate connection between bounded derivative property testing and binary search trees (BSTs). We exhibit a tester whose query complexity is the sum of expected depths of optimal BSTs for each marginal. Furthermore, we show this sum-of-depths is also a lower bound. A technical contribution of our work is an optimal dimension reduction theorem for all bounded derivative properties, which relates the distance of a function from the property to the distance of restrictions of the function to random lines. Such a theorem has been elusive even for monotonicity, and our theorem is an exponential improvement to the previous best known result.
Full-field axial deformation within molten-salt batteries was measured using x-ray imaging with a sampling moiré technique. This method worked for in situ testing of the batteries because of the inherent grid pattern of the battery layers when imaged with x-rays. High-speed x-ray imaging acquired movies of the layer deformation during battery activation. Numerical validation of the technique, as implemented in this paper, was done using synthetic and numerically shifted images. Typical results of a battery are shown for one test. Ongoing work on validation and more test results are in progress.
This work presents a technique for statistically modeling errors introduced by reduced-order models. The method employs Gaussian-process regression to construct a mapping from a small number of computationally inexpensive “error indicators” to a distribution over the true error. The variance of this distribution can be interpreted as the (epistemic) uncertainty introduced by the reduced-order model. To model normed errors, the method employs existing rigorous error bounds and residual norms as indicators; numerical experiments show that the method leads to a near-optimal expected effectivity in contrast to typical error bounds. To model errors in general outputs, the method uses dual-weighted residuals-which are amenable to uncertainty control-as indicators. Experiments illustrate that correcting the reduced-order-model output with this surrogate can improve prediction accuracy by an order of magnitude; this contrasts with existing “multifidelity correction” approaches, which often fail for reduced-order models and suffer from the curse of dimensionality. The proposed error surrogates also lead to a notion of “probabilistic rigor”; i.e., the surrogate bounds the error with specified probability.
A materials study of high reliability electronics cleaning is presented here. In Phase 1, mixed type substrates underwent a condensed contaminants application to view a worst- case scenario for unremoved flux with cleaning agent residue for parts in a silicone oil filled environment. In Phase 2, fluxes applied to copper coupons and to printed wiring boards underwent gentle cleaning then accelerated aging in air at 65% humidity and 30 O C. Both sets were aged for 4 weeks. Contaminants were no-clean (ORL0), water soluble (ORH1 liquid and ORH0 paste), and rosin (RMA; ROL0) fluxes. Defluxing agents were water, solvents, and engineered aqueous defluxers. In the first phase, coupons had flux applied and heated, then were placed in vials of oil with a small amount of cleaning agent and additional coupons. In the second phase, pairs of copper coupons and PWB were hand soldered by application of each flux, using tin-lead solder in a strip across the coupon or a set of test components on the PWB. One of each pair was cleaned in each cleaning agent, the first with a typical clean, and the second with a brief clean. Ionic contamination residue was measured before accelerated aging. After aging, substrates were removed and a visual record of coupon damage made, from which a subjective rank was applied for comparison between the various flux and defluxer combinations; more corrosion equated to higher rank. The ORH1 water soluble flux resulted in the highest ranking in both phases, the RMA flux the least. For the first phase, in which flux and defluxer remained on coupons, the aqueous defluxers led to worse corrosion. The vapor phase cleaning agents resulted in the highest ranking in the second phase, in which there was no physical cleaning. Further study of cleaning and rinsing parameters will be required.
We develop a computationally less expensive alternative to the direct solution of a large sparse symmetric positive definite system arising from the numerical solution of elliptic partial differential equation models. Our method, substituted factorization, replaces the computationally expensive factorization of certain dense submatrices that arise in the course of direct solution with sparse Cholesky factorization with one or more solutions of triangular systems using substitution. These substitutions fit into the tree-structure commonly used by parallel sparse Cholesky, and reduce the initial factorization cost at the expense of a slight increase cost in solving for a right-hand side vector. Our analysis shows that substituted factorization reduces the number of floating-point operations for the model k × k 5-point finite-difference problem by 10% and empirical tests show execution time reduction on average of 24.4%. On a test suite of three-dimensional problems we observe execution time reduction as high as 51.7% and 43.1% on average.
Resilience is a major challenge for large-scale systems. It is particularly important for iterative linear solvers, since they take much of the time of many scientific applications. We show that single bit flip errors in the Flexible GMRES iterative linear solver can lead to high computational overhead or even failure to converge to the right answer. Informed by these results, we design and evaluate several strategies for fault tolerance in both inner and outer solvers appropriate across a range of error rates.We implement them, extending Trilinos’ solver library with the Global View Resilience (GVR) programming model, which provides multi-stream snapshots, multi-version data structures with portable and rich error checking/recovery. Experimental results validate correct execution with low performance overhead under varied error conditions.
Experimental dynamic substructures in both modal and frequency response domains using the transmission simulator method have been developed for several systems since 2007. The standard methodology couples the stiffness, mass and damping matrices of the experimental substructure to a finite element (FE) model of the remainder of the system through multi-point constraints. This can be somewhat awkward in the FE code. It is desirable to have an experimental substructure in the Craig-Bampton (CB) form to ease the implementation process, since many codes such as Nastran, ABAQUS, ANSYS and Sierra Structural Dynamics have CB as a substructure option. Many analysts are familiar with the CB form. A square transformation matrix is derived that produces a modified CB form that still requires multi-point constraints to couple to the rest of the FE model. Finally the multi-point constraints are imported to the modified CB matrices to produce substructure matrices that fit in the standard CB form. The physical boundary degrees-of-freedom (dof) of the experimental substructure matrices can be directly attached to physical dof in the remainder of the FE model. This paper derives the new experimental substructure that fits in the CB form, and presents results from an analytical and an industrial example utilizing the new CB form.
This work was motivated by a desire to transform an experimental dynamic substructure derived using the transmission simulator method into the Craig-Bampton substructure form which could easily be coupled with a finite element code with the Craig-Bampton option. Near the middle of that derivation, a modal Craig-Bampton form emerges. The modal Craig-Bampton (MCB) form was found to have several useful properties. The MCB matrices separate the response into convenient partitions related to (1) the fixed boundary modes of the substructure (a diagonal partition), (2) the modes of the fixture it is mounted upon, (3) the coupling terms between the two sets of modes. Advantages of the MCB are addressed. (1) The impedance of the boundary condition for component testing, which is usually unknown, is quantified with simple terms. (2) The model is useful for shaker control in both single degree of freedom and multiple degree of freedom shaker control systems. (3) MCB provides an energy based framework for component specifications to reduce over-testing but still guarantee conservatism.
We report measurements of temperature and O2/N2 mole-fraction ratio in the vicinity of a burning and decomposing carbon-epoxy composite aircraft material samples exposed to uniform heat fluxes of 48 and 69 kW/m2. Controlled laboratory experiments were conducted with the samples suspended above a cone-type heater and enclosed in an optically accessible chimney. Noninvasive coherent anti-Stokes Raman scattering (CARS) measurements we performed on a single-laser-shot basis. The CARS data were performed with both a traditional point measurement system and with a one-dimensional line imaging scheme that provides single-shot temperature and O2/N2 profiles to reveal the quantitative structure of the temperature and oxygen concentration profiles over the duration of the 30-40 minute duration events. The measured near-surface temperature and oxygen transport are an important factor for exothermic chemistry and oxidation of char materials and the carbon fibers themselves in a fire scenario. These unique laser-diagnostic experiments provide new information on physical/chemical processes in a well-controlled environment which may be useful for the development of heat-and mass-transfer models for the composite fire scenario.
As more and more high-consequence applications such as aerospace systems leverage computational models to support decisions, the importance of assessing the credibility of these models becomes a high priority. Two elements in the credibility assessment are verification and validation. The former focuses on convergence of the solution (i.e. solution verification) and the “pedigree” of the codes used to evaluate the model. The latter assess the agreement of the model prediction to real data. The outcome of these elements should map to a statement of credibility on the predictions. As such this credibility should be integrated into the decision making process. In this paper, we present a perspective as to how to integrate these element into a decision making process. The key challenge is to span the gap between physics-based codes, quantitative capability assessments (V&V/UQ), and qualitative risk-mitigation concepts.
High-performance radar operation, particularly Ground Moving Target Indicator (GMTI) radar modes, are very sensitive to anomalous effects of system nonlinearities. System nonlinearities generate harmonic spurs that at best degrade, and at worst generate false target detections. One significant source of nonlinear behavior is the Analog to Digital Converter (ADC). One measure of its undesired nonlinearity is its Integral Nonlinearity (INL) specification. We examine in this paper the relationship of INL to radar performance; in particular its manifestation in a range-Doppler map or image.
In this paper, the effect of two different turbine blade designs on the wake characteristics was investigated using large-eddy simulation with an actuator line model. For the two different designs, the total axial load is nearly the same but the spanwise (radial) distributions are different. The one with higher load near the blade tip is denoted as Design A; the other is Design B. From the computed results, we observed that the velocity deficit from Design B is higher than that from Design A. The intensity of turbulence kinetic energy in the far wake is also higher for Design B. The effect of blade load distribution on the wind turbine axial and tangential induction factors was also investigated.
In the summer of 2020, the National Aeronautics and Space Administration (NASA) plans to launch a spacecraft as part of the Mars 2020 mission. One option for the rover on the proposed spacecraft uses a Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) to provide continuous electrical and thermal power for the mission. NASA has prepared an Environmental Impact Statement (EIS) in accordance with the National Environmental Policy Act. The EIS includes information on the risks of mission accidents to the general public and on-site workers at the launch complex. The Nuclear Risk Assessment (NRA) addresses the responses of the MMRTG option to potential accident and abort conditions during the launch opportunity for the Mars 2020 mission and the associated consequences. This information provides the technical basis for the radiological risks of the MMRTG option for the EIS. This paper provides a summary of the methods and results used in the NRA.
Light body armor development for the war fighter is based on trial-and-error testing of prototype designs against ballistic projectiles. Torso armor testing against blast is virtually nonexistent but necessary to ensure adequate mitigation against injury to the heart and lungs. In this paper, we discuss the development of a high-fidelity human torso model and the associated modeling & simulation (M&S) capabilities. Using this torso model, we demonstrate the advantage of virtual simulation in the investigation of wound injury as it relates to the war fighter experience. Here, we present the results of virtual simulations of blast loading and ballistic projectile impact to the torso with and without notional protective armor. Our intent here is to demonstrate the advantages of applying a modeling and simulation approach to the investigation of wound injury and relative merit assessments of protective body armor.
Recent cyber security events have demonstrated the need for algorithms that adapt to the rapidly evolving threat landscape of complex network systems. In particular, human analysts often fail to identify data exfiltration when it is encrypted or disguised as innocuous data. Signature-based approaches for identifying data types are easily fooled and analysts can only investigate a small fraction of network events. However, neural networks can learn to identify subtle patterns in a suitably chosen input space. To this end, we have developed a signal processing approach for classifying data files which readily adapts to new data formats. We evaluate the performance for three input spaces consisting of the power spectral density, byte probability distribution and sliding-window entropy of the byte sequence in a file. By combining all three, we trained a deep neural network to discriminate amongst nine common data types found on the Internet with 97.4% accuracy.
The theme of the paper is that consolidated interim storage can provide an important integrating function between storage and disposal in the United States. Given the historical tension between consolidated interim storage and disposal in the United States, this paper articulates a rationale for consolidated interim storage. However, the paper concludes more effort could be expended on developing the societal aspects of the rationale, in addition to the technical and operational aspects of using consolidated interim storage.
The relationship between the damage potential of a series of relatively low level shocks and a single high level shock that causes severe damage is complex and depends on many factors. Shock Response Spectra are the standard for describing mechanical shock events for aerospace vehicles, but are only applicable to single shocks. Energy response spectra are applicable to multiple shock events. This paper describes the results of an initial study that sought to gain insight into how energy response spectra of low amplitude shocks relate to energy response spectra of a high amplitude shock in which the component of interest fails. The study showed that maximum energy spectra of low level shocks cannot simply be summed to estimate the energy response spectra of a high level, failure causing single shock. A power law relationship between the energy spectra of a low amplitude shock and the energy spectra of the high amplitude shock was postulated. A range of values of the exponent was empirically determined from test data and found to be consistent with the values typically used in high-cycle fatigue S-N curves.
Numerous domains, ranging from medical diagnostics to intelligence analysis, involve visual search tasks in which people must find and identify specific items within large sets of imagery. These tasks rely heavily on human judgment, making fully automated systems infeasible in many cases. Researchers have investigated methods for combining human judgment with computational processing to increase the speed at which humans can triage large image sets. One such method is rapid serial visual presentation (RSVP), in which images are presented in rapid succession to a human viewer. While viewing the images and looking for targets of interest, the participant’s brain activity is recorded using electroencephalography (EEG). The EEG signals can be time-locked to the presentation of each image, producing event-related potentials (ERPs) that provide information about the brain’s response to those stimuli. The participants’ judgments about whether or not each set of images contained a target and the ERPs elicited by target and non-target images are used to identify subsets of images that merit close expert scrutiny [1]. Although the RSVP/EEG paradigm holds promise for helping professional visual searchers to triage imagery rapidly, it may be limited by the nature of the target items. Targets that do not vary a great deal in appearance are likely to elicit useable ERPs, but more variable targets may not. In the present study, we sought to extend the RSVP/EEG paradigm to the domain of aviation security screening, and in doing so to explore the limitations of the technique for different types of targets. Professional Transportation Security Officers (TSOs) viewed bag X-rays that were presented using an RSVP paradigm. The TSOs viewed bursts of images containing 50 segments of bag X-rays that were presented for 100 ms each. Following each burst of images, the TSOs indicated whether or not they thought there was a threat item in any of the images in that set. EEG was recorded during each burst of images and ERPs were calculated by time-locking the EEG signal to the presentation of images containing threats and matched images that were identical except for the presence of the threat item. Half of the threat items had a prototypical appearance and half did not. We found that the bag images containing threat items with a prototypical appearance reliably elicited a P300 ERP component, while those without a prototypical appearance did not. These findings have implications for the application of the RSVP/EEG technique to real-world visual search domains.
Proceedings of the ASME Design Engineering Technical Conference
Bonney, Matthew S.; Kammer, Daniel C.; Brake, M.R.W.
The uncertainty of a system is usually quantified with the use of sampling methods such as Monte-Carlo or Latin hypercube sampling. These sampling methods require many computations of the model and may include re-meshing. The re-solving and re-meshing of the model is a very large computational burden. One way to greatly reduce this computational burden is to use a parameterized reduced order model. This is a model that contains the sensitivities of the desired results with respect to changing parameters such as Young's modulus. The typical method of computing these sensitivities is the use of finite difference technique that gives an approximation that is subject to truncation error and subtractive cancellation due to the precision of the computer. One way of eliminating this error is to use hyperdual numbers, which are able to generate exact sensitivities that are not subject to the precision of the computer. This paper uses the concept of hyper-dual numbers to parameterize a system that is composed of two substructures in the form of Craig-Bampton substructure representations, and combine them using component mode synthesis. The synthesis transformations using other techniques require the use of a nominal transformation while this approach allows for exact transformations when a perturbation is applied. This paper presents this technique for a planar motion frame and compares the use and accuracy of the approach against the true full system. This work lays the groundwork for performing component mode synthesis using hyper-dual numbers.
The potential for bias to affect the results of knowledge elicitation studies is well recognized. Researchers and knowledge engineers attempt to control for bias through careful selection of elicitation and analysis methods. Recently, the development of a wide range of physiological sensors, coupled with fast, portable and inexpensive computing platforms, has added an additional dimension of objective measurement that can reduce bias effects. In the case of an abductive reasoning task, bias can be introduced through design of the stimuli, cues from researchers, or omissions by the experts. We describe a knowledge elicitation methodology robust to various sources of bias, incorporating objective and cross-referenced measurements. The methodology was applied in a study of engineers who use multivariate time series data to diagnose mance of devices throughout the production lifecycle. For visual reasoning tasks, eye tracking is particularly effective at controlling for biases of omission by providing a record of the subject’s attention allocation.
Developers and security analysts have been using static analysis for a long time to analyze programs for defects and vulnerabilities. Generally a static analysis tool is run on the source code for a given program, flagging areas of code that need to be further inspected by a human analyst. These tools tend to work fairly well – every year they find many important bugs. These tools are more impressive considering the fact that they only examine the source code, which may be very complex. Now consider the amount of data available that these tools do not analyze. There are many additional pieces of information available that would prove useful for finding bugs in code, such as a history of bug reports, a history of all changes to the code, information about committers, etc. By leveraging all this additional data, it is possible to find more bugs with less user interaction, as well as track useful metrics such as number and type of defects injected by committer. This paper provides a method for leveraging development metadata to find bugs that would otherwise be difficult to find using standard static analysis tools. We showcase two case studies that demonstrate the ability to find new vulnerabilities in large and small software projects by finding new vulnerabilities in the cpython and Roundup open source projects.
With an abundance of scientific information in hand, what are the remaining geomechanics issues for a salt repository for heat-generating nuclear waste disposal? The context of this question pertains to the development of a license application, rather than an exploration of the entire breadth of salt research. The technical foundation supporting a licensed salt repository has been developed in the United States and Germany since the 1960s. Although the level of effort has been inconsistent and discontinuous over the years, site characterization activities, laboratory testing, field-scale experiments, and advanced computational capability provide information and tools required for a license application, should any nation make that policy decision. Ample scientific bases exist to develop a safety case in the event a site is identified and governing regulations promulgated. Some of the key remaining geomechanics issues pertain to application of advanced computational tools to the repository class of problems, refinement of constitutive models and their validation, reduction of uncertainty in a few areas, operational elements, and less tractable requirements that may arise from regulators and stakeholders. This realm of issues as they pertain to salt repositories is being addressed in various research, development and demonstration activities in the United States and Germany, including extensive collaborations. Many research areas such as constitutive models and performance of geotechnical barriers have industry applications beyond repositories. And, while esoteric salt-specific phenomenology and micromechanical processes remain of interest, they will not be reviewed here. The importance of addressing geomechanics issues and their associated prioritization are a matter of discussion, though the discriminating criterion for considerations in this paper is a demonstrable tie to the salt repository safety case.
A three dimensional time-domain model, based on Cummins equation, has been developed for an axisymmetric point absorbing wave energy converter (WEC) with an irregular cross section. This model incorporates a number of nonlinearities to accurately account for the dynamics of the device: hydrostatic restoring, motion constraints, saturation of the powertake-off force, and kinematic nonlinearities. Here, an interpolation model of the hydrostatic restoring reaction is developed and compared with a surface integral based method. The effects of these nonlinear hydrostatic models on device dynamics are explored by comparing predictions against those of a linear model. For the studied WEC, the interpolation model offers a large improvement over a linear model and is roughly two orders-of-magnitude less computationally expensive than the surface integral based method.
Radar Intelligence, Surveillance, and Reconnaissance (ISR) does not always involve cooperative or even friendly environments or targets. The environment in general, and an adversary in particular, may offer numerous characteristics and impeding techniques to diminish the effectiveness of a radar ISR sensor. These generally fall under the banner of jamming, spoofing, or otherwise interfering with the Electromagnetic (EM) signals required by the radar sensor. Consequently mitigation techniques are often prudent to retain efficacy of the radar sensor. We discuss in general terms a number of mitigation techniques.
The interaction of Cs adatoms with mono- or bi-layered graphene (MLG and BLG), either free-standing or on a SiO2 substrate, was investigated using density functional theory. The most stable adsorption sites for Cs are found to be hollow sites on both graphene sheets and graphene-veiled SiO2(0001). Larger dipole moments are created when a MLG-veiled SiO2(0001) substrate is used for adsorption of Cs atoms compared to the adsorption on free-standing MLG, due to charge transfer occurring between the MLG and the SiO2 substrate. For the adsorption of Cs on BLG-veiled SiO2(0001) substrate, these differences are smoothed out and the binding energies corresponding to different sites are nearly degenerate; smaller dipole moments created by the Cs adatoms on BLG compared to MLG are also predicted.
Visual search data describe people’s performance on the common perceptual problem of identifying target objects in a complex scene. Technological advances in areas such as eye tracking now provide researchers with a wealth of data not previously available. The goal of this work is to support researchers in analyzing this complex and multimodal data and in developing new insights into visual search techniques. We discuss several methods drawn from the statistics and machine learning literature for integrating visual search data derived from multiple sources and performing exploratory data analysis. We ground our discussion in a specific task performed by officers at the Transportation Security Administration and consider the applicability, likely issues, and possible adaptations of several candidate analysis methods.
A helium leakage detection system was modified to measure gas permeability on extracted cores of nearly impermeable rock. Here we use a Helium - Mass - Spectrometry - Permeameter (HMSP) to conduct a constant pressure, steady state flow test through a sample using helium gas. Under triaxial stress conditions, the HMSP can measure flow and estimate permeability of rocks and geomaterials down to the nanodarcy scale (10-21 m2). In this study, measurements of flow through eight shale samples under hydrostatic conditions were in the range of 10-7 to 10-9 Darcy. We extend this flow measurement technology by dynamically monitoring the release of helium from a helium saturated shale sample during a triaxial deformation experiment. The helium flow, initially extremely low, consistent with the low permeability of shale, is observed to increase in advance of volume strain increase during deformation of the shale. This is perhaps the result of microfracture development and flow path linkage through the microfractures within the shale. Once microfracturing coalescence initiates, there is a large increase in helium release and flow. This flow rate increase is likely the result of development of a macrofracture in the sample, a flow conduit, later confirmed by post-test observations of the deformed sample. The release rate (flow) peaks and then diminishes slightly during subsequent deformation; however the post deformation flow rate is considerably greater than that of undeformed shale.
Modern high performance computers connect hundreds of thousands of endpoints and employ thousands of switches. This allows for a great deal of freedom in the design of the network topology. At the same time, due to the sheer numbers and complexity involved, it becomes more challenging to easily distinguish between promising and improper designs. With ever increasing line rates and advances in optical interconnects, there is a need for renewed design methodologies that comprehensively capture the requirements and expose tradeoffs expeditiously in this complex design space. We introduce a systematic approach, based on Generalized Moore Graphs, allowing one to quickly gauge the ideal level of connectivity required for a given number of end-points and traffic hypothesis, and to collect insight on the role of the switch radix in the topology cost. Based on this approach, we present a methodology for the identification of Pareto-optimal topologies. We apply our method to a practical case with 25,000 nodes and present the results.
Performance at Transportation Security Administration (TSA) airport checkpoints must be consistently high to skillfully mitigate national security threats and incidents. To accomplish this, Transportation Security Officers (TSOs) must exceptionally perform in threat detection, interaction with passengers, and efficiency. It is difficult to measure the human attributes that contribute to high performing TSOs because cognitive ability such as memory, personality, and competence are inherently latent variables. Cognitive scientists at Sandia National Laboratories have developed a methodology that links TSOs’ cognitive ability to their performance. This paper discusses how the methodology was developed using a strict quantitative process, the strengths and weaknesses, as well as how this could be generalized to other non-TSA contexts. The scope of this project is to identify attributes that distinguished high and low TSO performance for the duties at the checkpoint that involved direct interaction with people going through the checkpoint.
In this paper we present a localized polynomial chaos expansion for partial differential equations (PDE) with random inputs. In particular, we focus on time independent linear stochastic problems with high dimensional random inputs, where the traditional polynomial chaos methods, and most of the existing methods, incur prohibitively high simulation cost. The local polynomial chaos method employs a domain decomposition technique to approximate the stochastic solution locally. In each subdomain, a subdomain problem is solved independently and, more importantly, in a much lower dimensional random space. In a postprocesing stage, accurate samples of the original stochastic problems are obtained from the samples of the local solutions by enforcing the correct stochastic structure of the random inputs and the coupling conditions at the interfaces of the subdomains. Overall, the method is able to solve stochastic PDEs in very large dimensions by solving a collection of low dimensional local problems and can be highly efficient. In this paper we present the general mathematical framework of the methodology and use numerical examples to demonstrate the properties of the method.
Optically pumped semiconductor disk lasers (SDLs) provide high beam quality with high average-power power at designer wavelengths. However, material choices are limited by the need for a distributed Bragg reflector (DBR), usually monolithically integrated with the active region. We demonstrate DBR-free SDL active regions, which have been lifted off and bonded to various transparent substrates. For an InGaAs multi-quantum well sample bonded to a diamond window heat spreader, we achieved CW lasing with an output power of 2 W at 1150 nm with good beam quality.
We employ both the effective medium approximation (EMA) and Bloch theory to compare the dispersion properties of semiconductor hyperbolic metamaterials (SHMs) at mid-infrared frequencies and metallic hyperbolic metamaterials (MHMs) at visible frequencies. This analysis reveals the conditions under which the EMA can be safely applied for both MHMs and SHMs. We find that the combination of precise nanoscale layering and the longer infrared operating wavelengths puts the SHMs well within the effective medium limit and, in contrast to MHMs, allows for the attainment of very high photon momentum states. In addition, SHMs allow for new phenomena such as ultrafast creation of the hyperbolic manifold through optical pumping. In particular, we examine the possibility of achieving ultrafast topological transitions through optical pumping which can photo-dope appropriately designed quantum wells on the femtosecond time scale.
We present an improved deterministic method for analyzing transport problems in random media. In the original method realizations were generated by means of a product quadrature rule; transport calculations were performed on each realization and the results combined to produce ensemble averages. In the present work we recognize that many of these realizations yield identical transport problems. We describe a method to generate only unique transport problems with the proper weighting to produce identical ensemble-averaged results at reduced computational cost. We also describe a method to ignore relatively unimportant realizations in order to obtain nearly identical results with further reduction in costs. Our results demonstrate that these changes allow for the analysis of problems of greater complexity than was practical for the original algorithm.
Sabotage of spent nuclear fuel casks remains a concern nearly forty years after attacks against shipment casks were first analyzed and has a renewed relevance in the post-9/11 environment. A limited number of full-scale tests and supporting efforts using surrogate materials, typically depleted uranium dioxide (DUO2), have been conducted in the interim to more definitively determine the source term from these postulated events. In all the previous studies, the postulated attack of greatest interest was by a conical shape charge (CSC) that focuses the explosive energy much more efficiently than bulk explosives. However, the validity of these large-scale results remain in question due to the lack of a defensible Spent Fuel Ratio (SFR), defined as the amount of respirable aerosol generated by an attack on a mass of spent fuel compared to that of an otherwise identical surrogate. Previous attempts to define the SFR in the 1980's have resulted in estimates ranging from 0.42 to 12 and include suboptimal experimental techniques and data comparisons. Because of the large uncertainty surrounding the SFR, estimates of releases from security-related events may be unnecessarily conservative. Credible arguments exist that the SFR does not exceed a value of unity. A defensible determination of the SFR in this lower range would greatly reduce the calculated risk associated with the transport and storage of spent nuclear fuel in dry cask systems. In the present work, the CTH shock physics code is used to simulate spent nuclear fuel (SNF) and DUO2 targets impacted by a CSC jet at an ambient temperature condition. These preliminary results are used to illustrate an approach to estimate the respirable release fraction for each type of material and ultimately, an estimate of the SFR.
In this paper we explore simulated responses of electromagnetic (EM) signals relative to in situ field surveys and quantify the effects that different values of conductivity in sea ice have on the EM fields. We compute EM responses of ice types with a three-dimensional (3-D) finite-volume discretization of Maxwell's equations and present 2-D sliced visualizations of their associated EM fields at discrete frequencies. Several interesting observations result: First, since the simulator computes the fields everywhere, each gridcell acts as a receiver within the model volume, and captures the complete, coupled interactions between air, snow, sea ice and sea water as a function of their conductivity; second, visualizations demonstrate how 1-D approximations near deformed ice features are violated. But the most important new finding is that changes in conductivity affect EM field response by modifying the magnitude and spatial patterns (i.e. footprint size and shape) of current density and magnetic fields. These effects are demonstrated through a visual feature we define as 'null lines'. Null line shape is affected by changes in conductivity near material boundaries as well as transmitter location. Our results encourage the use of null lines as a planning tool for better ground-truth field measurements near deformed ice types.
We investigate through numerical simulation the usefulness of DC resistivity data for characterizing subsurface fractures with elevated electrical conductivity by considering a geophysical experiment consisting of a grounded current source deployed in a steel cased borehole. In doing so, the borehole casing behaves electrically as a spatially extended line source, efficiently energizing the fractures with a steady current. Finite element simulations of this experiment for a horizontal well intersecting a small set of vertical fractures indicate that the fractures manifest electrically in (at least) two ways: a local perturbation in the electric potential proximal the fracture set, with limited far-field expression; and, an overall reduction in the electric potential along the entire length of borehole casing due to enhanced current flow through the fractures into the surrounding formation. The change in casing potential results in a measureable effect that can be observed far from fractures themselves, at distances where the local perturbations in the electric potential around the fractures are imperceptible. Under these conditions, our results suggest that far-field, time-lapse measurements of DC potentials surrounding a borehole casing can be reasonably interpreted by simple, linear inversion for a Coulomb charge distribution along the borehole path, including a local charge perturbation due to the fractures. Such an approach offers an inexpensive method for detecting and monitoring the time-evolution of electrically conducting fractures while ultimately providing an estimate of their effective conductivity - the latter providing an important measure independent of seismic methods on fracture shape, size, and hydraulic connectivity.
Recent synthetic advances have made available very monodisperse zincblende CdSe/CdS quantum dots having near-unity photoluminescence quantum yields. Because of the absence of nonradiative decay pathways, accurate values of the radiative lifetimes can be obtained from time-resolved PL measurements. Radiative lifetimes can also be obtained from the Einstein relations, using the static absorption spectra and the relative thermal populations in the angular momentum sublevels. One of the inputs into these calculations is the shell thickness, and it is useful to be able to determine shell thickness from spectroscopic measurements. We use an empirically corrected effective mass model to produce a "map" of exciton wavelength as a function of core size and shell thickness. These calculations use an elastic continuum model and the known lattice and elastic constants to include the e ffect of lattice strain on the band gap energy. The map is in agreement with the known CdSe sizing curve and with the shell thicknesses of zincblende core/shell particles obtained from TEM images. If selenium-sulfur diffusion is included and lattice strain is omitted from the calculation then the resulting map is appropriate for wurtzite CdSe/CdS quantum dots synthesized at high temperatures, and this map is very similar to one previously reported (J. Am. Chem. Soc. 2009, 131, 14299). Radiative lifetimes determined from time-resolved measurements are compared to values obtained from the Einstein relations, and found to be in excellent agreement. For a specific core size (2.64 nm diameter, in the present case), radiative lifetimes are found to decrease with increasing shell thickness. This is similar to the size dependence of one-component CdSe quantum dots and in contrast to the size dependence in type-II quantum dots. (Graph Presented).
Interference and interference mitigation techniques degrade synthetic aperture radar (SAR) coherent data products. Radars utilizing stretch processing present a unique challenge for many mitigation techniques because the interference signal itself is modified through stretch processing from its original signal characteristics. Many sources of interference, including constant tones, are only present within the fast-time sample data for a limited number of samples, depending on the radar and interference bandwidth. Adaptive filtering algorithms to estimate and remove the interference signal that rely upon assuming stationary interference signal characteristics can be ineffective. An effective mitigation method, called notching, forces the value of the data samples containing interference to zero. However, as the number of data samples set to zero increases, image distortion and loss of resolution degrade both the image product and any second order image products. Techniques to repair image distortions,1 are effective for point-like targets. However, these techniques are not designed to model and repair distortions in SAR image terrain. Good terrain coherence is important for SAR second order image products because terrain occupies the majority of many scenes. For the case of coherent change detection it is the terrain coherence itself that determines the quality of the change detection image. This paper proposes an unique equalization technique that improves coherence over existing notching techniques. First, the proposed algorithm limits mitigation to only the samples containing interference, unlike adaptive filtering algorithms, so the remaining samples are not modified. Additionally, the mitigation adapts to changing interference power such that the resulting correction equalizes the power across the data samples. The result is reduced distortion and improved coherence for the terrain. SAR data demonstrates improved coherence from the proposed equalization correction over existing notching methods for chirped interference sources.
The dynamic wake meandering model (DWM) is a common wake model used for fast prediction of wind farm power and loads. This model is compared to higher fidelity vortex method (VM) and actuator line large eddy simulation (AL-LES) model results. By looking independently at the steady wake deficit model of DWM, and performing a more rigorous comparison than averaged result comparisons alone can produce, the models and their physical processes can be compared. The DWM and VM results of wake deficit agree best in the mid-wake region due to the consistent recovery prior to wake breakdown predicted in the VM results. DWM and AL-LES results agree best in the far-wake due to the low recovery of the laminar flow field AL-LES simulation. The physical process of wake recovery in the DWM model differed from the higher fidelity models and resulted solely from wake expansion downstream, with no momentum recovery up to 10 diameters. Sensitivity to DWM model input boundary conditions and their effects are shown, with greatest sensitivity to the rotor loading and to the turbulence model.
ASME 2015 9th International Conference on Energy Sustainability, ES 2015, collocated with the ASME 2015 Power Conference, the ASME 2015 13th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2015 Nuclear Forum
Falling particle receivers are being evaluated as an alternative to conventional fluid-based solar receivers to enable higher temperatures and higher efficiency power cycles with direct storage for concentrating solar power applications. This paper presents studies of the particle mass flow rate, velocity, particle-curtain opacity and density, and other characteristics of free-falling ceramic particles as a function of different discharge slot apertures. The methods to characterize the particle flow are described, and results are compared to theoretical and numerical models for unheated conditions.
ASME 2015 9th International Conference on Energy Sustainability, ES 2015, collocated with the ASME 2015 Power Conference, the ASME 2015 13th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2015 Nuclear Forum
This paper evaluates cost and performance tradeoffs of alternative supercritical carbon dioxide (s-CO2) closed-loop Brayton cycle configurations with a concentrated solar heat source. Alternative s-CO2 power cycle configurations include simple, recompression, cascaded, and partial cooling cycles. Results show that the simple closed-loop Brayton cycle yielded the lowest power-block component costs while allowing variable temperature differentials across the s-CO2 heating source, depending on the level of recuperation. Lower temperature differentials led to higher sensible storage costs, but cycle configurations with lower temperature differentials (higher recuperation) yielded higher cycle efficiencies and lower solar collector and receiver costs. The cycles with higher efficiencies (simple recuperated, recompression, and partial cooling) yielded the lowest overall solar and power-block component costs for a prescribed power output.
The complex coherence function describes information that is necessary to create maps from interferometric synthetic aperture radar (InSAR). This coherence function is complicated by building layover. This paper presents a mathematical model for this complex coherence in the presence of building layover and shows how it can describe intriguing phenomena observed in real interferometric SAR data.
Thermoelectric (TE) generators have very important applications, such as emerging automotive waste heat recovery and cooling applications. However, reliable transport properties characterization techniques are needed in order to scale-up module production and thermoelectric generator design DOE round-robin testing found that literature values for figure of merit (ZT) are sometimes not reproducible in part for the lack of standardization of transport properties measurements. In Sandia National Laboratories (SNL), we have been optimizing transport properties measurements techniques of TE materials and modules. We have been using commercial and custom-built instruments to analyze the perfomance of TE materials and modules We developed a reliable procedure to measure thermal conductivity, seebeck coefficient and resistivity of TE materials to calculate the ZT as function of temperature. We use NIST standards to validate our procedures and measure multiple samples of each specific material to establish consistency. Using these developed thermoelectric capabilities, we studied transport properties of BizTe, based alloys diermal aged up to 2 years. Parallel with analytical and microscopy studies, we correlated transport properties changes with chemical changes. Also, we have developed a resistance mApplng setup to measure the contact resistance of Au contacts on TE materials and TE modules as a whole in a non-destnictive way. The development of novel but reliable characterization techniques has been fundamental to better understand TE materials as fimction of aging hme, temperature and environmental conditions.
High temperature solid state sodium (23Na) magic angle spinning (MAS) NMR spin lattice relaxation times (T1) were evaluated for a series of NASICON (Na3Zr2PS12O12) materials to directly determine Na jump rates. Simulations of the Ti temperature variations that incorporated distributions in Na jump activation energies, or distribution of jump rates, improved the agreement with experiment. The 23Na NMR T1 relaxation results revealed that distributions in the Na dynamics were present for all of the NASICON materials investigated here. The 23Na relaxation experiments also showed that small differences in material composition and/or changes in the processing conditions impacted the distributions in the Na dynamics. The extent of the distribution was related to the presence of a disordered or glassy phosphate phase present in these different sol-gel processed materials. The 23Na NMR T1 relaxation experiments are a powerful tool to directly probing Na jump dynamics and provide additional molecular level details that could impact transport phenomena.
Measurements are presented from a two-beam structure with several bolted interfaces in order to characterize the nonlinear damping introduced by the joints. The measurements (all at force levels below macroslip) reveal that each underlying mode of the structure is well approximated by a single degree-of-freedom (SDOF) system with a nonlinear mechanical joint. At low enough force levels, the measurements show dissipation that scales as the second power of the applied force, agreeing with theory for a linear viscously damped system. This is attributed to linear viscous behavior of the material and/or damping provided by the support structure. At larger force levels, the damping is observed to behave nonlinearly, suggesting that damping from the mechanical joints is dominant. A model is presented that captures these effects, consisting of a spring and viscous damping element in parallel with a four-parameter Iwan model. The parameters of this model are identified for each mode of the structure and comparisons suggest that the model captures the stiffness and damping accurately over a range of forcing levels.
A radome, or radar dome, protects a radar system from exposure to the elements. Unfortunately, radomes can affect the radiation pattern of the enclosed antenna. The co-design of a platform"™s radome and radar is ideal to mitigate any deleterious effects of the radome. However, maintaining structural integrity and other platform flight requirements, particularly when integrating a new radar onto an existing platform, often limits radome electrical design choices. Radars that rely heavily on phase measurements such as monopulse, interferometric, or coherent change detection (CCD) systems require particular attention be paid to components, such as the radome, that might introduce loss and phase variations as a function of the antenna scan angle. Material properties, radome wall construction, overall dimensions, and shape characteristics of a radome can impact insertion loss and phase delay, antenna beamwidth and sidelobe level, polarization, and ultimately the impulse response of the radar, among other things, over the desired radar operating parameters. The precision-guided munitions literature has analyzed radome effects on monopulse systems for well over half a century. However, to the best of our knowledge, radome-induced errors on CCD performance have not been described. The impact of radome material and wall construction, shape, dimensions, and antenna characteristics on CCD is examined herein for select radar and radome examples using electromagnetic simulations.
Proceedings of SPIE - The International Society for Optical Engineering
Johnson, Timothy J.; Sweet, Lucas E.; Meier, David E.; Mausolf, Edward J.; Kim, Eunja; Weck, Philippe F.; Buck, Edgar C.; Mcnamara, Bruce K.
Uranyl nitrate is a key species in the nuclear fuel cycle, but is known to exist in different states of hydration, including the hexahydrate [UO2(NO3)2(H2O)6] (UNH) and the trihydrate [UO2(NO3)2(H2O)3] (UNT) forms. Their stabilities depend on both relative humidity and temperature. Both phases have previously been studied by infrared transmission spectroscopy, but the data were limited by both instrumental resolution and the ability to prepare the samples as pellets without desiccating it. We report time-resolved infrared (IR) measurements using an integrating sphere that allow us to observe the transformation from the hexahydrate to the trihydrate simply by flowing dry nitrogen gas over the sample. Hexahydrate samples were prepared and confirmed via known XRD patterns, then measured in reflectance mode. The hexahydrate has a distinct uranyl asymmetric stretch band at 949.0 cm-1 that shifts to shorter wavelengths and broadens as the sample dehydrates and recrystallizes to the trihydrate, first as a blue edge shoulder but ultimately resulting in a doublet band with reflectance peaks at 966 and 957 cm-1. The data are consistent with transformation from UNH to UNT since UNT has two non-equivalent UO22+ sites. The dehydration of UO2(NO3)2(H2O)6 to UO2(NO3)2(H2O)3 is both a morphological and structural change that has the lustrous lime green crystals changing to the dull greenish yellow of the trihydrate. Crystal structures and phase transformation were confirmed theoretically using DFT calculations and experimentally via microscopy methods. Both methods showed a transformation with two distinct sites for the uranyl cation in the trihydrate, as opposed to a single crystallographic site in the hexahydrate.
The efficiency of discrete-ordinates transport sweeps depends on the scheduling algorithm, domain decomposition, the problem to be solved, and the computational platform. Sweep scheduling algorithms may be categorized by their approach to several issues. In this paper we examine the strategy of domain overloading for mesh partitioning as one of the components of such algorithms. In particular, we extend the domain overloading strategy, previously defined and analyzed for structured meshes, to the general case of unstructured meshes. We also present computational results for both the structured and unstructured domain overloading cases. We find that an appropriate amount of domain overloading can greatly improve the efficiency of parallel sweeps for both structured and unstructured partitionings of the test problems examined on up to 105 processor cores.
The objective of this study was to explore an approach for measuring fatigue crack growth rates (da/dN) for Cr-Mo pressure vessel steels in high-pressure hydrogen gas over a broad cyclic stress intensity factor (ΔK) range while limiting test duration, which could serve as an alternative to the method prescribed in ASME BPVC VIII-3, Article KD-10. Fatigue crack growth rates were measured for SA-372 Grade J and 34CrMo4 steels in hydrogen gas as a function of ΔK, loadcycle frequency (f), and gas pressure. The da/dN vs. ΔK relationships measured for the Cr-Mo steels in hydrogen gas at 10 Hz indicate that capturing data at lower ΔK is valuable when these relationships serve as inputs into design-life analyses of hydrogen pressure vessels, since in this ΔK range crack growth rates in hydrogen gas approach rates in air. The da/dN vs. f data measured for the Cr-Mo steels in hydrogen gas at selected constant-ΔK levels demonstrate that crack growth rates at 10 Hz do not represent upper-bound behavior, since da/dN generally increases as f decreases. Consequently, although fatigue crack growth testing at 10 Hz can efficiently measure da/dN over a wide ΔK range, these da/dN vs. ΔK relationships at 10 Hz cannot be considered reliable inputs into design-life analyses. A possible hybrid approach to efficiently establishing the fatigue crack growth rate relationship in hydrogen gas without compromising data quality is to measure the da/dN vs. ΔK relationship at 10 Hz and then apply a correction based on the da/dN vs. f data. The reliability of such a hybrid approach depends on adequacy of the da/dN vs. f data, i.e., the data are measured at appropriate constant-ΔK levels and the data include upper-bound crack growth rates.
The Department of Energy (DOE) is laying the groundwork for implementing the Administration's Strategy for the Management and Disposal of Used Nuclear Fuel and High-Level Radioactive Waste, which calls for a consent-based siting process. Potential destinations for an interim storage facility or repository have yet to be identified. The purpose of this study is to evaluate how planning for future transportation of spent nuclear fuel as part of a waste management system may be affected by different choices and strategies. The transportation system is modeled using TOM (Transportation Operations Model), a computer code developed at the Oak Ridge National Laboratory (ORNL). The simulations include scenarios with and without an interim storage facility (ISF) and employing different at-reactor management practices. Various operational start times for the ISF and repository were also considered. The results of the cost analysis provide Rough Order of Magnitude (ROM) capital, operational, and maintenance costs of the transportation system and the corresponding spending profiles as well as information regarding the size of the transportation fleet, distance traveled (consist and cask miles), and fuel age and burnup during the transportation. This study provides useful insights regarding the role of the transportation as an integral part of the waste management system.
For long-term storage, spent nuclear fuel (SNF) is placed in dry storage cask systems, commonly consisting of welded stainless steel containers enclosed in ventilated cement or steel overpacks. At near-marine sites, failure by chloride-induced stress corrosion cracking (SCC) due to deliquescence of deposited salt aerosols is a major concern. This paper presents a preliminary probabilistic performance assessment model to assess canister penetration by SCC. The model first determines whether conditions for salt deliquescence are present at any given location on the canister surface, using an abstracted waste package thermal model and site-specific weather data (ambient temperature and absolute humidity). As the canister cools and aqueous conditions become possible, corrosion is assumed to initiate and is modeled as pitting (initiation and growth). With increasing penetration, pits convert to SCC and a crack growth model is implemented. The SCC growth model includes rate dependencies on temperature and crack tip stress intensity factor. The amount of penetration represents the summed effect of corrosion during time steps when aqueous conditions are predicted to occur. Model results and sensitivity analyses provide information on the impact of model assumptions and parameter values on predicted storage canister performance, and provide guidance for further research to reduce uncertainties.
The impact of automation on human performance has been studied by human factors researchers for over 35 years. One unresolved facet of this research is measurement of the level of automation across and within engineered systems. Repeatable methods of observing, measuring and documenting the level of automation are critical to the creation and validation of generalized theories of automation's impact on the reliability and resilience of human-in-the-loop systems. Numerous qualitative scales for measuring automation have been proposed. However these methods require subjective assessments based on the researcher's knowledge and experience, or through expert knowledge elicitation involving highly experienced individuals from each work domain. More recently, quantitative scales have been proposed, but have yet to be widely adopted, likely due to the difficulty associated with obtaining a sufficient number of empirical measurements from each system component. Our research suggests the need for a quantitative method that enables rapid measurement of a system's level of automation, is applicable across domains, and can be used by human factors practitioners in field studies or by system engineers as part of their technical planning processes. In this paper we present our research methodology and early research results from studies of electricity grid distribution control rooms. Using a system analysis approach based on quantitative measures of level of automation, we provide an illustrative analysis of select grid modernization efforts. This measure of the level of automation can be displayed as either a static, historical view of the system's automation dynamics (the dynamic interplay between human and automation required to maintain system performance) or it can be incorporated into real-time visualization systems already present in control rooms.
This paper describes technical, logistical, and sociopolitical factors to be considered in the development of guidelines for siting a facility for deep borehole disposal of radioactive waste. Technical factors include geological, hydro-geochemical, and geophysical characteristics that are related to the suitability of the site for drilling and borehole construction, waste emplacement activities, waste isolation, and long-term safety of the deep borehole disposal system. Logistical factors to be considered during site selection include: The local or regional availability of drilling contractors (equipment, services, and materials) capable of drilling a large-diameter borehole to approximately 5 km depth; the legal and regulatory requirements associated with drilling, construction of surface facilities, waste handling and emplacement, and postclosure safety; and access to transportation systems. Social and political factors related to site selection include the distance from population centers and the support or opposition of local and state entities and other stakeholders to the facility and its operations. These considerations are examined in the context of the siting process and guidelines for a deep borehole field test, designed to evaluate the feasibility of siting and operating a deep borehole disposal facility.
Options for disposal of the spent nuclear fuel and high level radioactive waste that are projected to exist in the United States in 2048 were studied. The options included four different disposal concepts: mined repositories in salt, clay/shale rocks, and crystalline rocks; and deep boreholes in crystalline rocks. Some of the results of this study are that all waste forms, with the exception of untreated sodium-bonded spent nuclear fuel, can be disposed of in any of the mined disposal concepts, although with varying degrees of confidence; salt allows for more flexibility in managing high-heat waste in mined repositories than other media; small waste forms are potentially attractive candidates for deep borehole disposal; and disposal of commercial SNF in existing dual-purpose canisters is potentially feasible but could pose significant challenges both in repository operations and in demonstrating confidence in long-term performance. Questions addressed by this study include: is a " 'one-size-fits-all ' repository a good strategic option for disposal?" and "do some disposal concepts perform significantly better with or without specific waste types or forms? " The study provides the bases for answering these questions by evaluating potential impacts of waste forms on the feasibility and performance of representative generic concepts for geologic disposal.
Sabotage of spent nuclear fuel casks remains a concern nearly forty years after attacks against shipment casks were first analyzed and has a renewed relevance in the post-9/11 environment. A limited number of full-scale tests and supporting efforts using surrogate materials, typically depleted uranium dioxide (DUO2), have been conducted in the interim to more definitively determine the source term from these postulated events. In all the previous studies, the postulated attack of greatest interest was by a conical shape charge (CSC) that focuses the explosive energy much more efficiently than bulk explosives. However, the validity of these large-scale results remain in question due to the lack of a defensible Spent Fuel Ratio (SFR), defined as the amount of respirable aerosol generated by an attack on a mass of spent fuel compared to that of an otherwise identical surrogate. Previous attempts to define the SFR in the 1980's have resulted in estimates ranging from 0.42 to 12 and include suboptimal experimental techniques and data comparisons. Because of the large uncertainty surrounding the SFR, estimates of releases from security-related events may be unnecessarily conservative. Credible arguments exist that the SFR does not exceed a value of unity. A defensible determination of the SFR in this lower range would greatly reduce the calculated risk associated with the transport and storage of spent nuclear fuel in dry cask systems. In the present work, the CTH shock physics code is used to simulate spent nuclear fuel (SNF) and DUO2 targets impacted by a CSC jet at an ambient temperature condition. These preliminary results are used to illustrate an approach to estimate the respirable release fraction for each type of material and ultimately, an estimate of the SFR.
Current techniques for building detection in Synthetic Aperture Radar (SAR) imagery can be computationally expensive and/or enforce stringent requirements for data acquisition. We present a technique that is effective and efficient at determining an approximate building location from multi-pass single-pol SAR imagery. This approximate location provides focus-of-attention to specific image regions for subsequent processing. The proposed technique assumes that for the desired image, a preprocessing algorithm has detected and labeled bright lines and shadows. Because we observe that buildings produce bright lines and shadows with predetermined relationships, our algorithm uses a graph clustering technique to find groups of bright lines and shadows that create a building. The nodes of the graph represent bright line and shadow regions, while the arcs represent the relationships between the bright lines and shadow. Constraints based on angle of depression and the relationship between connected bright lines and shadows are applied to remove unrelated arcs. Once the related bright lines and shadows are grouped, their locations are combined to provide an approximate building location. Experimental results are presented to demonstrate the outcome of this technique.
Stochastic media transport problems have long posed challenges for accurate modeling. Brute force Monte Carlo or deterministic sampling of realizations can be expensive in order to achieve the desired accuracy. The well-known Levermore-Pomraning (LP) closure is very simple and inexpensive, but is inaccurate in many circumstances. We propose a generalization to the LP closure that may help bridge the gap between the two approaches. Our model consists of local calculations to approximately determine the relationship between ensemble-averaged angular fluxes and the corresponding averages at material interfaces. The expense and accuracy of the method are related to how "local" the model is and how much local detail it contains. We show through numerical results that our approach is more accurate than LP for benchmark problems, provided that we capture enough local detail. Thus we identify two approaches to using ensemble calculations for stochastic media calculations: direct averaging of ensemble results for transport quantities of interest, or indirect use via a generalized LP equation to determine those same quantities; in some cases the latter method is more efficient. However, the method is subject to creating ill-posed problems if insufficient local detail is included in the model.
A Monte Carlo solution method for the system of deterministic equations arising in the application of stochastic collocation (SCM) and stochastic Galerkin (SGM) methods in radiation transport computations with uncertainty is presented for an arbitrary number of materials each containing two uncertain random cross sections. Moments of the resulting random flux are calculated using an intrusive and a non-intrusive Monte Carlo based SCM and two different SGM implementations each with two different truncation methods and compared to the brute force Monte Carlo sampling approach. For the intrusive SCM and SGM, a single set of particle histories is solved and weight adjustments are used to produce flux moments for the stochastic problem. Memory and runtime scaling of each method is compared for increased complexity in stochastic dimensionality and moment truncation. Results are also compared for efficiency in terms of a statistical figure-of-merit. The memory savings for the total-order truncation method prove significant over the full-tensor-product truncation. Scaling shows relatively constant cost per moment calculated of SCM and tensor-product SGM. Total-order truncation may be worthwhile despite poorer runtime scaling by achieving better accuracy at lower cost. The figure-of-merit results show that all of the intrusive methods can improve efficiency for calculating low-order moments, but the intrusive SCM approach is the most efficient for calculating high-order moments.
In this paper, we describe the use of various methods of one-dimensional spectral compression by variable selection as well as principal component analysis (PCA) for compressing multi-dimensional sets of spectral data. We have examined methods of variable selection such as wavelength spacing, spectral derivatives, and spectral integration error. After variable selection, reduced transmission spectra must be decompressed for use. Here we examine various methods of interpolation, e.g., linear, cubic spline and piecewise cubic Hermite interpolating polynomial (PCHIP) to recover the spectra prior to estimating at-sensor radiance. Finally, we compressed multi-dimensional sets of spectral transmittance data from moderate resolution atmospheric transmission (MODTRAN) data using PCA. PCA seeks to find a set of basis spectra (vectors) that model the variance of a data matrix in a linear additive sense. Although MODTRAN data are intricate and are used in nonlinear modeling, their base spectra can be reasonably modeled using PCA yielding excellent results in terms of spectral reconstruction and estimation of at-sensor radiance. The major finding of this work is that PCA can be implemented to compress MODTRAN data with great effect, reducing file size, access time and computational burden while producing high-quality transmission spectra for a given set of input conditions.
Researchers at Sandia National Laboratories are integrating qualitative and quantitative methods from anthropology, human factors and cognitive psychology in the study of military and civilian intelligence analyst workflows in the United States’ national security community. Researchers who study human work processes often use qualitative theory and methods, including grounded theory, cognitive work analysis, and ethnography, to generate rich descriptive models of human behavior in context. In contrast, experimental psychologists typically do not receive training in qualitative induction, nor are they likely to practice ethnographic methods in their work, since experimental psychology tends to emphasize generalizability and quantitative hypothesis testing over qualitative description. However, qualitative frameworks and methods from anthropology, sociology, and human factors can play an important role in enhancing the ecological validity of experimental research designs.
We present simulation results that show circularly polarized light persists through scattering environments better than linearly polarized light. Specifically, we show persistence is enhanced through many scattering events in an environment with a size parameter representative of advection fog at infrared wavelengths. Utilizing polarization tracking Monte Carlo simulations we show a larger persistence benefit for circular polarization versus linear polarization for both forward and backscattered photons. We show the evolution of the incident polarization states after various scattering events which highlight the mechanism leading to circular polarization's superior persistence.
The construction of the Grand Ethiopian Renaissance Dam (GERD) has generated tensions between Egypt and Ethiopia over control of the Nile River in Northern Africa. However, tensions within Egypt have also been pronounced, leading up to and following the Arab Spring uprising of 2011. This study used the Behavior Influence Assessment (BIA) framework to simulate a dynamic hypothesis regarding how tensions within Egypt may evolve given the impacts of the GERD. Primarily, we addressed the interplay between four parties over an upcoming ten-year period: the Egyptian Regime, the Military-Elite, the Militant population, and the non-Militant population. The core tenant of the hypothesis is that rising food prices was a strong driver to the unrest leading up to the Arab Spring events and that this same type of economic stress could be driven by the GERD—albeit with different political undertones. Namely, the GERD offers the Regime a target for inciting nationalism, and while this may buy the regime time to fix the underlying economic impacts, ultimately there exists a tipping point beyond which exponentially increasing unrest is unavoidable without implementing strong measures, such as state militarization.
Attitude diffusion is when "attitudes" (general, relatively enduring evaluative responses to a topic) spread through a population. Attitudes play an incredibly important role in human decision making and are a critical part of social psychology. However, existing models of diffusion do not account for key differentiating aspects of attitudes. We develop the "Multi-Agent, Multi-Attitude" (MAMA) model which incorporates several of these key factors: (1) multiple, interacting attitudes; (2) social influence between individuals; and (3) media influence. All three components have strong support from the social science community. Using the MAMA model, we study influence maximization in a attitude diffusion setting where media influence is possible - we show that strategic manipulation of the media can lead to statistically significant decreases in diffusion of attitudes.
Thermoelectric (TE) generators have very important applications, such as emerging automotive waste heat recovery and cooling applications. However, reliable transport properties characterization techniques are needed in order to scale-up module production and thermoelectric generator design DOE round-robin testing found that literature values for figure of merit (ZT) are sometimes not reproducible in part for the lack of standardization of transport properties measurements. In Sandia National Laboratories (SNL), we have been optimizing transport properties measurements techniques of TE materials and modules. We have been using commercial and custom-built instruments to analyze the perfomance of TE materials and modules We developed a reliable procedure to measure thermal conductivity, seebeck coefficient and resistivity of TE materials to calculate the ZT as function of temperature. We use NIST standards to validate our procedures and measure multiple samples of each specific material to establish consistency. Using these developed thermoelectric capabilities, we studied transport properties of BizTe, based alloys diermal aged up to 2 years. Parallel with analytical and microscopy studies, we correlated transport properties changes with chemical changes. Also, we have developed a resistance mApplng setup to measure the contact resistance of Au contacts on TE materials and TE modules as a whole in a non-destnictive way. The development of novel but reliable characterization techniques has been fundamental to better understand TE materials as fimction of aging hme, temperature and environmental conditions.
A microscale model of the brain was developed in order to understand the details of intracranial fluid cavitation and the damage mechanisms associated with cavitation bubble collapse due to blast-induced traumatic brain injury (TBI). Our macroscale model predicted cavitation in regions of high concentration of cerebrospinal fluid (CSF) and blood. The results from this macroscale simulation directed the development of the microscale model of the superior sagittal sinus (SSS) region. The microscale model includes layers of scalp, skull, dura, superior sagittal sinus, falx, arachnoid, subarachnoid spacing, pia, and gray matter. We conducted numerical simulations to understand the effects of a blast load applied to the scalp with the pressure wave propagating through the layers and eventually causing the cavitation bubbles to collapse. Collapse of these bubbles creates spikes in pressure and von Mises stress downstream from the bubble locations. We investigate the influence of cavitation bubble size, compressive wave amplitude, and internal bubble pressure. The results indicate that these factors may contribute to a greater downstream pressure and von Mises stress which could lead to significant tissue damage.
We describe the computational simulations and damage assessments that we provided in support of a tabletop exercise (TTX) at the request of NASA's Near-Earth Objects Program Office. The overall purpose of the exercise was to assess leadership reactions, information requirements, and emergency management responses to a hypothetical asteroid impact with Earth. The scripted exercise consisted of discovery, tracking, and characterization of a hypothetical asteroid; inclusive of mission planning, mitigation, response, impact to population, infrastructure and GDP, and explicit quantification of uncertainty. Participants at the meeting included representatives of NASA, Department of Defense, Department of State, Department of Homeland Security/Federal Emergency Management Agency (FEMA), and the White House. The exercise took place at FEMA headquarters. Sandia's role was to assist the Jet Propulsion Laboratory (JPL) in developing the impact scenario, to predict the physical effects of the impact, and to forecast the infrastructure and economic losses. We ran simulations using Sandia's CTH hydrocode to estimate physical effects on the ground, and to produce contour maps indicating damage assessments that could be used as input for the infrastructure and economic models. We used the FASTMap tool to provide estimates of infrastructure damage over the affected area, and the REAcct tool to estimate the potential economic severity expressed as changes to GDP (by nation, region, or sector) due to damage and short-term business interruptions.
Transmission electron microscopy (TEM) is a valuable methodology for investigating radiation-induced microstructural changes and elucidating the underlying mechanisms involved in the aging and degradation of nuclear reactor materials. However, the use of electrons for imaging may result in several inadvertent effects that can potentially change the microstructure and mechanisms active in the material being investigated. In this study, in situ TEM characterization is performed on nanocrystalline nickel samples under self-ion irradiation and post irradiation annealing. During annealing, voids are formed around 200 °C only in the area illuminated by the electron beam. Based on diffraction patterns analyses, it is hypothesized that the electron beam enhanced the growth of a NiO layer resulting in a decrease of vacancy mobility during annealing. The electron beam used to investigate self-ion irradiation ultimately significantly affected the type of defects formed and the final defect microstructure.
The simplified spherical harmonics (SPn) approximation to the radiative transport equation (RTE) is a computationally efficient deterministic solution method that may be derived either as an asymptotic correction to the diffusion approximation or as a 3D analog to the 1D spherical harmonics (Pn) or discrete ordinates (Sn) approximations. It is used to approximate the effects of participating media radiation. In order to trust the output of a given implementation for a high consequence application, code verification activities must be undertaken to build confidence in the results generated. The method of manufactured solutions is a widely accepted code verification technique in which a solution is assumed and arbitrary source terms are derived such that the code should converge to the prescribed solution. This convergence rate is then confirmed. In this paper we consider the set of coupled PDEs representative of radiation/conduction problems. The RTE is approximated using the “canonical” SPn equations with Mark boundary conditions. All boundaries are diffuse and emissivities range from 0 to 1. A set of manufactured solutions are presented for 1D-planar, 2D-planar, 2D-axisymmetric, and 3D-radially symmetric geometries. These manufactured solutions are used to verify the convergence rate of the conduction and simplified spherical harmonics approximations implemented in Sierra Aria, a highly scalable thermal analysis code.
We examine the scalability of the recently developed Albany/FELIX finite-element based code for the first-order Stokes momentum balance equations for ice flow. We focus our analysis on the performance of two possible preconditioners for the iterative solution of the sparse linear systems that arise from the discretization of the governing equations: (1) a preconditioner based on the incomplete LU (ILU) factorization, and (2) a recently-developed algebraic multigrid (AMG) preconditioner, constructed using the idea of semi-coarsening. A strong scalability study on a realistic, high resolution Greenland ice sheet problem reveals that, for a given number of processor cores, the AMG preconditioner results in faster linear solve times but the ILU preconditioner exhibits better scalability. A weak scalability study is performed on a realistic, moderate resolution Antarctic ice sheet problem, a substantial fraction of which contains floating ice shelves, making it fundamentally different from the Greenland ice sheet problem. Here, we show that as the problem size increases, the performance of the ILU preconditioner deteriorates whereas the AMG preconditioner maintains scalability. This is because the linear systems are extremely ill-conditioned in the presence of floating ice shelves, and the ill-conditioning has a greater negative effect on the ILU preconditioner than on the AMG preconditioner.
We demonstrate a Bayesian method that can be used to calibrate computationally expensive 3D RANS models with complex response surfaces. Such calibrations, conditioned on experimental data, can yield turbulence model parameters as probability density functions (PDF), concisely capturing the uncertainty in the estimation. Methods such as Markov chain Monte Carlo construct the PDF by sampling, and consequently a quick-running surrogate is used instead of the RANS simulator. The surrogate can be very difficult to design if the model’s response i.e., the dependence of the calibration variable (the observable) on the parameters being estimated is complex. We show how the training data used to construct the surrogate models can also be employed to isolate a promising and physically realistic part of the parameter space, within which the response is well-behaved and easily modeled. We design a classifier, based on treed linear models, to model the “well-behaved region”. This classifier serves as a prior in a Bayesian calibration study aimed at estimating 3 k-ε parameters C = (Cμ, Cε2, Cε1) from experimental data of a transonic jet-in-crossflow interaction. The robustness of the calibration is investigated by checking its predictions of variables not included in the calibration data. We also check the limit of applicability of the calibration by testing at an off-calibration point.
Reducing contamination is essential for producing optical coatings with high resistance to laser damage. One aspect of this principle is to make every effort to limit long interruptions during the coating's deposition. Otherwise, contamination may accumulate during the pause and become embedded in the coating after the deposition is restarted, leading to a lower laser-induced damage threshold (LIDT). However, pausing a deposition is sometimes unavoidable, despite our best efforts. For example, a sudden hardware or software glitch may require hours or even overnight to solve. In order to broaden our understanding of the role of embedded contamination on LIDT, and determine whether a coating deposited under such non-ideal circumstances could still be acceptable, this study explores how halting a deposition overnight impacts the LIDT, and whether ion cleaning can be used to mitigate any negative effects on the LIDT. The coatings investigated are a beam splitter design for high reflection at 1054 nm and high transmission at 527 nm, at 22.5° angle of incidence in S-polarization. LIDT tests were conducted in the nanosecond regime.
This paper presents a study of operational and abandoned large-diameter caverns and their long-term implications for oil storage facilities in domal salt. Two caverns at the U.S. Strategic Petroleum Reserves West Hackberry site, Caverns 6 and 9, present concerns due to their large diameters, unusual shapes and close proximity to each other. The Bryan Mound site has three caverns whose unusual shapes and dimensions have caused concerns about cavern collapse, sinkhole formation, and loss of accessibility to stored oil. This report presents a case study of how historical field data, computational geomechanical analyses, and the implementation of new instrumentation and historical data analyses may be used to develop site operation and monitoring plans for these caverns.
A new multi-year effort has been launched by the Department of Energy to validate the extent to which control strategies can increase the power produced by resonant wave energy conversion (WEC) devices. This paper describes the design of a WEC device to be employed by this program in the development and assessment of WEC control strategies. The operational principle of the device was selected to provide a test-bed for control strategies, in which a specific control strategies effectiveness and the parameters on which its effectiveness depends can be empirically determined. Numerical design studies were employed to determine the device geometry, so as to maximize testing opportunities in the Maneuvering and Seakeeping (MASK) Basin at the Naval Surface Warfare Centers David Taylor Model Basin. Details on the physical model including specific components and model fabrication methodologies are presented. Finally the quantities to be measured and the mechanisms of measurement are listed.
The process nuclear criticality accident that occurred at the Mayak Production Association (Chelyabinsk-40) on January 2, 1958 involving a vessel of uranyl nitrate solution claimed the lives of three workers and left a fourth worker with continuing health problems. There are a myriad of uncertain parameters involved with this accident: What was the molarity of the solution? How much solution was in the vessel at the time of the accident? In what position was the vessel and the solution when it went critical? How important was the impact of reflection due to the workers and/or the floor? These uncertain parameters have made this accident particularly difficult to analyze in the past. This work aims to lower the uncertainty on some of these parameters. A most-probable solution composition is determined by comparing literature on the physical properties of uranyl nitrate solutions to those presented in LA-13638 [1], which describes the accident in question. Using this most-probable solution, the main contributions to the reactivity of the system and hence the eventual accident, are identified through Serpent 2 and OpenFOAM analyses. Serpent 2, a Monte Carlo software tool, is used to perform calculations of the reactivity effects of lowering the vessel toward the floor and the reactivity added by the close proximity of workers. OpenFOAM, a C++ partial differential equation solver toolkit, is used to simulate the fluid inside the vessel as the vessel is tipped. This is done by treating the solution and air inside the vessel as two incompressible, isothermal, and immiscible fluids using a volume of fluid (VoF) approach. The goal of this approach is simply to track the interface between the two fluids, and hence give an accurate description of the geometrical structure of the solution as the vessel is tipped. These two unique tools are then coupled to provide a time-dependent flow simulation to study the effect that the changing geometrical structure had on the criticality of the system, which is novel to the criticality safety field. This work provides a more accurate picture of the accident going forward. Key Words: Serpent 2, OpenFOAM, multi-physics, prompt neutron excursion, nuclear criticality safety accident, process condition change.
sPulse-burst PIV has been employed to acquire time-resolved data at 25 kHz of a supersonic jet exhausting into a subsonic compressible crossflow. Data were acquired along the windward boundary of the jet mixing layer and can be used to identify the turbulent eddies as they convect downstream in the far-field of the interaction. Eddies were found to have a tendency to occur in closely-spaced counter-rotating pairs and are routinely observed in the PIV movies, but the variable orientation of these pairs makes them difficult to detect statistically. Correlated counter-rotating vortices are more strongly observed to pass by at a spacing about three times the separation between paired vortices, both leading and trailing the reference eddy. This indicates the paired nature of the turbulent eddies and the tendency for these pairs to convect through the field of view at repeatable spacings. Velocity spectra reveal a peak at a frequency consistent with this larger spacing between shear-layer vortices rotating with identical sign. The spatial scale of these vortices appears similar to previous observations of compressible jets in crossflow.
The flow over aircraft bays exhibits many characteristics of cavity flows, namely resonant pressures that can create high structural loading. An extensive dataset of pressure measurements within both simple and complex cavities was previously obtained and analyzed using power-spectral densities, coherence levels, and cross correlations between sensor pairs within the cavity. More in-depth analysis of the flow structure is studied here using modal decomposition techniques. Both Proper Orthogonal Decomposition (POD) and Dynamic Mode Decomposition (DMD) were applied to the experimental and computational results within a simple rectangular cavity. POD was able to show that the cavity modes are coherent across the cavity width. Only higher modes that were associated with more turbulent fluctuations exhibited spanwise variations. These were concentrated at the aft end of the cavity. DMD was able to isolate structures associated with single frequencies in the flow. At the Rossiter frequencies, coherent structures across the front cavity width were found, while more complex shapes were observed at the cavity rear, consistent with the POD analysis. Additional DMD modes in between the dominant Rossiter frequencies also appeared. These additional modes were associated with a low-frequency modulation of the cavity tones.
The Seven Percent Critical Experiment (7uPCX) at Sandia National Laboratories was designed to provide benchmark criticality and reactor physics data for water-moderated pin-fueled nuclear reactor cores in the 5 to 10 percent enrichment range. Approach-to-critical experiments were performed on nineteen partially-reflected arrays of pure water-moderated and -reflected fuel rods with a fuel-to-water volume ratio of 0.67. Those configurations are described and the results of the measurements are reported in this paper.
A multi-dimensional finite element solver for decomposing and non-decomposing ablating materials has recently been developed and is discussed in this paper. The underlying mathematical and material models are presented along with its discretization via the finite element method. The governing equations and solution algorithm is based on the one-dimensional control-volume finite element method (CVFEM) Chaleur code, a successful ablation code in use at Sandia National Labs, and this paper represents a multi-dimensional extension of Chaleur. The Equilibrium Surface Thermochemistry (EST) code, an equilibrium gas/surface thermochemistry code for decomposing and non-decomposing materials that was previously developed by the authors is used in conjunction with this new multi-dimensional ablation code to provide ablation thermochemistry information (i.e. B0c and enthalpy tables). This new multi-dimensional ablation response code is first applied to solve two established code-to-code comparison problems with tabular aeroheating data. Another aspect of this work has been to develop the ability to couple CFD-based aeroheating data to the ablation code as a spatial and time variant boundary condition. Towards this end, we have established a one-way passing of aeroheating data from a hypersonic CFD code to the ablation code. We then examine the problem of simulating the ablation response of non-decomposing and decomposing materials in two arc-jet facilities.
Despite technological advances making computing devices faster, smaller, and more prevalent in today's age, data generation and collection has outpaced data processing capabilities. Simply having more compute platforms does not provide a means of addressing challenging problems in the big data era. Rather, alternative processing approaches are needed and the application of machine learning to big data is hugely important. The MapReduce programming paradigm is an alternative to conventional supercomputing approaches, and requires less stringent data passing constrained problem decompositions. Rather, MapReduce relies upon defining a means of partitioning the desired problem so that subsets may be computed independently and recom-bined to yield the net desired result. However, not all machine learning algorithms are amenable to such an approach. Game-theoretic algorithms are often innately distributed, consisting of local interactions between players without requiring a central authority and are iterative by nature rather than requiring extensive retraining. Effectively, a game-theoretic approach to machine learning is well suited for the MapReduce paradigm and provides a novel, alternative new perspective to addressing the big data problem. In this paper we present a variant of our Support Vector Machine (SVM) Game classifier which may be used in a distributed manner, and show an illustrative example of applying this algorithm.
Memory failures in future extreme scale applications are a significant concern in the high-performance computing community and have attracted much research attention. We contend in this paper that using application checkpoint data to detect memory failures has potential benefits and is preferable to examining application memory. To support this contention, we describe the application of machine learning techniques to evaluate the veracity of checkpoint data. Our preliminary results indicate that supervised decision tree machine learning approaches can effectively detect corruption in restart files, suggesting that future extreme-scale applications and systems may benefit from incorporating such approaches in order to cope with memory failues.
A multi-dimensional finite element solver for decomposing and non-decomposing ablating materials has recently been developed and is discussed in this paper. The underlying mathematical and material models are presented along with its discretization via the finite element method. The governing equations and solution algorithm is based on the one-dimensional control-volume finite element method (CVFEM) Chaleur code, a successful ablation code in use at Sandia National Labs, and this paper represents a multi-dimensional extension of Chaleur. The Equilibrium Surface Thermochemistry (EST) code, an equilibrium gas/surface thermochemistry code for decomposing and non-decomposing materials that was previously developed by the authors is used in conjunction with this new multi-dimensional ablation code to provide ablation thermochemistry information (i.e. B0c and enthalpy tables). This new multi-dimensional ablation response code is first applied to solve two established code-to-code comparison problems with tabular aeroheating data. Another aspect of this work has been to develop the ability to couple CFD-based aeroheating data to the ablation code as a spatial and time variant boundary condition. Towards this end, we have established a one-way passing of aeroheating data from a hypersonic CFD code to the ablation code. We then examine the problem of simulating the ablation response of non-decomposing and decomposing materials in two arc-jet facilities.
Ultrasonic wave propagation decreases as a material is heated. Two factors that can characterize material properties are changes in wave speed and energy loss from interactions within the media. Relatively small variations in velocity and attenuation can detect significant differences in microstructures. This paper discusses an overview of experimental techniques that document the changes within a highly attenuative material as it is either being heated or cooled from 25°C to 90°C. The experimental set-up utilizes ultrasonic probes in a through-transmission configuration. The waveforms are recorded and analyzed during thermal experiments. To complement the ultrasonic data, a Discontinuous-Galerkin Model (DGM) was also created which uses unstructured meshes and documents how waves travel in these anisotropic media. This numerical method solves particle motion travel using partial differential equations and outputs a wave trace per unit time. Both experimental and analytical data are compared and presented.
Performance measurement of parallel algorithms is well studied and well understood. However, a flaw in traditional performance metrics is that they rely on comparisons to serial performance with the same input. This comparison is convenient for theoretical complexity analysis but impossible to perform in large-scale empirical studies with data sizes far too large to run on a single serial computer. Consequently, scaling studies currently rely on ad hoc methods that, although effective, have no grounded mathematical models. In this position paper we advocate using a rate-based model that has a concrete meaning relative to speedup and efficiency and that can be used to unify strong and weak scaling studies.
ASME 2015 9th International Conference on Energy Sustainability, ES 2015, collocated with the ASME 2015 Power Conference, the ASME 2015 13th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2015 Nuclear Forum
Gorman, Brandon T.; Johnson, Nathan G.; Miller, James E.; Stechel, Ellen B.
Concentrating solar power systems coupled to energy storage schemes, e.g. storage of sensible energy in a heat transfer fluid, are attractive options to reduce the transient effects of clouding on solar power output and to provide power after sunset and before sunrise. Common heat transfer fluids used to capture heat in a solar receiver include steam, oil, molten salt, and air. These high temperature fluids can be stored so that electric power can be produced on demand, limited primarily by the size of the capacity and the energy density of the storage mechanism. Phase changing fluids can increase the amount of stored energy relative to non-phase changing fluids due to the heat of vaporization or the heat of fusion. Reversible chemical reactions can also store heat; an endothermic reaction captures the heat, the chemical products are stored, and an exothermic reaction later releases the heat and returns the chemical compound to its initial state. Ongoing research is investigating the scientific and commercial potential of such reaction cycles with, for example, reduction (endothermic) and re-oxidation (exothermic) of metal oxide particles. This study includes thermodynamic analyses and considerations for component sizing of concentrating solar power towers with redox active metal oxide based thermochemical storage to reach target electrical output capacities of 0.1 MW to 100 MW. System-wide analyses here use one-dimensional energy and mass balances for the solar field, solar receiver reduction reactor, hot reduced particle storage, re-oxidizer reactor, power block, cold particle storage, and other components pertinent to the design. This work is part of a US Department of Energy (DOE) SunShot project entitled High Performance Reduction Oxidation of Metal Oxides for Thermochemical Energy Storage (PROMOTES).
SNL has developed a series of ionic-liquid electrolytes with accompanying non- Aqueous compatible membranes and flow cell designs for improved energy density redox flow batteries targeted to support increasing demands for stationary energy storage. The new electrolytes yield a higher energy density by chemically incorporating an electro- Active transition metal element into the solvent's molecular formula. Although ionic liquids have higher viscosities than conventional non- Aqueous electrolytes, they are promising for higher energy densities due to higher metal concentrations and wider voltage windows. We have addressed high viscosity by developing new materials through careful ligand and anion selection. We have also developed tunable membranes for non- Aqueous compatibility and rapid laboratory-scale prototyping to quickly screen materials and cell designs. We are projecting a four-fold improvement in energy density over the next two years.
The move towards extreme-scale computing platforms challenges scientific simulations in many ways. Given the recent tendencies in computer architecture development, one needs to reformulate legacy codes in order to cope with large amounts of communication, system faults, and requirements of low-memory usage per core. In this work, we develop a novel framework for solving PDEs via domain decomposition that reformulates the solution as a state of knowledge with a probabilistic interpretation. Such reformulation allows resiliency with respect to potential faults without having to apply fault detection, avoids unnecessary communication, and is generally well-suited for rigorous uncertainty quantification studies that target improvements of predictive fidelity of scientific models. We demonstrate our algorithm for one-dimensional PDE examples where artificial faults have been implemented as bit flips in the binary representation of subdomain solutions.
Falls prevention efforts for older adults have become increasingly important and are now a significant research effort. As part of the prevention effort, analysis of gait has become increasingly important. Data is typically collected in a laboratory setting using 3-D motion capture, which can be time consuming, invasive and requires expensive and specialized equipment as well as trained operators. Inertial sensors, which are smaller and more cost effective, have been shown to be useful in falls research. Smartphones now contain Micro Electro-Mechanical (MEM) Inertial Measurement Units (IMUs), which make them a compelling platform for gait data acquisition. This paper reports the development of an iOS app for collecting accelerometer data and an offline machine learning system to classify a subject, based on this data, as faller or non-faller based on their history of falls. The system uses the accelerometer data captured on the smartphone, extracts discriminating features, and then classifies the subject based on the feature vector. Through simulation, our preliminary and limited study suggests this system has an accuracy as high as 85%. Such a system could be used to monitor an at-risk person's gait in order to predict an increased risk of falling.
A laboratory testing program was developed to examine the short-term mechanical and time-dependent (creep) behavior of salt from the Bayou Choctaw Salt Dome. Core was tested under creep and quasi-static constant mean stress axisymmetric compression, and constant mean stress axisymmetric extension conditions. Creep tests were performed at 38 degrees Celsius, and the axisymmetric tests were performed at ambient temperatures (22-26 degrees Celsius). The testing performed indicates that the dilation criterion is pressure and stress state dependent. It was found that as the mean stress increases, the shear stress required to cause dilation increases. The results for this salt are reasonably consistent with those observed for other domal salts. Also it was observed that tests performed under extensile conditions required consistently lower shear stress to cause dilation for the same mean stress, which is consistent with other domal salts. Young's modulus ranged from 27.2 to 58.7 GPa with an average of 44.4 GPa, with Poisson's ratio ranging from 0.10 to 0.43 with an average of 0.30. Creep testing indicates that the BC salt is intermediate in creep resistance when compared with other bedded and domal salt steady-state behavior.
Kinetic theory is often used as a framework to derive moment equations for sprays, with considerable success in the case of a dilute spray in a fully resolved (DNS) gas field. In the prospect of computing LES of atomization with a spray solver, a formalism that accounts for the non-linear interaction between high-loading regions and turbulence at the subfilter level is needed. So we first introduce a kinetic theory frame, where the phase space is extended to space-filtered spray quantities. This rigorous formalism is a comprehensive baseline but it requires closures. Second we quantify segregation, through a priori DNS, as a relevant space-filtered quantity to account for the spray’s subfilter behavior. Third we discuss an assumption on the subfilter spray structures which allows the closure of drag, heating, and collisions from the sole knowledge of segregation.
Cui, Yu Y.; Brioude, Jerome; Mckeen, Stuart A.; Angevine, Wayne M.; Kim, Si W.; Frost, Gregory J.; Ahmadov, Ravan; Peischl, Jeff; Bousserez, Nicolas; Liu, Zhen; Ryerson, Thomas B.; Wofsy, Steve C.; Santoni, Gregory W.; Kort, Eric A.; Fischer, Marc L.; Trainer, Michael
Methane (CH4) is the primary component of natural gas and has a larger global warming potential than CO2. Recent top-down studies based on observations showed CH4 emissions in California’s South Coast Air Basin (SoCAB) were greater than those expected from population-apportioned bottom-up state inventories. In this study, we quantify CH4 emissions with an advanced mesoscale inverse modeling system at a resolution of 8 km× 8 km, using aircraft measurements in the SoCAB during the 2010 Nexus of Air Quality and Climate Change campaign to constrain the inversion. To simulate atmospheric transport, we use the FLEXible PARTicle-Weather Research and Forecasting (FLEXPART-WRF) Lagrangian particle dispersion model driven by three configurations of the Weather Research and Forecasting (WRF) mesoscale model. We determine surface fluxes of CH4 using a Bayesian least squares method in a four-dimensional inversion. Simulated CH4 concentrations with the posterior emission inventory achieve much better correlations with the measurements (R2 = 0.7) than using the prior inventory (U.S. Environmental Protection Agency’s National Emission Inventory 2005, R2 = 0.5). The emission estimates for CH4 in the posterior, 46.3 ± 9.2 Mg CH4/h, are consistent with published observation-based estimates. Changes in the spatial distribution of CH4 emissions in the SoCAB between the prior and posterior inventories are discussed. Missing or underestimated emissions from dairies, the oil/gas system, and landfills in the SoCAB seem to explain the differences between the prior and posterior inventories. We estimate that dairies contributed 5.9 ± 1.7 Mg CH4/h and the two sectors of oil and gas industries (production and downstream) and landfills together contributed 39.6 ± 8.1 Mg CH4/h in the SoCAB.
A helium leakage detection system was modified to measure gas permeability on extracted cores of nearly impermeable rock. Here we use a Helium - Mass - Spectrometry - Permeameter (HMSP) to conduct a constant pressure, steady state flow test through a sample using helium gas. Under triaxial stress conditions, the HMSP can measure flow and estimate permeability of rocks and geomaterials down to the nanodarcy scale (10-21 m2). In this study, measurements of flow through eight shale samples under hydrostatic conditions were in the range of 10-7 to 10-9 Darcy. We extend this flow measurement technology by dynamically monitoring the release of helium from a helium saturated shale sample during a triaxial deformation experiment. The helium flow, initially extremely low, consistent with the low permeability of shale, is observed to increase in advance of volume strain increase during deformation of the shale. This is perhaps the result of microfracture development and flow path linkage through the microfractures within the shale. Once microfracturing coalescence initiates, there is a large increase in helium release and flow. This flow rate increase is likely the result of development of a macrofracture in the sample, a flow conduit, later confirmed by post-test observations of the deformed sample. The release rate (flow) peaks and then diminishes slightly during subsequent deformation; however the post deformation flow rate is considerably greater than that of undeformed shale.
Multiscale characteristics of anisotropic, heterogeneous pore structure and compositional (e.g., kerogen, clay, cement, etc) distribution profoundly influence the hydro, mechanical, and chemical response of shale materials during stimulation and production. In this work the impact of these lithologic heterogeneities on physical, chemical, and mechanical properties is investigated over a micron to core scale of shale samples for Cretaceous Mancos Shale. Principal macroscopic lithofacies at a decimeter scale are petrographically examined. Thin sections (∼2-3cm) impregnated with fluorochromes are examined using laser scanning confocal microscopy and optical microscopy with different filters to characterize micro-facies (i.e., texture patterns) and using electron microprobe to identify the mineralogical distribution. Advanced multiscale image analysis for texture classification will be used to identify key features of samples which will be further analyzed using dual focused ion beam-scanning electron microscopy, aberration corrected-scanning TEM and energy dispersive X-ray spectrometry for nano-pore and organic-pore structures and mineralogies at nano scale. This characterization will be examined against experimental data including acoustic emission and nano-indentation measurements of elastic properties using focused ion-beam milled pillars. Finally, multiscale 3-D image stacks will be segmented to rigorously test the scale of a representative elementary volume based on multiple measures from image analysis and pore-scale simulations.
ASME 2015 9th International Conference on Energy Sustainability, ES 2015, collocated with the ASME 2015 Power Conference, the ASME 2015 13th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2015 Nuclear Forum
Standard glass and polymer covers on photovoltaic modules can partially reflect the sunlight causing glint and glare. Glint and glare from large photovoltaic installations can be significant and have the potential to create hazards for motorists, air-traffic controllers and pilots flying near installations. In this work, the reflectance, surface roughness and reflected solar beam spread were measured from various photovoltaic modules acquired from seven different manufacturers. The surface texturing of the PV modules varied from smooth to roughly textured. Correlations between the measured surface texturing (roughness parameters) and beam spread (subtended angle) were determined. These correlations were then used to assess surface texturing effects on transmittance and ocular impacts of glare from photovoltaic module covers. The results can be used to drive the designs for photovoltaic surface texturing to improve transmittance and minimize glint/glare.
The development of a reactive flow solver suitable for large-scale simulations of high-speed engine component flow fields is described in this paper. The intent is to mature an existing flow solver, North Carolina State University’s REACTMB, into a production-level tool suitable for test and evaluation (T&E) activities. The computational framework is based on the combined use of Reynolds-averaged Navier-Stokes (RANS) methods and large-eddy simulation (LES) strategies, with the former used to examine system-level effects and the latter used for detailed component studies. Specific modifications that extend the capabilities of REACTMB (bleed modeling, eddy-dissipation combustion modeling) are described, as are methods for coupling flow solutions with established 1D system performance tools.
We have designed and produced an optical coating suitable for broad bandwidth high reflection (BBHR) at 45° angle of incidence (AOI), P polarization (Ppol) of petawatt (PW) class fs laser pulses of ∼ 900 nm center wavelength. We have produced such BBHR coatings consisting of TiO2/SiO2 layer pairs deposited by ion assisted e-beam evaporation using the large optics coater at Sandia National Laboratories. This paper focuses on laser-induced damage threshold (LIDT) tests of these coatings. LIDT is difficult to measure for such coatings due to the broad range of wavelengths over which they can operate. An ideal test would be in the vacuum environment of the fs-pulse PW use laser using fs pulses identical to of the PW laser. Short of this ideal testing would be tests over portions of the HR band of the BBHR coating using ns or sub-ps pulses produced by tunable lasers. Such tests could be over ∼ 10 nm wide wavelength intervals whose center wavelengths could be tuned over the BBHR coating's operational band. Alternatively, the HR band of the BBHR coating could be adjusted by means of wavelength shifts due to changing the AOI of the LIDT tests or due to absorbed moisture by the coating under ambient conditions. We conduct LIDT tests on the BBHR coatings at selected AOIs to gain insight into the coatings' laser damage properties, and analyze how the results of the different LIDT tests compare.
Visual search has been an active area of research – empirically and theoretically – for a number of decades, however much of that work is based on novice searchers performing basic tasks in a laboratory. This paper summarizes some of the issues associated with quantifying expert, domain-specific visual search behavior in operationally realistic environments.
DuPont 9k7 low temperature cofired ceramic (LTCC) is a low loss, or high quality factor Q, tape system targeting at radio frequency (RF) applications. This paper reports the effect of a critical process parameter, heating rate, on the densification and dielectric properties of the 9k7 LTCC. The role of competing densification and crystallization during the sintering of 9k7 is discussed. The high Q of DuPont 9K7 can be used to improve RF system performance, for example a better receiver noise figure, by designing embedded passive RF components such as inductors, capacitors and filters. Miniaturized multilayer low pass filters (LPF) with a wide stopband were fabricated to showcase the technology.
Li/FeS2 thermal batteries provide a stable, robust, and reliable power source capable of long-term electrical energy storage without performance degradation. These systems rely on the electrical conductivity of FeS2 cathodes for critical performance parameters such as power and lifetime, and on permeability of the electrolyte through the solid FeS2 particles for ion transfer. The effects of component composition, manufacturing conditions, and the mechanical deformation on conductivity and permeability have not been studied. We present simulation results from a finite element computer model compared with impedance spectroscopy electrical conductivity experiments. Our methods elucidate the combined effects of slumping, particle size distribution, composition, and pellet density on properties related to electrical conduction in Li/FeS2 thermal battery cathodes.
ASME 2015 9th International Conference on Energy Sustainability, ES 2015, collocated with the ASME 2015 Power Conference, the ASME 2015 13th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2015 Nuclear Forum
Typical Concentrated Solar Power (CSP) central receiver power plants require the use of either an external or cavity receiver. Previous and current external receivers consist of a series of tubes connected to manifolds that form a cylindrical or rectangular shape such as in the cases of Solar One, Solar Two, and most recently the Ivanpah solar plant. These receivers operate at high surface temperatures (>600°C) at which point thermal re-radiation is significant. However, the geometric arrangement of these heat transfer tubes results in heat losses directly to the environment. This work focused on how to fundamentally reduce this heat loss through the manipulation of heat transfer tube configurations. Four receiver configurations are studied: flat receiver (base case study), a radial receiver with finned structures (fins arranged in a circular pattern on a cylinder), a louvered finned structure (horizontal and angled fins on a flat plate), and a vertical finned structure (fins oriented vertically along a flat plate). The thermal efficiency, convective heat loss patterns, and air flow around each receiver design is found using the computational fluid dynamics (CFD) code ANSYS FLUENT. Results presented in this paper show that alternative tubular configurations increase thermal efficiency by increasing the effective solar absorptance of these hightemperature receivers by increasing the light trapping effects of the receiver, reducing thermal emittance to the environment, and reducing the overall size of the receiver. Each receiver configuration has finned structures that take advantage of the directional dependence of the heliostat field resulting in a light trapping effect on the receiver. The finned configurations tend to lead to "hot" regions on the receiver, but the new configurations can take advantage of high local view factors (each surface can "see" another receiver surface) in these regions through the use of heat transfer fluid (HTF) flow patterns. The HTF reduces the temperatures in these regions increasing the efficiency of heat transfer to the fluid. Finally, the new receiver configurations have a lower overall optical intercept region resulting in a higher geometric concentration ratio for the receiver. Compared to the base case analysis (flat plate receiver), the novel tubular geometries results showed an increase in thermal efficiency.
ASME 2015 9th International Conference on Energy Sustainability, ES 2015, collocated with the ASME 2015 Power Conference, the ASME 2015 13th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2015 Nuclear Forum
Recent studies have evaluated closed-loop supercritical carbon dioxide (s-CO2) Brayton cycles to be a higher energydensity system in comparison to conventional superheated steam Rankine systems. At turbine inlet conditions of 923K and 25 MPa, high thermal efficiency (∼50%) can be achieved. Achieving these high efficiencies will make concentrating solar power (CSP) technologies a competitive alternative to current power generation methods. To incorporate a s-CO2 Brayton power cycle in a solar power tower system, the development of a solar receiver capable of providing an outlet temperature of 923 K (at 25 MPa) is necessary. The s-CO2 will need to increase in temperature by ∼200 K as it passes through the solar receiver to satisfy the temperature requirements of a s-CO2 Brayton cycle with recuperation and recompression. In this study, an optical-thermal-fluid model was developed to design and evaluate a tubular receiver that will receive a heat input ∼2 MWth from a heliostat field. The ray-tracing tool SolTrace was used to obtain the heat-flux distribution on the surfaces of the receiver. Computational fluid dynamics (CFD) modeling using the Discrete Ordinates (DO) radiation model was used to predict the temperature distribution and the resulting receiver efficiency. The effect of flow parameters, receiver geometry and radiation absorption by s-CO2 were studied. The receiver surface temperatures were found to be within the safe operational limit while exhibiting a receiver efficiency of ∼85%.
ASME 2015 9th International Conference on Energy Sustainability, ES 2015, collocated with the ASME 2015 Power Conference, the ASME 2015 13th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2015 Nuclear Forum
Closed-loop super-critical carbon dioxide (sCO2) Brayton cycles are being evaluated in combination with concentrating solar power to provide higher thermal-to-electric conversion efficiencies relative to conventional steam Rankine cycles. However, high temperatures (650-700°C) and pressures (20-25 MPa) are required in the solar receiver. In this study an extensive material review was performed along with a tube size optimization following the ASME Boiler and Pressure Vessel Code and B31.1 and B313.3 codes respectively. Subsequently a thermal-structural model was developed using ANSYS Fluent and Structural to design and analyze the tubular receiver that could provide the heat input for a ∼2 MWth plant. The receiver will be required to provide an outlet temperature of 650°C (at 25 MPa) or 700°C (at 20 MPa). The induced thermal stresses were applied using a temperature gradient throughout the tube while a constant pressure load was applied on the inner wall. The resulting stresses have been validated analytically using constant surface temperatures. The cyclic loading analysis was performed using the Larson-Miller creep model in nCode Design Life to define the structural integrity of the receiver over the desired lifetime of ∼10,000 cycles. The results have shown that the stresses induced by the thermal and pressure load can be withstood by the tubes selected. The creep-fatigue analysis displayed the damage accumulation due to the cycling and the permanent deformation of the tubes. Nonetheless, they are able to support the required lifetime. As a result, a complete model to verify the structural integrity and thermal performance of a high temperature and pressure receiver has been developed. This work will serve as reference for future design and evaluation of future direct and indirect tubular receivers.
Traditional tubular receivers used in concentrating solar power are formed using tubes connected to manifolds to form panels; which in turn are arranged in cylindrical or rectangular shapes. Previous and current tubular receivers, such as the ones used in Solar One, Solar Two, and most recently the Ivanpah solar plants, have used a black paint coating to increase the solar absorptance of the receiver. However, these coatings degrade over time and must be reapplied, increasing the receiver maintenance cost. This paper presents the thermal efficiency evaluation of novel receiver tubular panels that have a higher effective solar absorptance due to a light-trapping effect created by arranging the tubes in each panel into unique geometric configurations. Similarly, the impact of the incidence angle on the effective solar absorptance and thermal efficiency is evaluated. The overarching goal of this work is to achieve effective solar absorptances of ∼90% and thermal efficiencies above 85% without using an absorptance coating. Several panel geometries were initially proposed and were down-selected based on structural analyses considering the thermal and pressure loading requirements of molten salt and supercritical carbon-dioxide receivers. The effective solar absorptance of the chosen tube geometries and panel configurations were evaluated using the ray-tracing modeling capabilities of SolTrace. The thermal efficiency was then evaluated by coupling computational fluid dynamics with the ray-tracing results using ANSYS Fluent. Compared to the base case analysis (flat tubular panel), the novel tubular panels have shown an increase in effective solar absorptance and thermal efficiency by several percentage points.
Time-resolved particle image velocimetry (TR-PIV) has been achieved in a high-speed wind tunnel, providing velocity field movies of compressible turbulence events. The requirements of high-speed flows demand greater energy at faster pulse rates than possible with the TR-PIV systems developed for low-speed flows. This has been realized using a pulse-burst laser to obtain movies at up to 50 kHz with higher speeds possible at the cost of spatial resolution. The constraints imposed by use of a pulse-burst laser are a limited burst duration of 10.2 ms and a low duty cycle for data acquisition. Pulse-burst PIV has been demonstrated in a supersonic jet exhausting into a transonic crossflow and in transonic flow over a rectangular cavity. The velocity field sequences reveal the passage of turbulent structures and can be used to find velocity power spectra at every point in the field, providing spatial distributions of acoustic modes. The present work represents the first use of TR-PIV in a high-speed ground test facility.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Ciesko, Jan; Mateo, Sergi; Teruel, Xavier; Martorell, Xavier; Ayguade, Eduard; Labarta, Jesus; Duran, Alex; De Supinski, Bronis R.; Olivier, Stephen L.; Li, Kelvin; Eichenberger, Alexandre E.
Reductions represent a common algorithmic pattern in many scientific applications. OpenMP* has always supported them on parallel and worksharing constructs. OpenMP 3.0’s tasking constructs enable new parallelization opportunities through the annotation of irregular algorithms. Unfortunately the tasking model does not easily allow the expression of concurrent reductions, which limits the general applicability of the programming model to such algorithms. In this work, we present an extension to OpenMP that supports task-parallel reductions on task and taskgroup constructs to improve productivity and programmability. We present specification of the feature and explore issues for programmers and software vendors regarding programming transparency as well as the impact on the current standard with respect to nesting, untied task support and task data dependencies. Our performance evaluation demonstrates comparable results to hand coded task reductions.
Concentrating solar power receivers are comprised of panels of tubes arranged in a cylindrical or cubical shape on top of a tower. The tubes contain heat-transfer fluid that absorbs energy from the concentrated sunlight incident on the tubes. To increase the solar absorptance, black paint or a solar selective coating is applied to the surface of the tubes. However, these coatings degrade over time and must be reapplied, which reduces the system performance and increases costs. This paper presents an evaluation of novel receiver shapes and geometries that create a light-trapping effect, thereby increasing the effective solar absorptance and efficiency of the solar receiver. Several prototype shapes were fabricated from Inconel 718 and tested in Sandiaas solar furnace at an irradiance of ∼30 W/cm2. Photographic methods were used to capture the irradiance distribution on the receiver surfaces. The irradiance profiles were compared to results from raytracing models. The effective solar absorptance was also evaluated using the ray-tracing models. Results showed that relative to a flat plate, the new geometries could increase the effective solar absorptance from 86% to 92% for an intrinsic material absorptance of 86%, and from 60% to 73% for an intrinsic material absorptance of 60%.
Particle image velocimetry (PIV) measurements quantified the coherent structure of acoustic tones in a Mach 0.91 cavity flow. Stereoscopic PIV measurements were performed at 10-Hz and two-component, time-resolved data were obtained using a pulse-burst laser. The cavity had a square planform, a length-to-depth ratio of five, and an incoming turbulent boundary layer. Simultaneous fast-response pressure signals were bandpass filtered about each cavity tone frequency. The 10-Hz PIV data were then phase-averaged according to the bandpassed pressures to reveal the flow structure associated with the resonant tones. The first Rossiter mode was associated with large scale oscillations in the shear layer, while the second and third modes contained organized structures consistent with convecting vortical disturbances. The spatial wavelengths of the cavity tones, based on the vertical coherent velocity fields, were less than those predicted by the Rossiter relation. With increasing streamwise distance the spacing between structures increased and approached the predicted Rossiter value at the aft-end of the cavity. Moreover, the coherent structures appeared to rise vertically with downstream propagation. The time-resolved PIV data were bandpass filtered about the cavity tone frequencies to reveal flow structure. The resulting spacing between disturbances was similar to that in the phase-averaged flowfields.
Electric distribution utilities, the companies that feed electricity to end users, are overseeing a technological transformation of their networks, installing sensors and other automated equipment, that are fundamentally changing the way the grid operates. These grid modernization efforts will allow utilities to incorporate some of the newer technology available to the home user – such as solar panels and electric cars – which will result in a bi-directional flow of energy and information. How will this new flow of information affect control room operations? How will the increased automation associated with smart grid technologies influence control room operators’ decisions? And how will changes in control room operations and operator decision making impact grid resilience? These questions have not been thoroughly studied, despite the enormous changes that are taking place. In this study, which involved collaborating with utility companies in the state of Vermont, the authors proposed to advance the science of control-room decision making by understanding the impact of distribution grid modernization on operator performance. Distribution control room operators were interviewed to understand daily tasks and decisions and to gain an understanding of how these impending changes will impact control room operations. Situation awareness was found to be a major contributor to successful control room operations. However, the impact of growing levels of automation due to smart grid technology on operators’ situation awareness is not well understood. Future work includes performing a naturalistic field study in which operator situation awareness will be measured in real-time during normal operations and correlated with the technological changes that are underway. The results of this future study will inform tools and strategies that will help system operators adapt to a changing grid, respond to critical incidents and maintain critical performance skills.
In forged, welded, and machined components, residual stresses can form during the fabrication process. These residual stresses can significantly alter the fatigue and fracture properties compared to an equivalent component containing no residual stress. When performing lifetime assessment, the residual stress state must be incorporated into the analysis to most accurately reflect the initial condition of the component. The focus of this work is to present the computational and experimental tools that we are developing to predict and measure the residual stresses in stainless steel for use in pressure vessels. The contour method was used to measure the residual stress in stainless steel forgings. These results are compared to the residual stresses predicted using coupled thermo-mechanical simulations that track the evolution of microstructure, strength and residual stress during processing.
Human reliability analysis (HRA) is used in the context of probabilistic risk assessment (PRA) to provide risk information regarding human performance to support risk-informed decision-making with respect to high-reliability industries. The IntegrateD Human Event Analysis System (IDHEAS) is a new HRA method developed for internal, at-power nuclear power plant (NPP) events. It was motivated by the intention to reduce unnecessary and inappropriate variability in HRA results and improve the reliability of human error probability (HEP) estimates. The method has a strong foundation in human performance and cognitive psychology theories, and employs a cause-based quantification model. This paper documents a study conducted to pilot test IDHEAS to (1) identify issues that needed to be addressed and (2) provide feedback to refine the method before the method was finalized. An introduction on IDHEAS is provided first. Then sample IDHEAS analysis results are presented for illustration purposes. Next, insights from the testing in terms of method strengths and weaknesses are discussed, which is followed by concluding remarks.
There is a great need for creating cohesive, expert cybersecurity incident response teams and training them effectively. This paper discusses new methodologies for measuring and understanding expert and novice differences within a cybersecurity environment to bolster training, selection, and teaming. This methodology for baselining and characterizing individuals and teams relies on relating eye tracking gaze patterns to psychological assessments, human-machine transaction monitoring, and electroencephalography data that are collected during participation in the game-based training platform Tracer FIRE. We discuss preliminary findings from two pilot studies using novice and professional teams.
Identifying high-performance, system-level microgrid designs is a significant challenge due to the overwhelming array of possible configurations. Uncertainty relating to loads, utility outages, renewable generation, and fossil generator reliability further complicates this design problem. In this paper, the performance of a candidate microgrid design is assessed by running a discrete event simulation that includes extended, unplanned utility outages during which microgrid performance statistics are computed. Uncertainty is addressed by simulating long operating times and computing average performance over many stochastic outage scenarios. Classifier-guided sampling, a Bayesian classifier-based optimization algorithm for computationally expensive design problems, is used to search and identify configurations that result in reduced average load not served while not exceeding a predetermined microgrid construction cost. The city of Hoboken, NJ, which sustained a severe outage following Hurricane Sandy in October, 2012, is used as an example of a location in which a well-designed microgrid could be of great benefit during an extended, unplanned utility outage. The optimization results illuminate design trends and provide insights into the traits of high-performance configurations.
While much attention is paid to the impact of the active materials on the catastrophic failure of lithium ion batteries, much of the severity of a battery failure is also governed by the electrolytes used, which are typically flammable themselves and can decompose during battery failure. The use of LiPF6 salt can be problematic as well, not only catalyzing electrolyte decomposition, but also providing a mechanism for HF production. This work evaluates the safety performance of the common components ethylene carbonate (EC), diethyl carbonate (DEC), dimethyl carbonate (DMC), and ethyl methyl carbonate (EMC) in the context of the gasses produced during thermal decomposition, looking at both the quantity and composition of the vapor produced. EC and DEC were found to be the largest contributors to gas production, both producing upwards of 1.5 moles of gas/mole of electrolyte. DMC was found to be relatively stable, producing very little gas regardless of the presence of LiPF6. EMC was stable on its own, but the addition of LiPF6 catalyzed decomposition of the solvent. While gas analysis did not show evidence of significant quantities of any acutely toxic materials, the gasses themselves all contained enough flammable components to potentially ignite in air.
Ultrafast optical excitation of photocarriers has the potential to transform undoped semiconductor superlattices into semiconductor hyperbolic metamaterials (SHMs). In this paper, we investigate the optical properties associated with such ultrafast topological transitions. We first show reflectance, transmittance, and absorption under TE and TM plane wave incidence. In the unpumped state, the superlattice exhibits a frequency region with high reflectance (>80%) and a region with low reflectance (<1%) for both TE and TM polarizations over a wide range of incidence angles. In contrast, in the photopumped state, the reflectance for both frequencies and polarizations is very low (<1%) for a similar range of angles. Interestingly, this system can function as an all-optical reflection switch on ultrafast timescales. Furthermore, for TM incidence and close to the epsilon-near-zero point of the longitudinal permittivity, directional perfect absorption on ultrafast timescales may also be achieved. Finally, we discuss the onset of negative refraction in the photopumped state.
There is a recognized need to develop computational models that can represent and simulate the decision making process of various groups across socio-cultural domains [5]. Yet, developing such models can be greatly hampered by the need to acquire and represent information pertaining to the psychological and social aspects of decision-making within these groups. Currently, there are numerous techniques and tools to help facilitate the elicitation and structuring of knowledge within expert-type systems—particularly those that focus on technical processes such as mechanical troubleshooting [3]. However, few techniques and tools have been developed for models that are intended to represent and assess the decision making of groups within different societies—particularly including cultural elements within these societies. This paper seeks to help address this challenge by discussing an approach to eliciting and structuring cross-cultural psychosocial and behavioral-economic elements within a theory-based assessment model. This work was developed to address the needs of Sandia National Laboratories’ Behavioral Influence Assessment modeling capability, which assesses decision-making within societies. The main component of the knowledge engineering effort is what we call the “knowledge structure.” The knowledge structure acts as scaffolding for the organization of psychosocial processes underlying decision-making, as well as the actual content of that knowledge with respect to a modeled society.
Some fires may involve fuels that are contaminated with airborne particles such as hazardous chemicals or radioactive materials, and therefore pose a significant health risk by the potential inhalation of the contaminated material. In particular, consider a relatively inert solid material which is sub-micron in size that is suspended in a liquid solvent. Various mechanisms can lead to the solid becoming entrained in the air. First, as a liquid fuel is consumed it typically transitions through a boiling regime. As the vapor bubbles rupture at the liquid surface, the liquid response can result in the formation of film drops (collapsing bubble film) or jet drops (caused by liquid rapidly filling the vapor void). Surface wave action can also result in bubble formation and entrainment as the bubbles collapse. This mechanism is generally a function of wind speed and fluid properties. Also, mass may be entrained from a residual layer formed after consumption of the fuel. This paper reviews the existing literature on these entrainment mechanisms. Based on data from the review, the results from a Lagrangian/Eulerian coupled computational transport code are compared to some existing data on the entrainment of contaminants from liquid fuel fires. Since the multi-phase mechanistic prediction of the entrainment is not mature, the methods employ coupling of correlation data to the computational fluid dynamics (CFD) code.
The elastic properties and mechanical stability of zirconium alloys and zirconium hydrides have been investigated within the framework of density functional perturbation theory. Results show that the lowest-energy cubic Pn3m polymorph of δ-ZrH1.5 does not satisfy all the Born requirements for mechanical stability, unlike its nearly degenerate tetragonal P42/mcm polymorph. Elastic moduli predicted with the Voigt-Reuss-Hill approximations suggest that mechanical stability of α-Zr, Zr-alloy and Zr-hydride polycrystalline aggregates is limited by the shear modulus. According to both Pugh's and Poisson's ratios, α-Zr, Zr-alloy and Zr-hydride polycrystalline aggregates can be considered ductile. The Debye temperatures predicted for γ-ZrH, δ-ZrH1.5 and ε-ZrH2 are D = 299.7, 415.6 and 356.9 K, respectively, while D = 273.6, 284.2, 264.1 and 257.1 K for the α-Zr, Zry-4, ZIRLO and M5 matrices, i.e. suggesting that Zry-4 possesses the highest micro-hardness among Zr matrices.
The reproducing kernel particle method (RKPM) is a meshfree method for computational solid mechanics that can be tailored for an arbitrary order of completeness and smoothness. The primary advantage of RKPM relative to standard finiteelement (FE) approaches is its capacity to model large deformations, material damage, and fracture. Additionally, the use of a meshfree approach offers great flexibility in the domain discretization process and reduces the complexity of mesh modifications such as adaptive refinement. We present an overview of the RKPM implementation in the Sierra/SolidMechanics analysis code, with a focus on verification, validation, and software engineering for massively parallel computation. Key details include the processing of meshfree discretizations within a FE code, RKPM solution approximation and domain integration, stress update and calculation of internal force, and contact modeling. The accuracy and performance of RKPM are evaluated using a set of benchmark problems. Solution verification, mesh convergence, and parallel scalability are demonstrated using a simulation of wave propagation along the length of a bar. Initial model validation is achieved through simulation of a Taylor bar impact test. The RKPM approach is shown to be a viable alternative to standard FE techniques that provides additional flexibility to the analyst community.
Muons are subatomic particles capable of penetrating the earth's crust several kilometers. Muons have been used to image the Pyramid of Khafre of Giza, various volcanoes, and smaller targets like cargo. For objects like a volcano, the detector is placed at the volcano's base and muon fluxes for paths through the volcano are recorded for many days to weeks.
Fluid-structure interactions that occur during aircraft internal store carriage were experimentally explored at Mach 0.94 and 1.47 using a generic, aerodynamic store installed in a rectangular cavity having a length-to-depth ratio of 7. Similar to previous studies using a cylindrical store, the aerodynamic store responded to the cavity flow at its natural structural frequencies, and it exhibited a directionally dependent response to cavity resonance. Cavity tones excited the store in the streamwise and wall-normal directions consistently, whereas the spanwise response was much more limited. The store had interchangeable components to vary its natural frequencies by about 10 - 300 Hz. By tuning natural frequencies, mode-matched cases were explored where a prominent cavity tone frequency matched a structural natural frequency of the store. Mode matching produced substantial increases in store vibrations, though the response of the store continued to scale linearly with the dynamic pressure or loading in the bay. Near mode matching frequencies, the response of the store was quite sensitive as changes in cavity tone frequencies of 1% altered store vibrations by as much as a factor of two.
Langel, Christopher M.; Chow, Raymond; Hurley, Owen F.; Van Dam, C.P.; Ehrmann, Robert S.; White, Edward B.; Maniaci, David C.
Over time it has been reported wind turbine power output can diminish below manufacturers promised levels. This is clearly undesirable from an operator standpoint, and can also put pressure on turbine companies to make up the difference. A likely explanation for the discrepancy in power output is the contamination of the leading edge due to environmental conditions creating surfaces much coarser than intended. To examine the effects of airfoil leading edge roughness, a comprehensive study has been performed both experimentally and computationally on a NACA 633 - 418 airfoil. A description of the experimental setup and test matrix are provided, along with an outline of the computational roughness amplification model used to simulate rough configurations. The experimental investigation serves to provide insight into the changes in measurable airfoil properties such as lift, drag, and boundary layer transition location. The computational effort is aimed at using the experimental results to calibrate a roughness model that has been implemented in an unsteady RANS solver. Furthermore, a blade element momentum code was used to assess the impact on the performance of a turbine as whole due to discrepancies in clean vs. soiled airfoil characteristics. The results have implications in predicting the power loss due to leading edge surface roughness, and can help to establish an upper bound on admissible surface contamination levels.
Visible light laser voltage probing (LVP) for improved backside optical spatial resolution is demonstrated on ultrathinned bulk Si samples. A prototype system for data acquisition, a method to produce ultra-thinned bulk samples as well as LVP signal, imaging, and waveform acquisition are described on bulk Si devices. Spatial resolution and signal comparison with conventional, infrared LVP analysis is discussed.
We study several natural instances of the geometric hitting set problem for input consisting of sets of line segments (and rays, lines) having a small number of distinct slopes. These problems model path monitoring (e.g., on road networks) using the fewest sensors (the “hitting points”). We give approximation algorithms for cases including (i) lines of 3 slopes in the plane, (ii) vertical lines and horizontal segments, (iii) pairs of horizontal/vertical segments. We give hardness and hardness of approximation results for these problems. We prove that the hitting set problem for vertical lines and horizontal rays is polynomially solvable.
Optical coatings with the highest laser damage thresholds rely on clean conditions in the vacuum chamber during the coating deposition process. A low base pressure in the coating chamber, as well as the ability of the vacuum system to maintain the required pressure during deposition, are important aspects of limiting the amount of defects in an optical coating that could induce laser damage. Our large optics coating chamber at Sandia National Laboratories normally relies on three cryo pumps to maintain low pressures for e-beam coating processes. However, on occasion, one or more of the cryo pumps have been out of commission. In light of this circumstance, we decided to explore how deposition under compromised vacuum conditions resulting from the use of only one or two cryo pumps affects the laser-induced damage thresholds of optical coatings. The coatings of this study consist of HfO2 and SiO2 layer materials and include antireflection coatings for 527 nm at normal incidence, and high reflection coatings for 527 nm, 45° angle of incidence (AOI), in P-polarization (P-pol).
We have designed a dichroic beam combiner coating consisting of 11 HfO2/SiO2 layer pairs deposited on a large fused silica substrate. The coating provides high transmission (HT) at 527 nm and high reflection (HR) at 1054 nm for light at 22.5° angle of incidence (AOI) in air in S polarization (Spol). The coating's design is based on layers of near half-wave optical thickness in the design space for stable HT at 527 nm, with layer modifications that provide HR at 1054 nm while preserving HT at 527 nm. Its implementation in the 527 nm/1054 nm dual wavelength beam combiner arrangement has two options, with each option requiring one or the other of the high intensity beams to be incident on the dichroic coating from within the substrate (from glass). We show that there are differences between the two options with respect to the laser-induced damage threshold (LIDT) properties of the coating, and analyze the differences in terms of the 527 nm and 1054 nm E-field intensity behaviors for air → coating and glass → coating incidence. Our E-field analysis indicates that LIDTs for air → coating incidence should be higher than for glass → coating incidence. LIDT measurements for Spol at the use AOI with ns pulses at 532 nm and 1064 nm confirm this analysis with the LIDTs for glass → coating incidence being about half those for air → coating incidence at both wavelengths. These LIDT results and the E-field analysis clearly indicate that the best beam combiner option is the one for which the high intensity 527 nm beam is incident on the coating from air and the 1054 nm high intensity beam is incident on the coating from glass.
Proceedings of SPIE - The International Society for Optical Engineering
Webb, Timothy J.; Kiefer, Mark L.; Gignac, Raymond; Baker, Stuart A.
The self-magnetic pinch (SMP) diode is an intense radiographic source fielded on the Radiographic Integrated Test Stand (RITS-6) accelerator at Sandia National Laboratories in Albuquerque, NM. The accelerator is an inductive voltage adder (IVA) that can operate from 2-10 MV with currents up to 160 kA (at 7 MV). The SMP diode consists of an annular cathode separated from a flat anode, holding the bremsstrahlung conversion target, by a vacuum gap. Until recently the primary imaging diagnostic utilized image plates (storage phosphors) which has generally low DQE at these photon energies along with other problems. The benefits of using image plates include a high-dynamic range, good spatial resolution, and ease of use. A scintillator-based X-ray imaging system or "gamma camera" has been fielded in front of RITS and the SMP diode which has been able to provide vastly superior images in terms of signal-to-noise with similar resolution and acceptable dynamic range.
Aerosol release in the range of less than 10 μm is of concern in transportation accident situations, particularly those involving radioactive contaminants and fuel fires. An accurate approximation of the Airborne Release Fraction (ARF) is important to properly estimate the impact of the contaminant release to the environment and surrounding population. An experiment was selected which studied contaminant entrainment in a fire and contained enough data sufficiently well presented to simulate with existing computational fluid dynamics (CFD) tools. Work was enabled by utilizing source terms for similar physical systems as presented in other publications. It is possible to investigate physical sensitivities from this model, giving insight into the experimental behavior, and physical processes. The effort also helps prioritize model development in the interest in furthering this predictive capability. Four mechanisms were identified as contributing to contaminant entrainment. Two of these mechanisms, entrainment due to evaporation induction and boiling atomization, were the focus of this study. Parameters, including boiling regime duration, evaporation regime particle size and turbulence, were varied because of their numeric uncertainty, while others like particle injection location, simulation time, and fuel height were varied based on a presumed importance. Entrainment values, as collected downstream of a release, are dependent on the magnitude of the entrainment mechanism, in which boiling far exceeded evaporation in quantity of entrained mass.
In this work we provide a template-based approach for generating locally refined all-hex meshes. We focus specifically on refinement of initially structured grids utilizing a 2-refinement approach where uniformly refined hexes are subdivided into eight child elements. The refinement algorithm consists of identifying marked nodes that are used as the basis for a set of four simple refinement templates. The target application for 2-refinement is a parallel grid-based all-hex meshing tool for high performance computing in a distributed environment. The result is a parallel consistent locally refined mesh requiring minimal communication and where minimum mesh quality is greater than scaled Jacobian 0.4 prior to smoothing.
Anion receptors that bind strongly to fluoride anions in organic solvents can help dissolve the lithium fluoride discharge products of primary carbon monofluoride (CFx) batteries, thereby preventing the clogging of cathode surfaces and improving ion conductivity. The receptors are also potentially beneficial to rechargeable lithium ion and lithium air batteries.We apply Density Functional Theory (DFT) to show that an oxalate-based pentafluorophenyl-boron anion receptor binds as strongly, or more strongly, to fluoride anions than many phenyl-boron anion receptors proposed in the literature. Experimental data shows marked improvement in electrolyte conductivity when this oxalate anion receptor is present. The receptor is sufficiently electrophilic that organic solvent molecules compete with F- for boron-site binding, and specific solvent effects must be considered when predicting its F- affinity. To further illustrate the last point, we also perform computational studies on a geometrically constrained boron ester that exhibits much stronger gas-phase affinity for both F- and organic solvent molecules. After accounting for specific solvent effects, however, its net F- affinity is about the same as the simple oxalate-based anion receptor. Finally, we propose that LiF dissolution in cyclic carbonate organic solvents, in the absence of anion receptors, is due mostly to the formation of ionic aggregates, not isolated F- ions.
This paper discusses the viability of using Bayesian Network (BN) models to support qualification planning in order to predict the suitability of Six Degrees of Freedom (6DOF) vibration testing for qualification. Qualification includes environmental testing such as temperature, vibration, and shock to support a stochastic argument about the suitability of a design. Qualification is becoming more complex and restricted yet available new technologies are not fully utilized. Technology has advanced to the state where 6DOF vibration shakers and control systems capable of high frequency tests are possible, but the problem using these systems is far more complex than traditional single degree of freedom (SDOF) tests. This challenges systems engineers as they strive to plan qualification in an environment where technical, environmental, and political constraints are coupled with the traditional cost, risk and schedule constraints. New technologies are also available for systems engineers to combine technical understanding with cost, risk and schedule factors to aid in decision making for complex problems such as qualification planning. BN models may provide the framework to aid Systems Engineers in planning qualification efforts with complex constraints. This paper discusses related work, the current approach and results of this research.
For a pilot-main injection strategy in a single cylinder light duty diesel engine, the dwell between the pilot- and maininjection events can significantly impact combustion noise. As the solenoid energizing dwell decreases below 200 μs, combustion noise decreases by approximately 3 dB and then increases again at shorter dwells. A zero-dimensional thermodynamic model has been developed to capture the combustion-noise reduction mechanism; heat-release profiles are the primary simulation input and approximating them as top-hat shapes preserves the noise-reduction effect. A decomposition of the terms of the underlying thermodynamic equation reveals that the direct influence of heat-release on the temporal variation of cylinder-pressure is primarily responsible for the trend in combustion noise. Fourier analyses reveal the mechanism responsible for the reduction in combustion noise as a destructive interference in the frequency range between approximately 1 kHz and 3 kHz. This interference is dependent on the timing of increases in cylinder-pressure during pilot heat-release relative to those during main heat-release. The mechanism by which combustion noise is attenuated is fundamentally different from the traditional noise reduction that occurs with the use of long-dwell pilot injections, for which noise is reduced primarily by shortening the ignition delay of the main injection. Band-pass filtering of measured cylinderpressure traces provides evidence of this noise-reduction mechanism in the real engine. When this close-coupled pilot noise-reduction mechanism is active, metrics derived from cylinder-pressure such as the location of 50% heat-release, peak heat-release rates, and peak rates of pressure rise cannot be used reliably to predict trends in combustion noise. The quantity and peak value of the pilot heat-release affect the combustion noise reduction mechanism, and maximum noise reduction is achieved when the height and steepness of the pilot heat-release profile are similar to the initial rise of the main heat-release event. A variation of the initial rise-rate of the main heat-release event reveals trends in combustion noise that are the opposite of what would happen in the absence of a close-coupled pilot. The noise-reduction mechanism shown in this work may be a powerful tool to improve the tradeoffs among fuel efficiency, pollutant emissions, and combustion noise.
The Seven Percent Critical Experiment (7uPCX) was designed to provide benchmark criticality and reactor physics data for water-moderated pin-fueled nuclear reactor cores. The enrichment of the fuel was chosen to explore the enrichment range above the current 5% ceiling for US commercial pressurized water reactors. The experiment was part of the US Department of Energy (DOE) Nuclear Energy Research Initiative (NERI) Project 01-124 titled “Reactor Physics and Criticality Benchmark Evaluations for Advanced Nuclear Fuel”. The NERI project was a collaboration between AREVA Federal Services, LLC; the University of Florida; Oak Ridge National Laboratory; and Sandia National Laboratories (SNL). The experiments at Sandia are currently supported by the DOE National Nuclear Security Administration Nuclear Criticality Safety Program. Two sets of benchmark experiments have been completed and documented as LEU-COMP-THERM-080 and LEU-COMP-THERM-078. Those experiments were done with the number of fuel rods in the fully-reflected array as the approach parameter. The experiments reported here are similar to those in LEU-COMP-THERM-080 except that the arrays are partially-reflected – the arrays were larger than would be possible with full reflection and the approach-to-critical experiments were done with the depth of the water in the critical assembly as the approach parameter. These experiments are reported as LEU-COMP-THERM-096.
The reproducing kernel particle method (RKPM) is a meshfree method for computational solid mechanics that can be tailored for an arbitrary order of completeness and smoothness. The primary advantage of RKPM relative to standard finiteelement (FE) approaches is its capacity to model large deformations, material damage, and fracture. Additionally, the use of a meshfree approach offers great flexibility in the domain discretization process and reduces the complexity of mesh modifications such as adaptive refinement. We present an overview of the RKPM implementation in the Sierra/SolidMechanics analysis code, with a focus on verification, validation, and software engineering for massively parallel computation. Key details include the processing of meshfree discretizations within a FE code, RKPM solution approximation and domain integration, stress update and calculation of internal force, and contact modeling. The accuracy and performance of RKPM are evaluated using a set of benchmark problems. Solution verification, mesh convergence, and parallel scalability are demonstrated using a simulation of wave propagation along the length of a bar. Initial model validation is achieved through simulation of a Taylor bar impact test. The RKPM approach is shown to be a viable alternative to standard FE techniques that provides additional flexibility to the analyst community.
Two of the most popular deterministic radiation transport methods for treating the angular dependence of the radiative intensity for heat transfer: The discrete ordinates and simplified spherical harmonics approximations are compared. A problem with discontinuous boundary conditions is included to evaluate ray effects for discrete ordinates solutions. Mesh resolution studies are included to ensure adequate convergence and evaluate the effects of the contribution of false scattering. All solutions are generated using finite element spatial discretization. Where applicable, any stabilization used is included in the description of the approximation method or the statement of the governing equations. A previous paper by the author presented results for a set of 2D benchmark problems for the discrete ordinates method using the PN-TN quadrature of orders 4, 6, and 8 as well as the P1, M1, and SP3 approximations. This paper expands that work to include the Lathrop-Carlson level symmetric quadrature of order up to 20 as well as the Lebedev quadrature of order up to 76 and simplified spherical harmonics of odd orders from 1 to 15. Two 3D benchmark problems are considered here. The first is a canonical problem of a cube with a single hot wall. This case is used primarily to demonstrate the potentially unintuitive interaction between mesh resolution, quadrature order, and solution error. The second case is meant to be representative of a pool fire. The temperature and absorption coefficient distributions are defined analytically. In both cases, the relative error in the radiative flux or the radiative flux divergence within a volume is considered as the quantity of interest as these are the terms that enter into the energy equation. The spectral dependence of the optical properties and the intensity is neglected.
Carbonyl oxides, also known as Criegee intermediates, are key intermediates in both gas phase ozonolysis of unsaturated hydrocarbons in the troposphere and solution phase organic synthesis via ozonolysis. Although the study of Criegee intermediates in both arenas has a long history, direct studies in the gas phase have only recently become possible through new methods of generating stabilised Criegee intermediates in sufficient quantities. This advance has catalysed a large number of new experimental and theoretical investigations of Criegee intermediate chemistry. In this article we review the physical chemistry of Criegee intermediates, focusing on their molecular structure, spectroscopy, unimolecular and bimolecular reactions. These recent results have overturned conclusions from some previous studies, while confirming others, and have clarified areas of investigation that will be critical targets for future studies. In addition to expanding our fundamental understanding of Criegee intermediates, the rapidly expanding knowledge base will support increasingly predictive models of their impacts on society.
Proceedings - 15th European Turbulence Conference, ETC 2015
Smith, Thomas M.; Christon, Mark A.; Baglietto, Emilio; Luo, Hong
Accurate simulation of turbulence remains one of the most challenging problems in nuclear reactor analysis and design. Due to limitations in computing resources, Reynolds averaged Navier Stokes models (RANS) continue to play an important role in reactor simulations. The Consortium for advanced simulations of light water reactors (CASL) is a Department of Energy technology hub that is investing in research and development of a state-of-the-art computational fluid dynamics capability to meet the challenges of turbulent simulation of nuclear reactors. In this presentation, we assess several RANS eddy viscosity models appropriate for single-phase incompressible turbulent flows. Specifically, we compare the single equation Splalart-Allmaras to several variations of the k − ε model. The assessment takes into consideration elements of full system reactor cores such as complex geometries, heterogeneous meshes, swirling flow, near wall flow behavior, heat transfer and robustness issues. The goal of this strategically oriented assessment is to provide an accurate and robust turbulent simulation capability for the CASL community. Metrics of performance will be constructed by comparing different models on a strategically chosen set of problems that represent reactor core sub-systems.
Austenitic stainless steels such as 304L are frequently used for hydrogen service applications due to their excellent resistance to hydrogen embrittlement. However, welds in austenitic stainless steels often contain microstructures that are more susceptible to the presence of hydrogen. This study examines the tensile strength and ductility of a multi-pass gas tungsten arc weld made on 304L cross-rolled plate using 308L weld filler wire. Sub-sized tensile specimens were used to ensure the entire gage section of each tensile specimen consisted of weld metal. Specimens were extracted in both axial and transverse orientations, and at three different depths within the weld (root, center, and top). Yield strength decreased and ductility increased moving from the root to the top of the weld. A subset of specimens was precharged with hydrogen at 138 MPa (20,000 psi) and 300oC prior to testing, resulting in a uniform hydrogen concentration of 7700 appm. The presence of hydrogen resulted in a slight increase in yield and tensile strength and a roughly 50% decrease in tensile elongation and reduction in area, compared to the hydrogen-free properties.
Non-premixed oxy-fuel combustion of natural gas is used in industrial applications where highintensity heat is required, such as glass manufacturing and metal forging and shaping. In these applications, the high flame temperatures achieved by oxy-fuel increases radiative heat transfer to the surfaces of interest and soot formation within the flame is desired for further augmentation of radiation. However, the high energy consumption and cost of traditional methods of oxygen production have limited the penetration of oxy-fuel combustion technologies. New approaches to oxygen production, using ion transport membranes or metal organic frameworks (MOFs), are being developed that may reduce the oxygen production costs associated with conventional cryogenic air separation, but which are likely to be more economical for intermediate levels of oxygen enrichment of air, rather than for the high-purity oxygen that is produced by conventional cryogenic air separation. To determine the influence of oxygen enrichment on soot formation and radiation, we developed a non-premixed coannular burner in which oxygen concentrations and flow rates can be independently varied, to distinguish the effects of turbulent mixing intensity, characteristic flame residence time, and oxygen enrichment on soot formation and flame radiation intensity. Local radiation intensities and soot concentrations have been measured using a thin-film thermopile and planar laser-induced incandescence (LII), respectively. Results show that turbulence intensity has a marked effect on soot formation and thermal radiation. Somewhat surprisingly, soot formation is found to increase as the oxygen concentration decreases from 100% to 50%, for flames in which the turbulence intensity remains constant. At the same time, the thermal radiation from these flames only decreases gradually for an extended range of oxygen concentrations. These results suggest that properly designed oxygen-enriched burners that enhance soot formation for intermediate levels of oxygen purity may be able to achieve similar thermal radiation intensities as traditional oxy-fuel burners utilizing high-purity oxygen.
Although the high-performance computing (HPC) community increasingly embraces object-oriented programming (OOP), most HPC OOP projects employ the C++ programming language. Until recently, Fortran programmers interested in mining the benefits of OOP had to emulate OOP in Fortran 90/95. The advent of widespread compiler support for Fortran 2003 now facilitates explicitly constructing object-oriented class hierarchies via inheritance and leveraging related class behaviors such as dynamic polymorphism. Although C++ allows a class to inherit from multiple parent classes, Fortran and several other OOP languages restrict or prohibit explicit multiple inheritance relationships in order to circumvent several pitfalls associated with them. Nonetheless, what appears as an intrinsic feature in one language can be modeled as a user-constructed design pattern in another language. The present paper demonstrates how to apply the facade structural design pattern to support a multiple inheritance class relationship in Fortran 2003. The design unleashes the power of the associated class relationships for modeling complicated data structures yet avoids the ambiguities that plague some multiple inheritance scenarios.
Associative memory refers to remembering the association between two items, such as a face and a name. It is a crucial part of daily life, but it is also one of the first aspects of memory performance that is impacted by aging and by Alzheimer's disease. Evidence suggests that transcranial direct current stimulation (tDCS) can improve memory performance, but few tDCS studies have investigated its impact on associative memory. In addition, no prior study of the effects of tDCS on memory performance has systematically evaluated the impact of tDCS on different types of memory assessments, such as recognition and recall tests. In this study, we measured the effects of tDCS on associative memory performance in healthy adults, using both recognition and recall tests. Participants studied face-name pairs while receiving either active (30 min, 2 mA) or sham (30 min, 0.1 mA) stimulation with the anode placed at F9 and the cathode placed on the contralateral upper arm. Participants in the active stimulation group performed significantly better on the recall test than participants in the sham group, recalling 50% more names, on average, and making fewer recall errors. However, the two groups did not differ significantly in terms of their performance on the recognition memory test. This investigation provides evidence that stimulation at the time of study improves associative memory encoding, but that this memory benefit is evident only under certain retrieval conditions.
While deep borehole disposal of nuclear waste should rely primarily on off-the-shelf technologies pioneered by the oil and gas and geothermal industries, the development of new science and technology will remain important. Key knowledge gaps have been outlined in the research roadmap for deep boreholes (B. Arnold et al, 2012, Research, Development, and Demonstration Roadmap for Deep Borehole Disposal, Sandia National Laboratories, SAND2012-8527P) and in a recent Deep Borehole Science Needs Workshop. Characterizing deep crystalline basement, understanding the nature and role of deep fractures, more precisely age-dating deep groundwaters, and demonstrating long-term performance of seals are all important topics of interest. Overlapping deep borehole and enhanced geothermal technology needs include: quantification of seal material performance/failure, stress measurement beyond the borehole, advanced drilling and completion tools, and better subsurface sensors. A deep borehole demonstration has the potential to trigger more focused study of deep hydrology, high temperature brine-rock interaction, and thermomechanical behavior.
Cracks in glass-to-metal seals can be a threat to the hermeticity of isolated electronic components. Design and manufacturing of the materials and processes can be tailored to minimize the residual stresses responsible for cracking. However, this requires high fidelity material modeling accounting for the plastic strains in the metals, mismatched thermal shrinkage and property changes experienced as the glass solidifies during cooling of the assembly in manufacturing. Small plastic strains of just a few percent are typical during processing of glass-to-metal seals and yet can generate substantial tensile stresses in the glass during elastic unloading in thermal cycling. Therefore, experimental methods were developed to obtain very accurate measurements of strain near and just beyond the proportional limit. Small strain tensile characterization experiments were conducted with varying levels and rates of strain ratcheting over the temperatures range of -50 to 550 °C, with particular attention near the glass transition temperature of 500 °C. Additional experiments were designed to quantify the effects of stress relaxation and reloading. The experimental techniques developed and resulting data will be presented. Details of constitutive modeling efforts and glass material experiments and modeling can be found in Chambers et al. (Characterization & modeling of materials in glass-to-metal seals: Part I. SAND14-0192. Sandia National Laboratories, January 2014).
New blade designs are planned to support future research campaigns at the SWiFT facility in Lubbock, Texas. The sub-scale blades will reproduce specific aerodynamic characteristics of utility-scale rotors. Reynolds numbers for megawatt-, utility-scale rotors are generally vary from 2-8 million. The thickness of inboard airfoils for these large rotors are typically as high as 35-40%. The thickness and the proximity to three-dimensional flow of these airfoils present design and analysis challenges, even at the full scale, but more than a decade of experience with the airfoils in numerical simulation, in the wind tunnel, and in the field has generated confidence in their performance. When used on a sub-scale rotor, Reynolds number regimes are significantly lower for the inboard blade, ranging from 0.7 to 1 million. Performance of the thick airfoils in this regime is uncertain because of the lack of wind tunnel data and the inherent challenge associated with associated numerical simulations. This report documents efforts to determine the most capable analysis tools to support these simulations and to improve understanding of the aerodynamic properties of thick airfoils in this Reynolds number regime. Numerical results from various codes of four airfoils are verified against previously published wind tunnel results where data at those Reynolds numbers are available. Results are then computed for other Reynolds numbers of interest.
We present a methodology to assess the predictive fidelity of multiscale simulations by incorporating uncertainty in the information exchanged between the components of an atomisticto-continuum simulation. We account for both the uncertainty due to finite sampling in molecular dynamics (MD) simulations and the uncertainty in the physical parameters of the model. Using Bayesian inference, we represent the expensive atomistic component by a surrogate model that relates the long-term output of the atomistic simulation to its uncertain inputs. We then present algorithms to solve for the variables exchanged across the atomistic-continuum interface in terms of polynomial chaos expansions (PCEs). We consider a simple Couette flow where velocities are exchanged between the atomistic and continuum components, while accounting for uncertainty in the atomistic model parameters and the continuum boundary conditions. Results show convergence of the coupling algorithm at a reasonable number of iterations. The uncertainty in the obtained variables significantly depends on the amount of data sampled from the MD simulations and on the width of the time averaging window used in the MD simulations.
We introduce a new continuous-variable quantum key distribution (CV-QKD) protocol, self-referenced CV-QKD, that eliminates the need for transmission of a high-power local oscillator between the communicating parties. In this protocol, each signal pulse is accompanied by a reference pulse (or a pair of twin reference pulses), used to align Alice's and Bob's measurement bases. The method of phase estimation and compensation based on the reference pulse measurement can be viewed as a quantum analog of intradyne detection used in classical coherent communication, which extracts the phase information from the modulated signal. We present a proof-of-principle, fiber-based experimental demonstration of the protocol and quantify the expected secret key rates by expressing them in terms of experimental parameters. Our analysis of the secret key rate fully takes into account the inherent uncertainty associated with the quantum nature of the reference pulse(s) and quantifies the limit at which the theoretical key rate approaches that of the respective conventional protocol that requires local oscillator transmission. The self-referenced protocol greatly simplifies the hardware required for CV-QKD, especially for potential integrated photonics implementations of transmitters and receivers, with minimum sacrifice of performance. As such, it provides a pathway towards scalable integrated CV-QKD transceivers, a vital step towards large-scale QKD networks.
We study nanoporous-carbon (NPC) grown via pulsed laser deposition (PLD) as a sorbent coating on 96.5-MHz surface-acousticwave (SAW) devices to detect trihalomethanes (THMs), regulated byproducts from the chemical treatment of drinking water. Using both insertion-loss and isothermal-response measurements from known quantities of chloroform, the highest vapor pressure THM, we optimize the NPC mass-density at 1.05 ± 0.08 g/cm3 by controlling the background argon pressure during PLD. Precise THM quantities in a chlorobenzene solvent are directly injected into a separation column and detected as the phase-angle shift of the SAW device output compared to the drive signal. Using optimized NPC-coated SAWs, we study the chloroform response as a function of operating temperatures ranging from 10.50°C. Finally, we demonstrate individual responses from complex mixtures of all four THMs, with masses ranging from 10.2000 ng, after gas chromatography separation. Estimates for each THM detection limit using a simple peak-height response evaluation are 4.4 ng for chloroform and 1 ng for bromoform; using an integrated-peak area response analysis improves the detection limits to 0.73 ng for chloroform and 0.003 ng bromoform.
A position-aware linear solid (PALS) peridynamic constitutive model is proposed for isotropic elastic solids. The PALS model addresses problems that arise, in ordinary peridynamic material models such as the linear peridynamic solid (LPS), due to incomplete neighborhoods near the surface of a body. Improved model behavior in the vicinity of free surfaces is achieved through the application of two influence functions that correspond, respectively, to the volumetric and deviatoric parts of the deformation. The model is position-aware in that the influence functions vary over the body and reflect the proximity of each material point to free surfaces. Demonstration calculations on simple benchmark problems show a sharp reduction in error relative to the LPS model.
Gaseous mixtures of diatomic hydrogen isotopologues and helium are often encountered in the nuclear energy industry and in analytical chemistry. Compositions of stored mixtures can vary due to interactions with storage and handling materials. When tritium is present, it decays to form ions and helium-3, both of which can lead to further compositional variation. Monitoring of composition is typically achieved by mass spectrometry, a method that is bulky and energy-intensive. Mass spectrometers disperse sample material through vacuum pumps, which is especially troublesome if tritium is present. Our ultimate goal is to create a compact, fast, low-power sensor that can determine composition with minimal gas consumption and waste generation, as a complement to mass spectrometry that can be instantiated more widely. We propose calorimetry of metal hydrides as an approach to this, due to the strong isotope effect on gas absorption, and demonstrate the sensitivity of measured heat flow to atomic composition of the gas. Peak shifts are discernible when mole fractions change by at least 1%. A mass flow restriction results in a unique dependence of the measurement on helium concentration. A mathematical model is presented as a first step toward prediction of the peak shapes and positions. The model includes a useful method to compute estimates of phase diagrams for palladium in the presence of arbitrary mixtures of hydrogen isotopologues. We expect that this approach can be used to deduce unknown atomic compositions from measured calorimetric data over a useful range of partial pressures of each component.
Low temperature cofired ceramic (LTCC) is established as an excellent packaging technology for high reliability, high density microelectronics. LTCC multichip modules (MCMs) comprising both 'surface mount' and 'chip and wire' technologies provide additional customization for performance. Long term robustness of the packages is impacted by the selection of seal frame and lid materials used to enclose the components inside distinct rooms in LTCC MCMs. An LTCC seal frame and lid combination has been developed that is capable of meeting the sealing and electromagnetic shielding requirements of MCMs. This work analyzes the stress and strain performance of various seal frame and lid materials, sealing materials, and configurations. The application for the MCM will impact selection of the seal frame, lid, and sealing materials based on this analysis.
By relating the response theory of optical forces to waveguide dispersion, we are able to employ dispersion engineering to optimize radiation pressure forces at the nanoscale in W1 photonic crystal waveguides.
Cavity receivers used in solar power towers and dish concentrators may lose considerable energy by natural convection, which reduces the overall system efficiency. A validated numerical receiver model is desired to better understand convection processes and aid in heat loss minimization efforts. The purpose ofthis investigation was to evaluate heat loss predictions using the commercial computational fluid dynamics (CFD) software packages fluent 13.0 and solidworks flow simulation 2011 against experimentally measured heat losses for a heated cubical cavity receiver model (Kraabel, 1983, "An Experimental Investigation of the Natural Convection From a Side-Facing Cubical Cavity," Proceedings of the ASME JSME Thermal Engineering Joint Conference, Vol. 1, pp. 299-306) and a cylindrical dish receiver model (Taumoefolau et al., 2004, "Experimental Investigation of Natural Convection Heat Loss From a Model Solar Concentrator Cavity Receiver," ASME J. Sol. Energy Eng., 126(2), pp. 801-807). Simulated convective heat loss was underpredicted by 45% for the cubical cavity when experimental wall temperatures were implemented as isothermal boundary conditions and 32% when the experimental power was applied as a uniform heat flux from the cavity walls. Agreement between software packages was generally within 10%. Convective heat loss from the cylindrical dish receiver model was accurately predicted within experimental uncertainties by both simulation codes using both isothermal and constant heat flux wall boundary conditions except when the cavity was inclined at angles below 15 deg and above 75 deg, where losses were under- and overpredicted by fluent and solidworks, respectively. Comparison with empirical correlations for convective heat loss from heated cavities showed that correlations by Kraabel (1983, "An Experimental Investigation of the Natural Convection From a Side-Facing Cubical Cavity," Proceedings ofthe ASME JSME Thermal Engineering Joint Conference, Vol. 1, pp. 299-306) and for individual heated flat plates oriented to the cavity geometry (Pitts and Sissom, 1998, Schaum's Outline of Heat Transfer, 2nd ed., McGraw Hill, New York, p. 227) predicted heat losses from the cubical cavity to within experimental uncertainties. Correlations by Clausing (1987, "Natural Convection From Isothermal Cubical Cavities With a Variety of Side-Facing Apertures," ASME J. Heat Transfer, 109(2), pp. 407-412) and Paitoonsurikarn et al. (2011, "Numerical Investigation of Natural Convection Loss From Cavity Receivers in Solar Dish Applications," ASME J. Sol. Energy Eng. 133(2), p. 021004) were able to do the same for the cylindrical dish receiver. No single correlation was valid for both experimental receivers. The effect ofdifferent turbulence and air-property models within fluent were also investigated and compared in this study. However, no model parameter was found to produce a change large enough to account for the deficient convective heat loss simulated for the cubical cavity receiver case.
Listing all triangles is a fundamental graph operation. Triangles can have important interpretations in real-world graphs, especially social and other interaction networks. Despite the lack of provably efficient (linear, or slightly super linear) worst-case algorithms for this problem, practitioners run simple, efficient heuristics to find all triangles in graphs with millions of vertices. How are these heuristics exploiting the structure of these special graphs to provide major speedups in running time? We study one of the most prevalent algorithms used by practitioners. A trivial algorithm enumerates all paths of length 2, and checks if each such path is incident to a triangle. A good heuristic is to enumerate only those paths of length 2 in which the middle vertex has the lowest degree. It is easily implemented and is empirically known to give remarkable speedups over the trivial algorithm. We study the behavior of this algorithm over graphs with heavy-tailed degree distributions, a defining feature of real-world graphs. The erased configuration model (ECM) efficiently generates a graph with asymptotically (almost) any desired degree sequence. We show that the expected running time of this algorithm over the distribution of graphs created by the ECM is controlled by the l4/3-norm of the degree sequence. Norms of the degree sequence are a measure of the heaviness of the tail, and it is precisely this feature that allows non trivial speedups of simple triangle enumeration algorithms. As a corollary of our main theorem, we prove expected linear-time performance for degree sequences following a power law with exponent α ≥ 7/3, and non trivial speedup whenever α ∈ (2, 3).
Computational science and engineering application programs are typically large, complex, and dynamic, and are often constrained by distribution limitations. As a means of making tractable rapid explorations of scientific and engineering application programs in the context of new, emerging, and future computing architectures, a suite of "miniapps" has been created to serve as proxies for full scale applications. Each miniapp is designed to represent a key performance characteristic that does or is expected to significantly impact the runtime performance of an application program. In this paper we introduce a methodology for assessing the ability of these miniapps to effectively represent these performance issues. We applied this methodology to three miniapps, examining the linkage between them and an application they are intended to represent. Herein we evaluate the fidelity of that linkage. This work represents the initial steps required to begin to answer the question, "Under what conditions does a miniapp represent a key performance characteristic in a full app?"
The chlorine atom-initiated oxidation of two unsaturated primary C5 alcohols, prenol (3-methyl-2-buten-1-ol, (CH3)2CCHCH2OH) and isoprenol (3-methyl-3-buten-1-ol, CH2C(CH3)CH2CH2OH), is studied at 550 K and low pressure (8 Torr). The time- and isomer-resolved formation of products is probed with multiplexed photoionization mass spectrometry (MPIMS) using tunable vacuum ultraviolet ionizing synchrotron radiation. The peroxy radical chemistry of the unsaturated alcohols appears much less rich than that of saturated C4 and C5 alcohols. The main products observed are the corresponding unsaturated aldehydes - prenal (3-methyl-2-butenal) from prenol oxidation and isoprenal (3-methyl-3-butenal) from isoprenol oxidation. No significant products arising from QOOH chemistry are observed. These results can be qualitatively explained by the formation of resonance stabilized allylic radicals via H-abstraction in the Cl + prenol and Cl + isoprenol initiation reactions. The loss of resonance stabilization upon O2 addition causes the energies of the intermediate wells, saddle points, and products to increase relative to the energy of the initial radicals and O2. These energetic shifts make most product channels observed in the peroxy radical chemistry of saturated alcohols inaccessible for these unsaturated alcohols. The experimental findings are underpinned by quantum-chemical calculations for stationary points on the potential energy surfaces for the reactions of the initial radicals with O2. Under our conditions, the dominant channels in prenol and isoprenol oxidation are the chain-terminating HO2-forming channels arising from radicals, in which the unpaired electron and the -OH group are on the same carbon atom, with stable prenal and isoprenal co-products, respectively. These findings suggest that the presence of CC double bonds in alcohols will reduce low-temperature reactivity during autoignition.
Hybrid femtosecond/picosecond rotational coherent anti-Stokes Raman spectroscopy (CARS) is developed utilizing a two-beam phase-matching approach for one-dimensional (1D) measurements demonstrated in an impinging jet burner to probe time-resolved head on quenching (HOQ) of a methane/air premixed flame at Φ = 1.0 and Reynolds number = 5000. Single-laser-shot 1D temperature profiles are obtained over a distance of at least 4 mm by fitting the pure-rotational N2 CARS spectra to a spectral library calculated from a time-domain CARS code. An imaging resolution of ∼61 μm is obtained in the 1D-CARS measurements. The acquisition of single-shot 1D CARS measurements, as opposed to traditional point-wise CARS techniques, enables new spatially correlated conditional statistics to be determined, such as the position, magnitude, and fluctuations of the instantaneous temperature gradient. The temperature gradient increases as the flame approaches the metal surface, and decreases during quenching. The standard deviation of the temperature gradient follows the same trend as the temperature gradient, increasing as the flame front approaches the surface, and decreasing after quenching.
The oxidation of 1,3-butadiene/n-butanol flames was studied in a combined experimental and modeling work. The goal is to provide a detailed combustion chemistry model that allows for identification of the important pathways for butadiene and butanol oxidation as well as the formation of soot precursors and aromatics. Therefore, the chemical composition has been investigated for three low-pressure (20-30 Torr) premixed flames, with different shares of butanol ranging between 25% and 75% compared to butadiene in 50% argon. Mole fraction profiles of reactants, products, and intermediates including C3Hx and C4Hx radicals as well as mono-aromatics such as benzyl radicals, were measured quantitatively as a function of height above burner surface employing flame-sampled molecular-beam mass spectrometry (MBMS) utilizing photoionization with tunable vacuum-ultraviolet synchrotron radiation. The comparison of measured species profiles with modeling results provides a comprehensive view of the reaction model's quality and predictive capability with respect to the combustion chemistry of 1,3-butadiene and n-butanol under the current low-pressure, high-temperature conditions. In general, a good agreement was found between experimental and modeled results. Reaction flux and sensitivity analysis were used to get more insights into the combustion of the fuels.
Nawdiyal, A.; Hansen, Nils; Zeuch, T.; Seidel, L.; Mauß, F.
An existing detailed and broadly validated kinetic scheme is augmented to capture the flame chemistry of 1-hexene under stoichiometric and fuel rich conditions including benzene formation pathways. In addition, the speciation in a premixed stoichiometric 1-hexene flame (flat-flame McKenna-type burner) has been studied under a reduced pressure of 20-30 mbar applying flame-sampling molecular-beam time-of-flight mass spectrometry and photoionization by tunable vacuum-ultraviolet synchrotron radiation. Mole fraction profiles of 40 different species have been measured and validated against the new detailed chemical reaction model consisting of 275 species and 3047 reversible elementary reactions. A good agreement of modelling results with the experimentally observed mole fraction profiles has been found under both stoichiometric and fuel rich conditions providing a sound basis for analyzing benzene formation pathways during 1-hexene combustion. The analysis clearly shows that benzene formation via the fulvene intermediate is a very important pathway for 1-hexene.
The growth of poly-cyclic aromatic hydrocarbon (PAH) soot precursors are observed using a two-laser technique combining laser-induced fluorescence (LIF) of PAH with laser-induced incandescence (LII) of soot in a diesel engine under low-temperature combustion (LTC) conditions. The broad mixture distributions and slowed chemical kinetics of LTC "stretch out" soot-formation processes in both space and time, thereby facilitating their study. Imaging PAH-LIF from pulsed-laser excitation at three discrete wavelengths (266, 532, and 633 nm) reveals the temporal growth of PAH molecules, while soot-LII from a 1064-nm pulsed laser indicates inception to soot. The distribution of PAH-LIF also grows spatially within the combustion chamber before soot-LII is first detected. The PAH-LIF signals have broad spectra, much like LII, but typically with spectral profile that is inconsistent with laser-heated soot. Quantitative natural-emission spectroscopy also shows a broad emission spectrum, presumably from PAH chemiluminescence, temporally coinciding with of the PAH-LIF.
This study investigates combustion variability of a stratified-charge direct-injection spark ignited (DISI) engine, operated with near-TDC injection of E70 fuel and a spark timing that occurs during the early part of the fuel injection. Using EGR, low engine-out NOx can be achieved, but at the expense of increased combustion variability at higher engine speeds. Initial motored tests at different speeds reveal that the in-cylinder gas flow becomes sufficiently strong at 2000 rpm to cause significant cycle-to-cycle variations of the spray penetration. Hence, the fired tests focus on operation at 2000 rpm with N2 dilution ([O2] = 19% and 21%) to simulate EGR. In-cylinder flow, spray, and early-flame measurements are correlated to reveal their effect on the combustion variability. Results reveal two types of flow/spray-interactions that predict the likelihood of a partial burn. (1) Proper flow direction before injection with a more collapsed spray leads to high kinetic energy of the flow during injection, thus generating a rapid early burn, which ensures complete combustion, regardless of the EGR level. (2) Improper flow direction and less collapsed spray generate low flow energy during the early phase of combustion. For this second type of flow/spray-interaction, application of EGR results in a partial-burn frequency of 30%, whereas without EGR, early combustion is shown to be insensitive to flow variations. Flame-probability maps illustrate that the partial-burn cycles for operation with EGR have a weak flame development in that the flame does not develop uniformly and reliably from the spark plug. Without EGR, the flame development is more repeatable regardless of the type of flow/spray-interaction, at the expense of higher NOx emissions.
This paper presents a detailed investigation of 2-methylbutanol combustion chemistry in low-pressure premixed flames. This chemistry is of particular interest to study because this compound is potentially a lignocellulosic-based, next-generation biofuel. The detailed chemical structure of a stoichiometric low-pressure (25 Torr) flame was determined using flame-sampling molecular-beam mass spectrometry. A total of 55 species were identified and subsequently quantitative mole fraction profiles as function of distance from the burner surface were determined. In an independent effort, a detailed flame chemistry model for 2-methylbutanol was assembled based on recent knowledge gained from combustion chemistry studies for butanol isomers ([Sarathy et al. Combust. Flame 159 (6) (2012) 2028-2055]) and iso-pentanol (3-methylbutanol) [Sarathy et al. Combust. Flame 160 (12) (2013) 2712-2728]. Experimentally determined and modeled mole fraction profiles were compared to demonstrate the model's capabilities. Examples of individual mole fraction profiles are discussed together with the most significant fuel consumption pathways to highlight the combustion chemistry of 2-methylbutanol. Discrepancies between experimental and modeling results are used to suggest areas where improvement of the kinetic model would be needed.
Final burnout of char particles from practical fuels such as coal and biomass occurs in the presence of a large ash component. Also, newly utilized coal resources, such as those from India, often contain much larger ash fractions than have traditionally been utilized. In the past, the inhibitory influence of ash on pulverized coal particle combustion has been most frequently modeled using an ash film model, though such films are rarely found when examining partially combusted particles. Conversely, some measurements have suggested that mineral components exposed on the surface of burning pulverized coal (pc) particles may diffuse back into the char matrix, the effect of which can be modeled as an ash dilution effect. To explore the implications of these different ash inhibition models on the temporal evolution of char combustion during burnout, we have developed a new computational model that considers the possibility of an ash film effect, an ash dilution effect, or some arbitrary combination of the two effects acting in tandem, which is the most realistic scenario. This new model predicts that restricted diffusion through the ash film has a significant impact on the char burnout rate throughout its lifetime, whereas char dilution only inhibits combustion significantly when most of the char has been consumed and the combustion mode shifts from predominantly external diffusion control to mixed diffusion control, with sensitivity to both external and internal diffusion resistance. The comparison of the model predictions with experimental results also confirms the previously suggested need to include gasification reaction steps when modeling coal char combustion.