The overall goal of this project is to establish a network of TCUs with essential advanced manufacturing (AM) facilities, associated training and education programs, and private sector and federal agency partnerships to both prepare an American Indian AM workforce and create economic and employment opportunities within Tribal communities through design, manufacturing, and marketing of high quality products. Some examples of high quality products involve next generation grid components such as mechanical energy storage, cabling for distribution of energy, and electrochemical energy storage enclosures. Sandia National Laboratories (Sandia) is tasked to provide technical advising, planning, and academic program development support for the TCU/American Indian Higher Education Consortium (AIHEC) Advanced Manufacturing Project. The TCUs include Bay Mills Community College (BMCC), Cankdeska Cikana Community College (CCCC), Navajo Technical University (NTU), Southwestern Indian Polytechnic Institute (SIPI), and Salish Kooteani College. AIHEC and Sandia, with collaboration from SIPI, will be establishing an 8-week summer institute on the SIPI campus during the summer of 2017. Up to 20 students from TCUs are anticipated to take part in the summer program. The goal of the program is to bring AM science, technology, engineering, and mathematics (STEM) awareness and opportunities for the American Indian students. Prior to the summer institute, Sandia will be providing reviews on curriculum plans at the each of the TCUs to ensure the content is consistent with current AM design and engineering practice. In addition, Sandia will provide technical assistance to each of the TCUs in regards to their current AM activities.
Physical property measurements including viscosity, density, thermal conductivity, and heat capacity of low-molecular weight polydimethylsiloxane (PDMS) fluids were measured over a wide temperature range (-50°C to 150°C when possible). Properties of blends of 1 cSt and 20 cSt PDMS fluids were also investigated. Uncertainties in the measurements are cited. These measurements will provide greater fidelity predictions of environmental sensing device behavior in hot and cold environments.
The 2017 Annual Terrestrial Sampling Plan for Sandia National Laboratories/New Mexico on Kirtland Air Force Base has been prepared in accordance with the “Letter of Agreement Between Department of Energy, National Nuclear Security Administration, Sandia Field Office (DOE/NNSA/SFO) and 377th Air Base Wing (ABW), Kirtland Air Force Base (KAFB) for Terrestrial Sampling” (signed January 2017), Sandia National Laboratories, New Mexico (SNL/NM). The Letter of Agreement requires submittal of an annual terrestrial sampling plan.
This report describes findings from the culminating experiment of the LDRD project entitled, "Analyst-to-Analyst Variability in Simulation-Based Prediction". For this experiment, volunteer participants solving a given test problem in engineering and statistics were interviewed at different points in their solution process. These interviews are used to trace differing solutions to differing solution processes, and differing processes to differences in reasoning, assumptions, and judgments. The issue that the experiment was designed to illuminate -- our paucity of understanding of the ways in which humans themselves have an impact on predictions derived from complex computational simulations -- is a challenging and open one. Although solution of the test problem by analyst participants in this experiment has taken much more time than originally anticipated, and is continuing past the end of this LDRD, this project has provided a rare opportunity to explore analyst-to-analyst variability in significant depth, from which we derive evidence-based insights to guide further explorations in this important area.
This goal of this project is to address the current inability to assess the overall error and uncertainty of data products developed and distributed by DOE’s Consequence Management (CM) Program. This is a widely recognized shortfall, the resolution of which would provide a great deal of value and defensibility to the analysis results, data products, and the decision making process that follows this work. A global approach to this problem is necessary because multiple sources of error and uncertainty contribute to the ultimate production of CM data products. Therefore, this project will require collaboration with subject matter experts across a wide range of FRMAC skill sets in order to quantify the types of uncertainty that each area of the CM process might contain and to understand how variations in these uncertainty sources contribute to the aggregated uncertainty present in CM data products. The ultimate goal of this project is to quantify the confidence level of CM products to ensure that appropriate public and worker protections decisions are supported by defensible analysis.
Solving sparse linear systems from the discretization of elliptic partial differential equations (PDEs) is an important building block in many engineering applications. Sparse direct solvers can solve general linear systems, but are usually slower and use much more memory than effective iterative solvers. To overcome these two disadvantages, a hierarchical solver (LoRaSp) based on H2-matrices was introduced in [22]. Here, we have developed a parallel version of the algorithm in LoRaSp to solve large sparse matrices on distributed memory machines. On a single processor, the factorization time of our parallel solver scales almost linearly with the problem size for three-dimensional problems, as opposed to the quadratic scalability of many existing sparse direct solvers. Moreover, our solver leads to almost constant numbers of iterations, when used as a preconditioner for Poisson problems. On more than one processor, our algorithm has significant speedups compared to sequential runs. With this parallel algorithm, we are able to solve large problems much faster than many existing packages as demonstrated by the numerical experiments.
This paper presents a 3D finite element model for simulating shear slip on fractures in rock in response to coupled thermo-poro-mechanical processes. The modeling is part of a broader effort to investigate the role of pore pressure and cooling by cold water injection on shear slip and permeability increase in granitic rock using laboratory shearing experiments under triaxial conditions. In particular, 3D thermo-poro-mechanical finite element modeling and analysis of injection experiment in fractured rock has been carried out to analyze the role of pore pressure, temperature, fracture deformation and their interactions. 4-noded tetrahedral elements are employed for intact rock deformation and transport processes within the matrix. To represent the mechanical response of a fracture surface, zero thickness contact interface element is developed based on recently developed element partitioning algorithm and procedures for applying hydraulic pressure on the fracture surfaces. A Mohr-Coulomb type criterion is adapted to capture the slip on the fracture and to quantify its reversible and irreversible deformation. The numerical model has been calibrated using results from well controlled, advanced laboratory experiments. Excellent agreement between modeling and experimental observations is achieved. Simulation results illustrate that pore pressure increase and rock matrix/fracture surface cooling cause the fracture system to deform and slip. Fracture slip is promoted due to its normal stress reduction associated with cooling effect of cold fluid injection. The numerical model provides a physics-based understanding of the role of coupled processes on shear stimulation phenomenon and the resulting permeability enhancement.
Room-temperature (RT) multiferroics, possessing ferroelectricity and ferromagnetism simultaneously at RT, hold great promise in miniaturized devices including sensors, actuators, transducers, and multi-state memories. In this work, we report a novel 2D layered RT multiferroic system with self-assembled layered supercell structure consisting of two mismatch-layered sub-lattices of [Bi3O3+δ] and [MO2]1.84 (M=Al/Mn, simply named as BAMO), i.e., alternative layered stacking of two mutually incommensurate sublattices made of a three-layer-thick Bi-O slab and a one-layer-thick Al/Mn-O octahedra slab along the out-of-plane direction. Strong room-temperature multiferroic responses, e.g., ferromagnetic and ferroelectric properties, have been demonstrated and attributed to the highly anisotropic 2D nature of the non-ferromagnetic and ferromagnetic sublattices which are highly mismatched. The work demonstrates an alternative design approach for new 2D layered oxide materials that hold promises as single-phase multiferroics, 2D oxides with tunable bandgaps, and beyond.
The ability to measure the velocity of neutral atoms and molecules with a precision of several meter/sec provides an opportunity to measure subtle perturbations on electronic states with high resolution. Using Velocity Mapped Ion Imaging we are able to measure induced perturbations of electronic states such as broadening and magnetic and electric field splittings . We demonstrate this ability utilizing the 5s[3/2]2 → 5p[5/2]3 cycling transition at 811.5 nm in metastable Kr atoms to investigate the saturation broadening caused by Rabi cycling on a resonant transition with MHz resolution. In addition we investigate the lifetime broadening associated with ionization from the cycling states and the Zeeman splitting of the states. We discuss the inherent limits to resolution obtained with this technique.
This work was conducted as part of a Harry S. Truman Fellowship Laboratory Directed Research and Development project. The goal was to use machine learning methods to provide uncertainty quantification and model improvements for Reynolds Averaged Navier Stokes (RANS) turbulence models. For applications of interest in energy, safety, and security, it is critical to be able to model turbulence accurately. Current RANS models are unreliable for many flows of engineering relevance. Machine learning provides an avenue for developing improved models based on the data generated by high fidelity simulations. In this project, machine learning methods were used to predict when current RANS models would fail. They were also used to develop improved RANS closure models. A key aim was developing a tight feedback loop between scientific domain knowledge and data driven methods. To this end, a methodology for incorporating known invariance constraints into the machine learning models was proposed and evaluated. This work demonstrated that incorporating known constraints into the data driven models provided improved performance and reduced computational cost. This research represents one of the first applications of deep learning to turbulence modeling.
The Nuclear Regulatory Commission's (NRC) current fire protection regulatory framework was initiated in response to a cable fire that occurred at the Browns Ferry Nuclear Power Station in 1975. Following the issuance of several guidance documents, in 1981 the Commission codified deterministic requirements to provide reasonable assurance that fire would not jeopardize reactor safety (10 CFR 50.48 "Fire Protection" and Appendix R to 10 CFR 50). Since then, the results of plant operating experience, NRC inspection activities and cable fire testing programs have served to clarify the application of these requirements. In 2004, the NRC amended 10 CFR Part 50.48 to add a new subsection, 10 CFR 50.48(c), that endorses, with exceptions, the National Fire Protection Association's 805, "Performance-Based Standard for Fire Protection for Light Water Reactor Electric Generating Plants — 2001 Edition," as a voluntary alternative for demonstrating compliance with Appendix R. To date, approximately half of all operating plants have transitioned to a risk-informed approach under 10 CFR 50.48(c). Regardless of the selected approach, each operating nuclear power plant should establish a comprehensive fire protection program that includes features needed to minimize the likelihood and consequence of firesl. To achieve this objective, fire protection programs integrate the NRC's long-held safety concept of defense-in-depth (DID) by providing multiple barriers against potentially unacceptable consequences of fire. To minimize the frequency and size of fires, the first lines of defense include controls for fire prevention, such as controlling combustibles and ignition sources and fire mitigation features, such as fire detection and suppression systems. In the unlikely event that a fire should start and continue to grow in spite of these features, appropriate fire protection features, such as fire-rated barriers are provided as necessary to ensure the accomplishment of essential shutdown functions. This handbook was specifically developed for NRC inspectors that may be assigned to perform elements of Inspection Procedure (IP) 71111.05T, "Fire Protection (Triennial)," including, (a) "Protection of Safe Shutdown Capabilities," (e) "Alternative Shutdown Capability," and (f) "Circuit Analyses." Thus, the document concentrates solely on the final element of defense-in-depth— ensuring reactor safety will not be compromised in the event of a serious fire. In addition to describing how the NRC's regulatory framework has evolved since the Browns Ferry Fire, the handbook illustrates the content and scope of various analyses typically referenced in a plant's fire protection licensing basis and includes techniques and insights for assessing the plant's conformance to those criteria.
Recent Magnetized Liner Inertial Fusion experiments at the Sandia National Laboratories Z pulsed power facility have featured a PDV (Photonic Doppler Velocimetry) diagnostic in the final power feed section for measuring load current. In this paper, we report on an anomalous pressure that is detected on this PDV diagnostic very early in time during the current ramp. Early time load currents that are greater than both B-dot upstream current measurements and existing Z machine circuit models by at least 1 MA would be necessary to describe the measured early time velocity of the PDV flyer. This leads us to infer that the pressure producing the early time PDV flyer motion cannot be attributed to the magnetic pressure of the load current but rather to an anomalous pressure. Using the MHD code ALEGRA, we are able to compute a time-dependent anomalous pressure function, which when added to the magnetic pressure of the load current, yields simulated flyer velocities that are in excellent agreement with the PDV measurement. As a result, we also provide plausible explanations for what could be the origin of the anomalous pressure.
SNL’s IDC Reengineering Phase 2 team developed 31 Use Cases (UCs) during the E3 Elaboration Iteration. This document describes the changes made to these UCs after their initial delivery to the IDC in October 2016.
Wrought Al-Ge-Si alloys were designed and produced to ensure dislocation bypass strengthening (“hard pin” precipitates) without significant precipitate cutting/shearing (“soft pin” precipitates). These unusual alloys were processed from the melt, solution heat treated and aged. Aging curves at temperatures of 120, 160, 200 and 240 °C were established and the corresponding precipitate spacings, sizes, and morphologies were measured using TEM. The role of non-shearable precipitates in determining the magnitude of Bauschinger was revealed using large-strain compression/tension tests. The effect of precipitates on the Bauschinger response was stronger than that of grain boundaries, even for these dilute alloys. The Bauschinger effect increases dramatically from the under-aged to the peak aged condition and remains constant or decreases slowly through over-aging. This is consistent with reported behavior for Al-Cu alloys (maximum effect at peak aging) and for other Al alloys (increasing through over-aging) such as Al-Cu-Li, Al 6111, Al 2524, and Al 6013. The Al-Ge-Si alloy response was simulated with three microstructural models, including a novel SD (SuperDislocation) model, to reveal the origins of the Bauschinger effect in dilute precipitation-hardened / bypass alloys. The dominant mechanism is related to the elastic interaction of polarized dislocation arrays (generalized pile-up or bow-out model) at precipitate obstacles. Such effects are ignored in continuum and crystal plasticity models.
This study describes a cyber security research & development (R&D) gap analysis and research plan to address cyber security for industrial control system (ICS) supporting critical energy systems (CES). The Sandia National Laboratories (SNL) team addressed a long-term perspective for the R&D planning and gap analysis. Investment will posture CES for sustained and resilient energy operations well into the future.
Elastomeric materials are used as shock isolation materials in a variety of environments to dampen vibrations and/or absorb energy from external impact to minimize energy transfer between two objects or bodies. Some applications require the shock isolation materials to behave as a low-pass mechanical filter to mitigate the shock/impact at high frequencies but transmit the energy at low frequencies with minimal attenuation. To fulfill this requirement, a shock isolation material needs to be carefully evaluated and selected with proper experimental design, procedures, and analyses. In this study, a Kolsky bar was modified with precompression (up to 15.5 kN) and confinement capabilities to evaluate low-pass shock isolation performance in terms of acceleration attenuation through a variety of elastomers. Also investigated were the effects of preload and specimen geometry on the low-pass shock isolation response.
Ihlefeld, Jon F.; Kang, Xiaoyu; Shetty, Smitha; Garten, Lauren; Trolier-Mckinstry, Susan; Maria, Jon P.
Dielectric and piezoelectric properties for Zn1-xMgxO (ZMO) thin films are reported as a function of MgO composition up to and including the phase separation region. Zn1-xMgxO (0.25 ≤ x ≤ 0.5) thin films with c-axis textures were deposited by pulsed laser deposition on platinized sapphire substrates. The films were phase pure wurtzite for MgO concentrations up to 40%; above that limit, a second phase with rocksalt structure evolves with strong {100} texture. With increasing MgO concentration, the out-of-plane (d33,f) and in-plane (e31,f) piezoelectric coefficients increase by 360% and 290%, respectively. The increase in piezoelectric coefficients is accompanied by a 35% increase in relative permittivity. Loss tangent values fall monotonically with increasing MgO concentration, reaching a minimum of 0.001 for x ≥ 0.30, at which point the band gap is reported to be 4 eV. The enhanced piezoelectric response, the large band gap, and the low dielectric loss make Zn1-xMgxO an interesting candidate for thin film piezoelectric devices, and demonstrate that compositional phase transformations provide opportunities for property engineering.
The efficiency of photoconductive (PC) devices, including terahertz detectors, is constrained by the bulk optical constants of PC materials. Here, we show that optical absorption in a PC layer can be modified substantially within a hybrid cavity containing nanoantennas and a Distributed Bragg Reflector. We find that a hybrid cavity, consisting of a GaAs PC layer of just 50 nm, can be used to absorb >75% of incident photons by trapping the light within the cavity. We provide an intuitive model, which describes the dependence of the optimum operation wavelength on the cavity thickness. We also find that the nanoantenna size is a critical parameter, small variations of which lead to both wavelength shifting and reduced absorption in the cavity, suggesting that impedance matching is key for achieving efficient absorption in the optically thin hybrid cavities.
Proceedings of COM-HPC 2016: 1st Workshop on Optimization of Communication in HPC Runtime Systems - Held in conjunction with SC 2016: The International Conference for High Performance Computing, Networking, Storage and Analysis
Chan, Cy P.; Bachan, John D.; Kenny, Joseph; Wilke, Jeremiah; Beckner, Vincent E.; Almgren, Ann S.; Bell, John B.
We introduce a topology-aware performance optimization and modeling workflow for AMR simulation that includes two new modeling tools, ProgrAMR and Mota Mapper, which interface with the BoxLib AMR framework and the SSTmacro network simulator. ProgrAMR allows us to generate and model the execution of task dependency graphs from high-level specifications of AMR-based applications, which we demonstrate by analyzing two example AMR-based multigrid solvers with varying degrees of asynchrony. Mota Mapper generates multiobjective, network topology-aware box mappings, which we apply to optimize the data layout for the example multigrid solvers. While the sensitivity of these solvers to layout and execution strategy appears to be modest for balanced scenarios, the impact of better mapping algorithms can be significant when performance is highly constrained by network hop latency. Furthermore, we show that network latency in the multigrid bottom solve is the main contributing factor preventing good scaling on exascale-class machines.
This paper details a model for the response of a finite- or an infinite-length wire interacting with a conducting ground to an electromagnetic pulse excitation. We develop a frequency–domain method based on transmission line theory that we name ATLOG–Analytic Transmission Line Over Ground. This method is developed as an alternative to full-wave methods, as it delivers a fast and reliable solution. It allows for the treatment of finite or infinite lossy, coated wires, and lossy grounds. The cases of wire above ground, as well as resting on the ground and buried beneath the ground are treated. The reported method is general and the time response of the induced current is obtained using an inverse Fourier transform of the current in the frequency domain. The focus is on the characteristics and propagation of the transmission line mode. Comparisons with full-wave simulations strengthen the validity of the proposed method.
Here, a new method for the solution of the non-linear equations forming the core of constitutive model integration is proposed. Specifically, the trust-region method that has been developed in the numerical optimization community is successfully modified for use in implicit integration of elastic-plastic models. Although attention here is restricted to these rate-independent formulations, the proposed approach holds substantial promise for adoption with models incorporating complex physics, multiple inelastic mechanisms, and/or multiphysics. As a first step, the non-quadratic Hosford yield surface is used as a representative case to investigate computationally challenging constitutive models. The theory and implementation are presented, discussed, and compared to other common integration schemes. Multiple boundary value problems are studied and used to verify the proposed algorithm and demonstrate the capabilities of this approach over more common methodologies. Robustness and speed are then investigated and compared to existing algorithms. Through these efforts, it is shown that the utilization of a trust-region approach leads to superior performance versus a traditional closest-point projection Newton-Raphson method and comparable speed and robustness to a line search augmented scheme.
Here, a new method for the solution of the non-linear equations forming the core of constitutive model integration is proposed. Specifically, the trust-region method that has been developed in the numerical optimization community is successfully modified for use in implicit integration of elastic-plastic models. Although attention here is restricted to these rate-independent formulations, the proposed approach holds substantial promise for adoption with models incorporating complex physics, multiple inelastic mechanisms, and/or multiphysics. As a first step, the non-quadratic Hosford yield surface is used as a representative case to investigate computationally challenging constitutive models. The theory and implementation are presented, discussed, and compared to other common integration schemes. Multiple boundary value problems are studied and used to verify the proposed algorithm and demonstrate the capabilities of this approach over more common methodologies. Robustness and speed are then investigated and compared to existing algorithms. Through these efforts, it is shown that the utilization of a trust-region approach leads to superior performance versus a traditional closest-point projection Newton-Raphson method and comparable speed and robustness to a line search augmented scheme.
A new method for the solution of the non-linear equations forming the core of constitutive model integration is proposed. Specifically, the trust-region method that has been developed in the numerical optimization community is successfully modified for use in implicit integration of elastic-plastic models. Although attention here is restricted to these rate-independent formulations, the proposed approach holds substantial promise for adoption with models incorporating complex physics, multiple inelastic mechanisms, and/or multiphysics. As a first step, the non-quadratic Hosford yield surface is used as a representative case to investigate computationally challenging constitutive models. The theory and implementation are presented, discussed, and compared to other common integration schemes. Multiple boundary value problems are studied and used to verify the proposed algorithm and demonstrate the capabilities of this approach over more common methodologies. Robustness and speed are then investigated and compared to existing algorithms. As a result through these efforts, it is shown that the utilization of a trust-region approach leads to superior performance versus a traditional closest-point projection Newton-Raphson method and comparable speed and robustness to a line search augmented scheme.
We demonstrate the ultrafast formation of terahertz (THz) metasurfaces through all-optical creation of spatially modulated carrier density profiles in a deep-subwavelength GaAs film. The switch-on of the transient plasmon mode, governed by the GaAs effective electron mass and electron− phonon interactions, is revealed by structured-optical pump THz probe spectroscopy, on a time scale of 500 fs. By modulating the carrier density using different pump fluences, we observe a wide tuning of the electric dipole resonance of the transient GaAs metasurface from 0.5 THz to 1.7 THz. Furthermore, we numerically demonstrate that the metasurface presented here can be generalized to more complex architectures for realizing functionalities such as perfect absorption, leading to a 30 dB modulation depth. The platform also provides a pathway to achieve ultrafast manipulation of infrared beams in the linear and, potentially, nonlinear regime.
The wealth of information available on seemingly every topic creates a considerable challenge both for information providers trying to rise above the noise and discerning individuals trying to find relevant, trustworthy information. We approach this information problem by investigating how passive versus interactive information interventions can impact the antecedents of behavior change using the context of solar energy adoption, where persistent information gaps are known to reduce market potential. We use two experiments to investigate the impact of both passive and interactive approaches to information delivery on the antecedents (attitudes, subjective norms, and perceived behavioral control in the Theory of Planned Behavior) of intentions and behavior, as well as their effect on intentions and behavior directly. The passive information randomized control trial delivered via Amazon Mechanical Turk tests the effectiveness of delivering the same content in a single message versus multiple shorter messages. The interactive information delivery uses an online (mobile and PC) trivia-style gamification platform. Both experiments use the same content and are carried out over a two-week time period. Lastly, our findings suggest that interactive, gamified information has greater impact than passive information, and that shorter multiple messages of passive information are more effective than a single passive message.
An important question in the reading literature regards the nature of the semantic information readers can extract from the parafovea (i.e., the next word in a sentence). Recent eye-tracking findings have found a semantic parafoveal preview benefit under many circumstances, and findings from event-related brain potentials (ERPs) also suggest that readers can at least detect semantic anomalies parafoveally. We use ERPs to ask whether fine-grained aspects of semantic expectancy can affect the N400 elicited by a word appearing in the parafovea. In an RSVP-with-flankers paradigm, sentences were presented word by word, flanked 2° bilaterally by the previous and upcoming words. Stimuli consisted of high constraint sentences that were identical up to the target word, which could be expected, unexpected but plausible, or anomalous, as well as low constraint sentences that were always completed with the most expected ending. Findings revealed an N400 effect to the target word when it appeared in the parafovea, which was graded with respect to the target’s expectancy and congruency within the sentence context. Moreover, when targets appeared at central fixation, this graded congruency effect was mitigated, suggesting that the semantic information gleaned from parafoveal vision functionally changes the semantic processing of those words when foveated.
Advances in the emerging field of coherent quantum feedback control (CQFC) have led to the development of new capabilities in the areas of quantum control and quantum engineering, with a particular impact on the theory and applications of quantum optical networks. For this study, we consider a CQFC network consisting of two coupled optical parametric oscillators (OPOs) and study the squeezing spectrum of its output field. The performance of this network as a squeezed-light source with desired spectral characteristics is optimized by searching over the space of model parameters with experimentally motivated bounds. We use the QNET package to model the network’s dynamics and the PyGMO package of global optimization algorithms to maximize the degree of squeezing at a selected sideband frequency or the average degree of squeezing over a selected bandwidth. The use of global search methods is critical for identifying the best possible performance of the CQFC network, especially for squeezing at higher-frequency sidebands and higher bandwidths. The results demonstrate that the CQFC network of two coupled OPOs makes it possible to vary the squeezing spectrum, effectively utilize the available pump power, and overall significantly outperform a single OPO. Additionally, the Hessian eigenvalue analysis shows that the squeezing generation performance of the optimally operated CQFC network is robust to small variations of phase parameters.
Hexanitrostilbene (HNS) films were deposited onto polycarbonate substrates using vacuum thermal sublimation. The deposition conditions were varied in order to alter porosity in the films, and the resulting microstructures were quantified by analyzing ion-polished cross-sections using scanning electron microscopy. The effects of these changes in microstructure on detonation velocity and the critical thickness needed to sustain detonation were determined. The polycarbonate substrates also acted as recording plates for detonation experiments, and films near the critical thickness displayed distinct patterns in the dent tracks that indicate instabilities in the detonation front when approaching failure conditions.
We report a series of time-resolved spectroscopic measurements that aim to characterize the reactions that occur during shock initiation of high explosives. The experiments employ time-and wavelength-resolved emission spectroscopy to analyze light emitted from detonating thin explosive films. This paper presents analysis of optical emission spectra from hexanitrostilbene (HNS) and pentaerythritol tetranitrate (PETN) thin film samples. Both vibrationally resolved and broadband emission features are observed in the spectra and area as electronic transitions of intermediate species.
Physical vapor deposition is a technique that can be used to produce explosive films with controlled geometry and microstructure. Films of the high explosive hexanitroazobenzene (HNAB) were deposited by vacuum thermal evaporation. HNAB deposits in an amorphous state that crystallizes over time into a polycrystalline material with high density and a consistent porosity distribution. In previous work, we evaluated detonation critical thickness in HNAB films in an effectively infinite slab geometry with insignificant side losses. In this work, the effect of geometry on detonation failure was investigated by performing experiments on films with different thicknesses, while also changing lateral dimensions such that side losses became significant. The experimental failure thickness was determined to be 75.5 μm and 71.6 μm, for 400 μm and 1600 μm wide HNAB lines, respectively. It follows from this that the minimum width to achieve detonation behavior representing an infinite slab configuration is greater than 400 μm.
Understanding the mechanisms by which shock waves initiate chemical reactions in explosives is key to understanding their unique and defining property: the ability to undergo rapid explosive decomposition in response to mechanical stimulus. Although shock-induced reactions in explosives have been studied experimentally and computationally for decades, the nature of even the first chemical reactions that occur in response to shock remain elusive. To predictively understand how explosives respond to shock, the detailed sequence of events that occurs-mechanical deformation, energy transfer, bond breakage, and first chemical reactions-must be understood at the quantum-mechanical level. This paper reviews recent work in this field and ongoing experimental and theoretical work at Sandia National Laboratories in this important area of explosive science.
A multi-point microwave interferometer (MPMI) concept is presented for non-invasively monitoring the internal transit of a shock, detonation, or reaction front in energetic media. The concept utilizes an electro-optic (EO) crystal to impart a timevarying phase lag onto a laser with a microwave signal. Polarization optics convert this phase lag into an amplitude modulation. A heterodyne interferometer compares the modulated laser beam to a constant reference. This enables the detection of changes in the modulating microwave frequency generated by the motion of the measurement surface. The design is scalable and makes use of the established construction and analysis methods employed in photonic Doppler velocimetry (PDV). The technical challenges associated with the concept are the frequency stability of the lasers, the amount of light return after EO modulation, and the frequency uncertainty of fast Fourier transform (FFT) methods.
Exploding wires are used in many high-energy applications, such as initiating explosives. Previous work analyzing gold wire burst in detonator applications has shown burst current and action metrics to be inconsistent with burst phenomenon across multiple firing-sets. Energy density better captures the correlation between different wire geometries, different electrical inputs, and explosive initiation. This idea has been expanded upon, to analyze the burst properties in power-energy space. Further inconsistencies in the understanding of wire burst and its relation to peak voltage have been found. An argument will be made for redefining the definition of burst. The result is a more broad understanding of rapid metal phase transition and the initiation of explosives in EBW applications.
Dynamic materials experiments on the Z-machine are beginning to reach a regime where traditional analysis techniques break down. Time dependent phenomena such as strength and phase transition kinetics often make the data obtained in these experiments difficult to interpret. We present an inverse analysis methodology to infer the equation of state (EOS) from velocimetry data in these types of experiments, building on recent advances in the propagation of uncertain EOS information through a hydrocode simulation. An example is given for a shock-ramp experiment in which tantalum was shock compressed to 40 GPa followed by a ramp to 80 GPa. The results are found to be consistent with isothermal compression and Hugoniot data in this regime.
A kinetic description for electronic excitation of helium for principal quantum number n 4 has been included into a particle-in-cell (PIC) simulation utilizing direct simulation Monte Carlo (DSMC) for electron-neutral interactions. The excited electronic levels radiate state-dependent photons with wavelengths from the extreme ultraviolet (EUV) to visible regimes. Photon wavelengths are chosen according to a Voigt distribution accounting for the natural, pressure, and Doppler broadened linewidths. This method allows for reconstruction of the emission spectrum for a non-thermalized electron energy distribution function (EEDF) and investigation of high energy photon effects on surfaces, specifically photoemission. A parallel plate discharge with a fixed field (i.e. space charge neglected) is used to investigate the effects of including photoemission for a Townsend discharge. When operating at a voltage near the self-sustaining discharge threshold, it is observed that the electron current into the anode is higher when including photoemission from the cathode than without even when accounting for self-absorption from ground state atoms. The photocurrent has been observed to account for as much as 20% of the total current from the cathode under steady-state conditions.
The dispersion and connectivity of particles with a high degree of polydispersity is relevant to problems involving composite material properties and reaction decomposition prediction and has been the subject of much study in the literature. This work utilizes Monte Carlo models to predict percolation thresholds for a two-dimensional systems containing disks of two different radii. Monte Carlo simulations and spanning probability are used to extend prior models into regions of higher polydispersity than those previously considered. A correlation to predict the percolation threshold for binary disk systems is proposed based on the extended dataset presented in this work and compared to previously published correlations. A set of boundary conditions necessary for a good fit is presented, and a condition for maximizing percolation threshold for binary disk systems is suggested.
Bowman, Daniel; Cutts, James; Komjathy, Attila; Pauken, Michael; Whitaker, Rod
It is therefore of paramount importance to quantify the three dimensional propagation characteristics of infrasound from buried sources. Despite initial success with using an octocopter to quantify ground motion with a seismic hammer (Jones et al., 2015), attempts to capture buried explosion sources using this method have proven very difficult. Even when successful, octocopter-borne sensors suffer from high levels of background noise, have limited flight time due to battery life, and require substantial resources to deploy.
We present a new collection of data on the load-stress relaxation-unload behavior of MinK and FiberFrax Board (FF) insulation materials used as pellets in-line with thermal battery electrochemical stacks. Both materials were subjected to standard thermal preparations, and then tested at room temperature. Intermediate term stress relaxation tests are presented (order 104 minutes of relaxation) showing that FF relaxation is not significantly stress or deformation dependent, but MinK is moderately so. Moreover, stress-strain curves associated with specimen unloading, reloading, and unloading again are presented for both materials. FF and MinK are substantially different here. Acute material variability is observed though test conditions and material preparations are standardized. A modeling approach is presented to empirically estimate the amount of stress relaxation at room temperature, and from this state, represent the unloading stress-strain behavior of both materials. This effort provides a complete framework for representing (in an engineering sense) both materials in thermal battery performance simulations.
Energetic materials (EMs, explosives, pyrotechnics, propellants) provide high-power output of high temperature reaction products. These products can be solid, liquid, or gaseous during reaction or after the products have equilibrated with the surroundings. For example, high explosives typically consist of carbon, hydrogen, nitrogen, and oxygen bonded within a single molecule, and produce almost exclusively gaseous products. Conversely, intermetallics consist of physical mixtures of metals and metalloids, and produce almost exclusively condensed products. Other materials such as pyrotechnics and propellants have intermediate behavior. All energetic materials react in a self-propagating manner that after ignition, does not necessarily require energy input from the surroundings. The range of reaction velocities can range from mm/s for intermetallics, to km/s for high explosives. Energetic material selection depends on numerous requirements specific to the needs of a system. High explosives are used for applications where high pressure gases are necessary for pushing or fracturing materials (e.g., rock, metal) or creating shock waves or air blast. Propellants are used to produce moderate-pressure, high-temperature products without a shock wave. Pyrotechnics are used to produce numerous effects including: high-temperature products, gases, light, smoke, sound, and others. Thermites are used to produce heat, high-temperature products, materials, and other effects that require condensed products. Intermetallics are used to produce high-temperature condensed products and materials, with very little gas production. Numerous categories of energetic materials exist with overlapping definitions, effects, and properties.
This paper investigates three-dimensional cut wire pair (CWP) behavior in vertically oriented meta-atoms. We first analyze CWP metamaterial inclusions using full-wave electromagnetic simulations. The scattering behavior of the vertical CWP differs substantially from that of the planar version of the same structure. In particular, we show that the vertical CWP supports a magnetic resonance that is solely excited by the incident magnetic field. This is in stark contrast to the bianisotropic resonant excitation of in-plane CWPs. We further show that this CWP behavior can occur in other vertical metamaterial resonators, such as back-to-back linear dipoles and back-to-back split ring resonators (SRRs), due to the strong coupling between the closely spaced metallic elements in the back-to-back configuration. In the case of SRRs, the vertical CWP mode (unexplored in previous literature) can be excited with a magnetic field that is parallel to both SRR loops, and exists in addition to the familiar fundamental resonances of the individual SRRs. In order to fully describe the scattering behavior from such dense arrays of three-dimensional structures, coupling effects between the close-packed inclusions must be included. Here, the new flexibility afforded by using vertical resonators allows us to controllably create purely electric inclusions, purely magnetic inclusions, as well as bianisotropic inclusions, and vastly increases the degrees of freedom for the design of metafilms.
Uniaxial strain, plate-on-plate impact experiments were performed on cold-rolled Ni/Al multilayer composites and the resulting Hugoniot was determined through time-resolved measurements combined with impedance matching. The experimental Hugoniot agreed with that previously predicted by two dimensional (2D) meso-scale calculations [Specht et al., J. Appl. Phys. 111, 073527 (2012)]. Additional 2D meso-scale simulations were performed using the same computational method as the prior study to reproduce the experimentally measured free surface velocities and stress profiles. These simulations accurately replicated the experimental profiles, providing additional validation for the previous computational work.
In this work, under-expanded cryogenic hydrogen jets were investigated experimentally for their ignition and flame characteristics. The test facility described herein, was designed and constructed to release hydrogen at a constant temperature and pressure, to study the dispersion and thermo-physical properties of cryogenic hydrogen releases and flames. In this study, a non-intrusive laser spark focused on the jet axis was used to measure the maximum ignition distance. The radiative power emitted by the corresponding jet flames was also measured for a range of release scenarios from 37 K to 295 K, 2–6 barabsthrough nozzles with diameters from 0.75 to 1.25 mm. The maximum ignition distance scales linearly with the effective jet diameter (which scales as the square root of the stagnant fluid density). A 1-dimensional (stream-wise) cryogenic hydrogen release model developed previously at Sandia National Laboratories (although this model is not yet validated for cryogenic hydrogen) was exercised to predict that the mean mole fraction at the maximum ignition distance is approximately 0.14, and is not dependent on the release conditions. The flame length and width were extracted from visible and infra-red flame images for several test cases. The flame length and width both scale as the square root of jet exit Reynolds number, as reported in the literature for flames from atmospheric temperature hydrogen. As shown in previous studies for ignited atmospheric temperature hydrogen, the radiative power from the jet flames of cold hydrogen scales as a logarithmic function of the global flame residence time. The radiative heat flux from jet flames of cold hydrogen is higher than the jet flames of atmospheric temperature hydrogen, for a given mass flow rate, due to the lower choked flow velocity of low-temperature hydrogen. This study provides critical information with regard to the development of models to inform the safety codes and standards of hydrogen infrastructure.
We review liquid hydrogen (LH2) as a maritime vessel fuel, from descriptions of its fundamental properties to its practical application and safety aspects, in the context of the San Francisco Bay Renewable Energy Electric Vessel with Zero Emissions (SF-BREEZE) high-speed fuel-cell ferry. Since marine regulations have been formulated to cover liquid natural gas (LNG) as a primary propulsion fuel, we frame our examination of LH2as a comparison to LNG, for both maritime use in general, and the SF-BREEZE in particular. Due to weaker attractions between molecules, LH2is colder than LNG, and evaporates more easily. We describe the consequences of these physical differences for the size and duration of spills of the two cryogenic fuels. The classical flammability ranges are reviewed, with a focus on how fuel buoyancy modifies these combustion limits. We examine the conditions for direct fuel explosion (detonation) and contrast them with initiation of normal (laminar) combustion. Direct fuel detonation is not a credible accident scenario for the SF-BREEZE. For both fuels, we review experiments and theory elucidating the deflagration to detonation transition (DDT). LH2fires have a shorter duration than energy-equivalent LNG fires, and produce significantly less thermal radiation. The thermal (infrared) radiation from hydrogen fires is also strongly absorbed by humidity in the air. Hydrogen permeability is not a leak issue for practical hydrogen plumbing. We describe the chemistry of hydrogen and methane at iron surfaces, clarifying their impact on steel-based hydrogen storage and transport materials. These physical, chemical and combustion properties are pulled together in a comparison of how a LH2or LNG pool fire on the Top Deck of the SF-BREEZE might influence the structural integrity of the aluminum deck. Neither pool fire scenario leads to net heating of the aluminum decking. Overall, LH2and LNG are very similar in their physical and combustion properties, thereby posing similar safety risks. For ships utilizing LH2or LNG, precautions are needed to avoid fuel leaks, minimize ignition sources, minimize confined spaces, provide ample ventilation for required confined spaces, and to monitor the enclosed spaces to ensure any fuel accumulation is detected far below the fuel/air mix threshold for any type of combustion.
Dissolved CO2 in the subsurface resulting from geological CO2 storage may react with minerals in fractured rocks, confined aquifers, or faults, resulting in mineral precipitation and dissolution. The overall rate of reaction can be affected by coupled processes including hydrodynamics, transport, and reactions at the (sub) pore-scale. In this work pore-scale modeling of coupled fluid flow, reactive transport, and heterogeneous reactions at the mineral surface is applied to account for permeability alterations caused by precipitation-induced pore-blocking. This paper is motivated by observations of CO2 seeps from a natural CO2 sequestration analog, Crystal Geyser, Utah. Observations along the surface exposure of the Little Grand Wash fault indicate the lateral migration of CO2 seep sites (i.e., alteration zones) of 10–50 m width with spacing on the order of ~100 m over time. Sandstone permeability in alteration zones is reduced by 3–4 orders of magnitude by carbonate cementation compared to unaltered zones. One granular porous medium and one fracture network systems are used to conceptually represent permeable porous media and locations of conduits controlled by fault-segment intersections and/or topography, respectively. Simulation cases accounted for a range of reaction regimes characterized by the Damköhler (Da) and Peclet (Pe) numbers. Pore-scale simulation results demonstrate that combinations of transport (Pe), geochemical conditions (Da), solution chemistry, and pore and fracture configurations contributed to match key patterns observed in the field of how calcite precipitation alters flow paths by pore plugging. This comparison of simulation results with field observations reveals mechanistic explanations of the lateral migration and enhances our understanding of subsurface processes associated with the CO2 injection. In addition, permeability and porosity relations are constructed from pore-scale simulations which account for a range of reaction regimes characterized by the Da and Pe numbers. Finally, the functional relationships obtained from pore-scale simulations can be used in a continuum scale model that may account for large-scale phenomena mimicking lateral migration of surface CO2 seeps.
Park, Samuel; Baranov, Dmitry; Ryu, Jisu; Cho, Byungmoon; Halder, Avik; Seifert, Sonke; Vajda, Stefan; Jonas, David M.
Femtosecond two-dimensional Fourier transform spectroscopy is used to determine the static bandgap inhomogeneity of a colloidal quantum dot ensemble. The excited states of quantum dots absorb light, so their absorptive two-dimensional (2D) spectra will typically have positive and negative peaks. It is shown that the absorption bandgap inhomogeneity is robustly determined by the slope of the nodal line separating positive and negative peaks in the 2D spectrum around the bandgap transition; this nodal line slope is independent of excited state parameters not known from the absorption and emission spectra. The absorption bandgap inhomogeneity is compared to a size and shape distribution determined by electron microscopy. The electron microscopy images are analyzed using new 2D histograms that correlate major and minor image projections to reveal elongated nanocrystals, a conclusion supported by grazing incidence small-angle X-ray scattering and high-resolution transmission electron microscopy. Finally, the absorption bandgap inhomogeneity quantitatively agrees with the bandgap variations calculated from the size and shape distribution, placing upper bounds on any surface contributions.
Low frequency sound waves transmit information on both natural and anthropogenic phenomena, transfer energy between the lower and upper atmosphere, and often propagate for thousands of kilometers. These sound waves are typically in the "infrasound" (below human hearing) range. Although the vast majority of geoacoustic sensor networks have existed on the Earth's surface, microphones drifting in the atmosphere may have much greater sensitivity as well as sample regions inaccessible from the ground.
The resonance modes in Mach 0.94 turbulent flow over a cavity having a length-to-depth ratio of five were explored using time-resolved particle image velocimetry and time-resolved pressure sensitive paint. Mode-switching occurred in the velocity field simultaneous with the pressure field. The first cavity mode corresponded to large-scale motions in shear layer and in the vicinity of the recirculation region, whereas the second and third modes contained organized structures associated with shear layer vortices. Modal surface pressures exhibited streamwise periodicity generated by the interference of downstream-traveling disturbances in shear layer with upstream-traveling acoustical waves. Because of this interference, the modal velocity fields also exhibited local maxima at locations containing pressure minima and vice-versa. Modal convective (phase) velocities, based on cross-correlations of bandpass-filtered velocity fields, decreased with decreasing mode number as the modal activity resided in lower portions of the cavity. These phase velocities also exhibited streamwise periodicity caused by wave interference. The measurements demonstrate that despite the complexities inherent in compressible cavity flows, many of the most prevalent resonance dynamics can be described with simple acoustical analogies.
The k-ε turbulence model has been described as perhaps “the most widely used complete turbulence model.” This family of heuristic Reynolds Averaged Navier-Stokes (RANS) turbulence closures is supported by a suite of model parameters that have been estimated by demanding the satisfaction of well-established canonical flows such as homogeneous shear flow, log-law behavior, etc. While this procedure does yield a set of so-called nominal parameters, it is abundantly clear that they do not provide a universally satisfactory turbulence model that is capable of simulating complex flows. Recent work on the Bayesian calibration of the k-ε model using jet-in-crossflow wind tunnel data has yielded parameter estimates that are far more predictive than nominal parameter values. Here we develop a self-similar asymptotic solution for axisymmetric jet-in-crossflow interactions and derive analytical estimates of the parameters that were inferred using Bayesian calibration. The self-similar method utilizes a near field approach to estimate the turbulence model parameters while retaining the classical far-field scaling to model flow field quantities. Our parameter values are seen to be far more predictive than the nominal values, as checked using RANS simulations and experimental measurements. They are also closer to the Bayesian estimates than the nominal parameters. A traditional simplified jet trajectory model is explicitly related to the turbulence model parameters and is shown to yield good agreement with measurement when utilizing the analytical derived turbulence model coefficients. The close agreement between the turbulence model coefficients obtained via Bayesian calibration and the analytically estimated coefficients derived in this paper is consistent with the contention that the Bayesian calibration approach is firmly rooted in the underlying physical description.
While conducting siderite (FeCO3) solubility experiments in NaCl-Na2CO3 brines, evidence for a second phase was detected. Experiments, in which synthesized siderite was reacted with high ionic strength (0.18 - 7.5 m) solutions at room temperature and high pH (>10), were conducted in a glovebox. As the aging time of siderite-bearing experiments increased, the pH of the solution decreased, signaling formation of a hydroxyl-bearing phase. Decreasing pH values are interpreted to indicate that a hydroxyl-bearing phase, such as chukanovite, is the reaction controlling solid in the solid assemblage. Chukanovite was tentatively identified by XRD analysis. We set out, therefore, to determine the thermodynamic stability of chukanovite under the experimental conditions. Aqueous thermodynamic model parameters were determined with experimentally analyzed Fe(II) solubility data, and subsequently yielded a proposed formation free energy of chukanovite (-1149.8 kJ/mol).
Borate is present in natural groundwaters and borate is also released into groundwaters when borosilicate glass, waste form for high level nuclear waste, is corroded. Borate can form an aqueous complex, AmHB4O7 2+, with actinides in +III oxidation state. In this work, we present our evaluation of the equilibrium constant for formation of AmHB4O7 2+ and the associated Pitzer interaction parameters at 25°C. Using Nd(III) as an analog to Am(III), solubility data of Nd(OH)3(s) in NaCl solutions in the presence of borate ion from the literature, is used to determine Am(III) interactions with borate. The log10K for the formation reaction is 37.34. This evaluation is in accordance with the Waste Isolation Pilot Plant (WIPP) thermodynamic model in which the borate species include B(OH)3(aq), B(OH)4 -, B3O3(OH)4 -, B4O5(OH)4 2-, and NaB(OH)4(aq). The WIPP thermodynamic database uses the Pitzer model to calculate activity coefficients of aqueous species. In addition, the equilibrium constant for dissolution of AmB9O13(OH)4(cr) at 25°C is evaluated from the solubility data on NdB9O13(OH)4(cr) in NaCl solutions, again using Nd(III) as an analog to Am(III). The log10K for the dissolution reaction is -79.30. In the evaluation for log10K for the dissolution reaction, AmHB4O7 2+ is also considered. The equilibrium constant and Pitzer parameters evaluated by this study will be important to describe the chemical behavior of Am(III) in the presence of borate in geological repositories.
Spurious energy in received radar data is unanticipated and undesired signal relevant to radar target signatures, usually a consequence of nonideal component and circuit behavior, perhaps due to I/Q imbalance, nonlinear component behavior, additive interference (e.g. cross-talk, etc.), or other sources. The manifestation of the spurious energy in a range-Doppler map or image can often be influenced by appropriate pulse-to-pulse phase modulation. Comparing multiple images having been processed with the same data but different signal paths and modulations allows identifying undesired spurs and then cropping or apodizing them.
It is often advantageous to modify, or warp, radar waveforms, particularly with respect to group-delay and spectral dilation. These warping adjustments may facilitate real-time motion compensation of waveforms in radar systems, especially when those waveforms are generated by a digital parametric waveform generator. Relevant waveforms to this paper include Frequency Modulated (FM) waveforms, such as the Linear-FM (LFM) chirp, Non-Linear FM (NLFM) chirp, and other general FM waveforms. We present techniques for making fine adjustments to dynamically warp general FM waveforms.
We designed and produced optical coatings for broad bandwidth high reflection (BBHR) of femtosecond (fs) pulses for high energy petawatt (PW) lasers. These BBHR coatings consist of TiO2/SiO2 and/or HfO2/SiO2 layer pairs formed by reactive E-beam evaporation with ion-assisted deposition in Sandia's Large Optics Coating Facility. Specifications for the HR band and center wavelength of the coatings are for 45° angle of incidence (AOI), P polarization (Ppol), with use of the coatings at different AOIs and in humid or dry/vacuum environments providing corresponding different HR center wavelengths and spectral widths. These coatings must provide high laserinduced damage threshold (LIDT) to handle the PW fluences, and also low group delay dispersion (GDD) to reflect fs pulses without distortion of their temporal profiles. We present results of LIDT and GDD measurements on these coatings. The LIDT tests are at 45° or 65° AOI, Ppol in a dry environment with 100 fs laser pulses of 800 nm line center for BBHR coatings whose HR band line centers are near 800 nm. A GDD measurement for one of the BBHR coatings whose design HR center wavelength is near 900 nm shows reasonably low and smoothly varying GDD over the HR band. Our investigations include BBHR coatings designed for 45° AOI, Ppol with HR bands centered at 800 nm in dry or vacuum environments, and featuring three options: all TiO2/SiO2 layer pairs; all HfO2/SiO2 layer pairs; and TiO2/SiO2 inner layer pairs with 5 outer HfO2/SiO2 layer pairs. LIDT tests of these coatings with 100 fs, 800 nm line center pulses in their use environment show that replacing a few outer TiO2 layers of TiO2/SiO2 BBHR coatings with HfO2 leads to ∼ 80% higher LIDT with only minor loss of HR bandwidth.
An enriched finite element method is described for capillary hydrodynamics including dynamic wetting. The method is enriched via the Conformal Decomposition Finite Element Method (CDFEM). Two formulations are described, one with first-order accuracy and one with second-order accuracy in time. Both formulations utilize a semi-implicit form for the surface tension that is shown to effectively circumvent the explicit capillary time step limit. Sharp interface boundary conditions are developed for capturing the dynamic contact angle as the fluid interface moves along the wall. By virtue of the CDFEM, the contact line is free to move without risk of mesh tangling, but is sharply captured. Multiple problems are used to demonstrate the effectiveness of the methods.
Printed circuit heat exchangers (PCHEs) have an important role in supercritical CO2 (sCO2) Brayton cycles because of their small footprint and the high level of recuperation required for this power cycle. Compact heat exchangers like PCHEs are a rapidly evolving technology, with many companies developing various designs. One technical unknown that is common to all compact heat exchangers is the flow distribution inside the headers that affects channel flow uniformity. For compact heat exchangers, the core frontal area is often large compared with the inlet pipe area, increasing the possibility of flow maldistribution. With the large area difference, there is potential for higher flow near the center and lower flow around the edges of the core. Flow maldistribution increases pressure drop and decreases effectiveness. In some header geometries, flow separation inside the header adds to the pressure drop without increasing heat transfer. This is the first known experiment to test for flow maldistribution by direct velocity measurements in the headers. A PCHE visualization prototype was constructed out of transparent acrylic for optical flow measurements with Particle Image Velocimetry (PIV). The channels were machined out of sheets to form many semi-circular cross sections typical of chemically-etched plates used in PCHE fabrication. These plates were stacked and bolted together to resemble the core geometry. Two header geometries were tested, round and square, both with a normally-oriented jet. PIV allows for velocities to be measured in an entire plane instantly without disturbing the flow. Small particles of approximately 10 micrometers in diameter were added to unheated water. The particles were illuminated by two laser flashes that were carefully timed, and two images were acquired with a specialized digital camera. The movement of particle groups was detected by a cross-correlation algorithm with a result of about 50k velocity measurements in a plane. The velocity distribution inside the header volume was mapped using this method over many planes by traversing the PCHE relative to the optical equipment. The level of flow maldistribution was measured by the spatially-changing velocity coming out of the channels. This effect was quantified by the coefficient of variation proposed by Baek et al. The relative levels of flow maldistribution in the different header geometries in this study were assessed. With highly-resolved velocity measurements, improvements to header geometry to reduce flow maldistribution can be developed.
ASME 2017 11th International Conference on Energy Sustainability, ES 2017, collocated with the ASME 2017 Power Conference Joint with ICOPE 2017, the ASME 2017 15th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2017 Nuclear Forum
This paper presents a study of alternative heliostat standby aiming strategies and their impact on avian flux hazards and operational performance of a concentrating solar power plant. A mathematical model was developed that predicts the bird-feather temperature as a function of solar irradiance, thermal emittance, convection, and thermal properties of the feather. The irradiance distribution in the airspace above the Ivanpah Unit 2 heliostat field was simulated using a ray-trace model for two different times of the day, four days of the year, and nine different standby aiming strategies. The impact of the alternative aiming strategies on operational performance was assessed by comparing the heliostat slew times from standby position to the receiver for the different aiming strategies. Increased slew times increased a proxy start-up time that reduced the simulated annual energy production. Results showed that spreading the radial aim points around the receiver to a distance of ∼150 m or greater reduced the hazardous exposure times that the feather temperature exceeded the hazard metric of 160 °C. The hazardous exposure times were reduced by ∼23% and 90% at a radial spread of aim points extending to 150 m and 250 m, respectively, but the simulated annual energy production decreased as a result of increased slew times. Single point-focus aiming strategies were also evaluated, but these strategies increased the exposure hazard relative to other aiming strategies.
The Rim-to-Rim Wearables At The Canyon for Health (R2R WATCH) study examines metrics recordable on commercial off the shelf (COTS) devices that are most relevant and reliable for the earliest possible indication of a health or performance decline. This is accomplished through collaboration between Sandia National Laboratories (SNL) and The University of New Mexico (UNM) where the two organizations team up to collect physiological, cognitive, and biological markers from volunteer hikers who attempt the Rim-to-Rim (R2R) hike at the Grand Canyon. Three forms of data are collected as hikers travel from rim to rim: physiological data through wearable devices, cognitive data through a cognitive task taken every 3 hours, and blood samples obtained before and after completing the hike. Data is collected from both civilian and warfighter hikers. Once the data is obtained, it is analyzed to understand the effectiveness of each COTS device and the validity of the data collected. We also aim to identify which physiological and cognitive phenomena collected by wearable devices are the most relatable to overall health and task performance in extreme environments, and of these ascertain which markers provide the earliest yet reliable indication of health decline. Finally, we analyze the data for significant differences between civilians’ and warfighters’ markers and the relationship to performance. This is a study funded by the Defense Threat Reduction Agency (DTRA, Project CB10359) and the University of New Mexico (The main portion of the R2R WATCH study is funded by DTRA. UNM is currently funding all activities related to bloodwork. DTRA, Project CB10359; SAND2017-1872 C). This paper describes the experimental design and methodology for the first year of the R2R WATCH project.
Dissolved CO2 in the subsurface resulting from geological CO2 storage may react with minerals in fractured rocks, confined aquifers, or faults, resulting in mineral precipitation and dissolution. The overall rate of reaction can be affected by coupled processes including hydrodynamics, transport, and reactions at the (sub) pore-scale. In this work pore-scale modeling of coupled fluid flow, reactive transport, and heterogeneous reactions at the mineral surface is applied to account for permeability alterations caused by precipitation-induced pore-blocking. This work is motivated by observations of CO2 seeps from a natural CO2 sequestration analog, Crystal Geyser, Utah. Observations along the surface exposure of the Little Grand Wash fault indicate the lateral migration of CO2 seep sites (i.e., alteration zones) of 10–50 m width with spacing on the order of ~100 m over time. Sandstone permeability in alteration zones is reduced by 3–4 orders of magnitude by carbonate cementation compared to unaltered zones. One granular porous medium and one fracture network systems are used to conceptually represent permeable porous media and locations of conduits controlled by fault-segment intersections and/or topography, respectively. Simulation cases accounted for a range of reaction regimes characterized by the Damköhler (Da) and Peclet (Pe) numbers. Pore-scale simulation results demonstrate that combinations of transport (Pe), geochemical conditions (Da), solution chemistry, and pore and fracture configurations contributed to match key patterns observed in the field of how calcite precipitation alters flow paths by pore plugging. This comparison of simulation results with field observations reveals mechanistic explanations of the lateral migration and enhances our understanding of subsurface processes associated with the CO2 injection. In addition, permeability and porosity relations are constructed from pore-scale simulations which account for a range of reaction regimes characterized by the Da and Pe numbers. The functional relationships obtained from pore-scale simulations can be used in a continuum scale model that may account for large-scale phenomena mimicking lateral migration of surface CO2 seeps.
Product formation from the low-temperature oxidation of two isotopologues of the proposed biofuel butanone was studied via multiplexed photoionization mass spectrometry (MPIMS) at 500 and 700 K to elucidate product branching ratios for R and QOOH pathways. Products were identified and branching ratios quantified for a number of species, with the aid of ab initio calculations. Chain-inhibiting C-C β-scission of R and select chain-propagating channels are discussed. Whilst methyl vinyl ketone and HOO, (from chain-inhibiting pathways) were found to be major products, chain propagation pathways leading to carbonyl and cyclic ether species following OH-elimination from QOOH were found to be pertinent at both temperatures. At 700 K, R C-C β-scission was significantly enhanced, as evident in the branching ratios, however the formation of QOOH-derived chain-propagation products remained relevant.
High-voltage (20 kV peak), single-pulse, nanosecond, low-temperature plasma discharges were examined in nitrogen-diluted desiccated air (15.9% oxygen) with addition of 1%, 2%, and 3% carbon dioxide or water for a pin-to-pin electrode configuration in an optically accessible spark calorimeter at elevated density (2.9 kg/m3). Discharge behavior was characterized through pressure-rise calorimetry, direct imaging of excited-state atomic oxygen, and high-speed schlieren. Increasing carbon dioxide or water concentration led to an increased likelihood of surface discharges rather than the desired streamer discharge between the pin electrodes. For streamer discharges, carbon dioxide addition decreased the electrical-to-thermal conversion efficiency, while minimal impact was observed for water. Both carbon dioxide and water addition led to faster pressure rise rates. Carbon dioxide addition decreased excited state atomic oxygen signal, while water addition led to negligible changes. Finally, increased streamer branching was observed in the schlieren images when carbon dioxide or water was added to the gas mixture.
A human readiness levels (HRL) scale provides a framework to factor in the human dimension during technology development. This framework promotes careful consideration of the human as a part of the system throughout the product lifecycle. Insufficient attention to the human component of the system can lead to added costs, delayed deliverables, system failure, and even the loss of human life in high-consequence systems. We make the economic and technical justification for using an HRL scale by evaluating a reactive case study within a national laboratory. We create a historical technology readiness level (TRL) adoption roadmap to forecast a potential HRL adoption roadmap. We identify characteristics of organizations that are most likely to adopt the scale and conclude by recommending several project management tactics to ensure successful implementation.
The flame structure corresponding to lean hydrogen–air premixed flames in intense sheared turbulence in the thin reaction zone regime is quantified from flame thickness and conditional scalar dissipation rate statistics, obtained from recent direct numerical simulation data of premixed temporally-evolving turbulent slot jet flames [1]. It is found that, on average, these sheared turbulent flames are thinner than their corresponding planar laminar flames. Extensive analysis is performed to identify the reason for this counter-intuitive thinning effect. The factors controlling the flame thickness are analyzed through two different routes i.e., the kinematic route, and the transport and chemical kinetics route. The kinematic route is examined by comparing the statistics of the normal strain rate due to fluid motion with the statistics of the normal strain rate due to varying flame displacement speed or self-propagation. It is found that while the fluid normal straining is positive and tends to separate iso-scalar surfaces, the dominating normal strain rate due to self-propagation is negative and tends to bring the iso-scalar surfaces closer resulting in overall thinning of the flame. The transport and chemical kinetics route is examined by studying the non-unity Lewis number effect on the premixed flames. The effects from the kinematic route are found to couple with the transport and chemical kinetics route. In addition, the intermittency of the conditional scalar dissipation rate is also examined. It is found to exhibit a unique non-monotonicity of the exponent of the stretched exponential function, conventionally used to describe probability density function tails of such variables. The non-monotonicity is attributed to the detailed chemical structure of hydrogen-air flames in which heat release occurs close to the unburnt reactants at near free-stream temperatures.
In the present work, a direct numerical simulation (DNS) of an experimental high Karlovitz number (Ka) CH4/air piloted premixed flame was analyzed to study the inner structure and the stabilization mechanism of the turbulent flame. A reduced chemical mechanism for premixed CH4/air combustion with NOx based on GRI-Mech3.0 was used, including 268 elementary reactions and 28 transported species. The evolution of the stretch factor, I0, indicates that the burning rate per unit flame surface area is considerably reduced in the near field and exhibits a minimum at x/D = 8. Downstream, the burning rate gradually increases. The stretch factor is different between different species, suggesting the quenching of some reactions but not others. Comparison between the turbulent flame and strained laminar flames indicates that certain aspects of the mean flame structure can be represented surprisingly well by flamelets if changes in boundary conditions are accounted for and the strain rate of the mean flow is employed; however, the thickening of the flame due to turbulence is not captured. The spatial development of displacement speeds is studied at higher Ka than previous DNS. In contrast to almost all previous studies, the mean displacement speed conditioned on the flame front is negative in the near field, and the dominant contribution to the displacement speed is normal diffusion with the reaction contribution being secondary. Further downstream, reaction overtakes normal diffusion, contributing to a positive displacement speed. The negative displacement speed in the near field implies that the flame front situates itself in the pilot region where the inner structure of the turbulent flame is affected significantly, and the flame stabilizes in balance with the inward flow. Notably, in the upstream region of the turbulent flame, the main reaction contributing to the production of OH, H+O2⇔O+OH (R35), is weak. Moreover, oxidation reactions, H2+OH⇔H+H2O (R79) and CO+OH⇔CO2+H (R94), are influenced by H2O and CO2 from the pilot and are completely quenched. Hence, the entire radical pool of OH, H and O is affected. However, the fuel consumption layer remains comparably active and generates heat, mainly via the reaction CH4+OH⇔CH3+H2O (R93).
Controlling the distribution of structural defects in nanostructures is important since such defects can strongly affect critical properties, including thermal and electronic transport. However, characterizing the defect arrangements in individual nanostructures is difficult because of the small length scales involved. Here, we investigate the evolution of microstructural disorder with annealing in electrochemically deposited Bi2Te3 nanowires, which are of interest for thermoelectrics. We combine Convergent Beam Electron Diffraction (CBED) and Scanning Transmission Electron Microscopy (STEM) to provide the necessary spatial and orientational resolution. We find that despite their large initial grain sizes and strong 1120 crystallographic texturing, the as-deposited nanowires still exhibit significant intragranular orientational disorder. Annealing drives both grain growth and a significant reduction in the intragranular disorder. The results are discussed in the context of the existing understanding of the initial microstructure of electrodeposited materials and the understanding of annealing microstructures in both electrochemically deposited and bulk-deformed materials. This analysis highlights the importance of assessing both the grain size and intragranular disorder in understanding the microstructural evolution of individual nanostructures.
Coupled reservoir and geomechanical simulations are significantly important to understand the long-term behavior of geologic carbon storage (GCS) systems. In this study, we performed coupled fluid flow and geomechanical modeling of CO2 storage using available field data to (1) validate our existing numerical model and (2) perform parameter estimation via inverse modeling to identify the impact of key geomechanical (Young's modulus and Biot's coefficient) and hydrogeological (permeability and anisotropy ratio) properties on surface uplift and the pore pressure buildup at In Salah in Algeria. Two sets of surface uplift data featuring low and high uplifts above two injection wells and the maximum change in the pore pressure due to CO2 injection were used to constrain the inverse model. Forward simulation results with representative parameter values from the literature match both low and high surface uplifts reasonably well and predicted the maximum change in the pore pressure. In particular, forward modeling results with estimated Biot's coefficients for reservoir and caprock layers, match the observed uplift well, highlighting the significance of Biot's coefficient in coupled reservoir and geomechanical models. Parameter estimation with 12 parameter sets for both low and high uplift data demonstrates that multiple sets of parameters can match the observed data equally well and the inclusion of the pore pressure data is critically important to constrain the parameter solution during inverse modeling. For a majority of cases, estimation results for both low and high uplift data show the vertical intrinsic permeability and Young's modulus of the reservoir remained close to 13 mD (1.3×10−14 m2) and 10 GPa, respectively, suggesting that these parameters may represent the actual effective properties. Additionally, higher correlations between reservoir permeability and caprock's Biot's coefficient with high surface uplift data were observed consistently under the pore pressure constraint, suggesting the inclusion of the pore pressure constraint is required to estimate the proper values of coupled flow and geomechanical properties associated with different surface uplift data. Overall, this study suggests that given limited data, including Biot's coefficient, in addition to permeability and Young's modulus can enhance parameter estimation of the geomechanical response during GCS.
In this paper, we will summarize a group of architectural principles that inform the development of secure control system architectures, followed by a methodology that allows designers to understand the attack surface of components and subsystems in a way that supports the integration of these surfaces into a single attack surface. We will then show how this methodology can be used to analyze the control system attack surface from a variety of threats, including knowledgeable insiders. We close the paper with an overview of how this approach can be folded into a more rigorous mathematical analysis of the system to define the system's security posture.
A new multi-step, solution-phase method for the spontaneous deposition of tungsten from a room temperature ethereal solution is reported. This immersion process relies on the deposition of a sacrificial zinc coating which is galvanically displaced by the ethermediated reduction of oxophilic WCl6. Subsequent thermal treatment renders a crystalline, metallic tungsten film. The chemical evolution of the surface and formation of a complex intermediate tungsten species is characterized by X-ray diffraction, infrared spectroscopy, and X-ray photoelectron spectroscopy. Efficient metallic tungsten deposition is first characterized on a graphite substrate and then demonstrated on a functional carbon foam electrode. The resulting electrochemical performance of the modified electrode is interrogated with the canonical aqueous ferricyanide system. A tungsten-coated carbon foam electrode showed that both electrode resistance and overall electrochemical cell resistance were reduced by 50%, resulting in a concomitant decrease in redox peak separation from 1.902 V to 0.783 V. This process promises voltage efficiency gains in electrodes for energy storage technologies and demonstrates the viability of a new route to tungsten coating for technologies and industries where high conductivity and chemical stability are paramount.
This paper presents a risk assessment of a Liquefied Natural Gas (LNG)/diesel hybrid locomotive to identify and rank failures that could result in the release of LNG or Gaseous Natural Gas (GNG) to the surrounding environment. The Federal Railroad Administration (FRA) will analyze industry safety assessments of the proposed rail vehicles and the goal of this risk analysis is to identify and prioritize hazard scenarios so the FRA can ensure that they are properly addressed. For operational activities, a Failure Modes and Effects Analysis (FMEA) was performed to identify high risk failure modes. A modified hazard and operability study (HAZOP) methodology was used to analyze hazard scenarios for the maintenance activities for the LNG and Compressed Natural Gas (CNG) dual-fuel locomotives and the LNG tender car. Because refueling operations are highly dependent on human interactions, a human factors assessment was also performed on a sample refueling procedure to identify areas of improvement and identify best practices for analyzing future procedures. The FMEA resulted in the identification of 87 total failure modes for the operational phase, three of which were deemed to have a High risk priority, all involving the cryogenic storage tank. The HAZOP for the LNG tender resulted in the identification of eight credible hazard scenarios and the HAZOP for the locomotive in the maintenance mode identified 27 credible hazard scenarios. The high and medium risk failure modes and hazard scenarios should be prioritized for further analysis.
ANS IHLRWM 2017 - 16th International High-Level Radioactive Waste Management Conference: Creating a Safe and Secure Energy Future for Generations to Come - Driving Toward Long-Term Storage and Disposal
The Deep Borehole Field Test (DBFT) is a planned multi-year project led by the US Department of Energy's Office of Nuclear Energy to drill two boreholes to 5 km total depth into crystalline basement in the continental US. The purpose of the first characterization borehole is to demonstrate the ability to characterize in situ formation fluids through sampling and perform downhole hydraulic testing to demonstrate groundwater from 3 to 5 km depth is old and isolated from the atmosphere. The purpose of the second larger-diameter borehole is to demonstrate safe surface and downhole handling procedures. This paper details many of the drilling, testing, and characterization activities planned in the first smaller-diameter characterization borehole.
Fully-polarimetric X-band (9.6 GHz center frequency) VideoSAR with 0.125-meter ground resolution flew collections before, during, and after the fifth Source Physics Experiment (SPE-5) underground chemical explosion. We generate and exploit synthetic aperture RADAR (SAR) and VideoSAR products to characterize surface effects caused by the underground explosion. To our knowledge, this has never been done. Exploited VideoSAR products are "movies" of coherence maps, phase-difference maps, and magnitude imagery. These movies show two-dimensional, time-varying surface movement. However, objects located on the SPE pad created unwanted, vibrating signatures during the event which made registration and coherent processing more difficult. Nevertheless, there is evidence that dynamic changes are captured by VideoSAR during the event. VideoSAR provides a unique, coherent, time-varying measure of surface expression of an underground chemical explosion.
We present a series of benchmark flames consisting of six partially-premixed piloted dimethyl ether (DME)/air jet flames. These flames provide an opportunity to understand turbulence-flame interactions for oxygenated fuels and to develop predictive models for these interactions using a canonical burner geometry. The development of accurate models for DME/air flames would establish a foundation for studies of more complex oxygenated fuels. The flames are stabilized on a piloted jet burner similar to that of the partially-premixed methane/air jet flames that have been studied extensively within the context of the TNF Workshop. This series of six jet flames spans jet exit Reynolds numbers, ReD, from 29,300 to 73,300 and stoichiometric mixture fractions, ξst, from 0.35 to 0.60. Flame conditions range from very low probability of localized extinction to a high probability of localized extinction and subsequent re-ignition. Measurements in the flames are compared at downstream locations from 5 to 25 diameters above the nozzle exit. Mean and fluctuating velocity components are measured using stereo particle image velocimetry (SPIV). Simultaneous laser-induced fluorescence (LIF) imaging of OH and CH2O provides insights into the distribution of these intermediate species in partially-premixed DME/air flames. OH LIF imaging is also combined with SPIV to investigate the strain rate field across the reaction zone.
For many aerospace applications, there exists significant demand for more accurate tur- bulence models. Data-driven machine learning algorithms have the capability to accurately predict when Reynolds Averaged Navier Stokes (RANS) models will have increased model form uncertainty due to the breakdown of underlying model assumptions. These machine learning models can be used to adaptively trigger relevant model corrections in the regions they are needed. This paper presents a framework for data-driven adaptive physics model- ing that leverages known RANS model corrections and proven machine learning methods. This adaptive physics modeling framework is evaluated for two case studies: fully developed turbulent square duct flow and flow over a wavy wall. It is demonstrated that implement- ing model corrections zonally based on machine learning classification of where underlying RANS model assumptions are violated can achieve the same accuracy as implementing those corrections globally.
ANS IHLRWM 2017 - 16th International High-Level Radioactive Waste Management Conference: Creating a Safe and Secure Energy Future for Generations to Come - Driving Toward Long-Term Storage and Disposal
The Deep Borehole Field Test will include demonstration of the emplacement and retrieval of test waste packages (containing no waste) in a 5 km deep borehole drilled into the crystalline basement. A conceptual design for packaging, surface handling and transfer equipment, and borehole emplacement was developed in anticipation of the demonstration project. Test packages are designed to withstand external pressure greater than 65 MPa, at temperature up to 170°C. Two packaging concepts were developed: 1) flasktype for granular waste, and 2) internal semi-flush type for waste that is pre-canistered in cylindrical containers. Oilfield casing materials and sealing connections would be selected giving a safety factor of 2.0 against yield. Packages would have threaded fittings top and bottom for attachment of impact limiters and latch fittings. Packages would be lowered one-at-a-time into the borehole on electric wireline. This offers important safety advantages over using drill pipe or coiled tubing to lower waste packages, because it avoids the possibility of dropping a heavy assembly in the borehole. An electromechanical latch would release each package, or reconnect for retrieval. Frequency of waste package delivery to a disposal site could be the effective limit on emplacement throughput. Packages would be delivered in a shielded Type B transportation cask and transferred to a shielded, doubleended transfer cask on site. The transfer cask would be upended over the borehole and secured to the wellhead. The transfer cask would become an integral part of the pressure control envelope for well pressure control. Blowout preventers can be incorporated as needed for regulatory compliance. Operational safety has been assessed with respect to normal operations, and off-normal events that could cause package breach in the borehole. Worker exposures can be limited by using standard industry practices for nuclear material handling. The waste packages would effectively be robust pressure vessels that will not breach if dropped during surface handling. The possibility of package breach in the borehole during emplacement can be effectively eliminated using impact limiters on every package.
We propose here a novel device, called the Triassico, to microscopically study the entire surface of millimeter-sized spheres. The sphere dimensions can be as small as 1 mm, and the upper limit defined only by the power and by the mechanical characteristics of the motors used. Three motorized driving rods are arranged so an equilateral triangle is formed by the rod's axes, on such a triangle the sphere sits. Movement is achieved by rotating the rods with precise relative speeds and by exploiting the friction between the sphere and the rods surfaces. The sphere can be held in place by gravity or by an opposing trio of rods. By rotating the rods with specific relative angular velocities, a net torque can be exerted on the sphere which then rotates. No repositioning of the sphere or of the motors is needed to cover the full surface with the investigating tools. An algorithm was developed to position the sphere at any arbitrary polar and azimuthal angle. The algorithm minimizes the number of rotations needed by the rods, in order to efficiently select a particular position on the sphere surface. A prototype Triassico was developed for the National Ignition Facility, of the Lawrence Livermore National Laboratory (Livermore, California, USA), as a sphere manipulation apparatus for ion microbeam analysis at Sandia National Laboratories (Albuquerque, NM, USA) of Xe-doped DT inertial confinement fusion fuel spheres. Other applications span from samples orientation, ball bearing manufacturing, or jewelry.
ANS IHLRWM 2017 - 16th International High-Level Radioactive Waste Management Conference: Creating a Safe and Secure Energy Future for Generations to Come - Driving Toward Long-Term Storage and Disposal
An important feature required in all geological disposal system modeling is proper representation of waste package degradation and waste form dissolution. These processes are often treated as batch operations, meaning they are zero-dimensional. However, waste package canister degradation or waste form dissolution are affected by near-field conditions, and thus they must be coupled to the computational domain through the exchange of information on local conditions. Accurate waste package and waste form degradation behavior is essential because processes occurring at the batch level also affect far field conditions through heat and mass transport by advection or diffusion. Presented here is the development and performance of the Waste Form Process Model, an integrated module for waste package canister degradation and waste form dissolution developed by Sandia National Laboratories within PFLOTRAN. PFLOTRAN is an open source, massively parallel subsurface simulator for multiphase, multicomponent, and multiscale reactive flow and transport processes in porous media. PFLOTRAN is used to model geologic disposal systems for the Spent Fuel and Waste Science and Technology (SFWST) Campaign under the Spent Fuel and Waste Disposition Program of the U.S. Department of Energy (DOE) Office of Nuclear Energy.
A series of tests on NAS1352-06-6P threaded fasteners were coupled with analysis to fit constitutive models, evaluate multiple modeling approaches, and ultimately predict failure. Experiments loading the fasteners in tension at both quasistatic and dynamic loading rates were performed to obtain calibration and validation data for the analysis. The fastener was modeled with two low-fidelity approaches - a "plug" of hex elements retaining the nominal fastener geometry (without threads) and a "spot weld", which incorporates similar geometry but the fastener is sliced near its mid-plane to define a tensile loaddisplacement relationship between the two exposed surfaces - to accommodate the use of these modeling methods in a larger, more detailed finite element analysis. Both modeling approaches were calibrated using quasistatic test data and then extended to the dynamic analyses to compare with the analogous test results. The analysis accurately reproduces most acceleration time-histories observed in the dynamic testing but under predicts failure, indicating the possible presence of strain rate effects that have been neglected in the constitutive models.
Parabolic dish technology, for concentrating solar power (CSP) applications, has been continuously modified and improved since the pioneering work in the 1970s. Best practice dishes now have features such as lightweight structure, balanced design, high-quality, low-cost mirror panels, and can be deployed rapidly with little in-field labour. This review focuses on the evolution of dish design, by examining features such as mode of tracking, structure and mirror design, for a wide selection of CSP dish examples. The review includes a brief summary of power generation options – both on-dish and central plant – as well as a discussion about options for storage and hybridisation.
Time multiplexed spectral images of burning aluminum particles from two experiments using a hyperspectral imaging system (HIS) coupled to a high speed video (HSV) camera were investigated. The first experiment looks at ignited aluminum particles generated by a welding torch that were continuously funneled into the imaging plane of the HISHSV system. The HIS was set to hop between two wavelengths at a rate of 300 frames per second (fps): 485.7 nm, the peak emission of aluminum monoxide, and 502.3nm, the bottom of the same emission peak. The second experiment images ignited AlO from the burn of an aluminized ammonium perchlorate solid propellant hoping between the wavelength of 486.3nm and 480.0nm at 2100 fps.
ANS IHLRWM 2017 - 16th International High-Level Radioactive Waste Management Conference: Creating a Safe and Secure Energy Future for Generations to Come - Driving Toward Long-Term Storage and Disposal
This paper discusses software design choices made during the ongoing development of PFLOTRAN with the intent of improving the longevity and flexibility of the code while maintaining robustness. PFLOTRAN is a massively parallel reactive multiphase flow and transport code employed to simulate subsurface processes in support of radioactive waste management licensing and performance assessment studies. PFLOTRAN's open source licensing, software configuration management, object-oriented design through modern Fortran 2003/2008, approach to coupling scientific process models, and automated testing are discussed in detail.
ANS IHLRWM 2017 - 16th International High-Level Radioactive Waste Management Conference: Creating a Safe and Secure Energy Future for Generations to Come - Driving Toward Long-Term Storage and Disposal
The Waste Isolation Pilot Plant (WIPP) is a U.S. Department of Energy geological repository for the permanent disposal of defense-related transuranic (TRU) waste. Industrial-grade MgO consisting mainly of the mineral periclase is the only engineered barrier certified by U.S. EPA for emplacement in the WIPP in the U.S. An Mg(OH)2-based engineered barrier consisting mainly of the mineral brucite is to be employed in the Asse repository in Germany. The WIPP is located in a bedded salt formation, and the Asse repository is located in a domal salt formation. Colloids would facilitate transport of contaminants including actinides. The regulator for the WIPP, U.S. Environmental Protection Agency (EPA), expressed its interest that possible formation of mineral colloids by MgO and its hydration and carbonation products under the WIPP-relevant conditions be evaluated. In this presentation, we report a systematic experimental study to address U.S. EPA's interest. We evaluated the possible formation of mineral colloids by using two approaches. In the first approach, as the hydration products, Mg(OH)2 (brucite), and(Mg)3Cl(OH)5′4H2O (phase 5), and the carbonation product, (Mg)5(CO3)4(OH)2•4H2O (hydromagnesite), contain magnesium, should mineral fragment colloids exist, magnesium concentrations in solution samples from MgO hydration and carbonation experiments would show a dependence on ultrafiltration, i.e., a decrease in magnesium concentrations as a function of ultrafiltration with decreasing molecular weight (MW) cut-offs. Therefore, we investigated magnesium concentrations from solutions samples in hydration and carbonation experiments as a function of ultrafiltration. We ultrafiltered solutions with a series of MW cut-off filters at 100 κD, 50 κD, 30 κD and 10 κD. Our results demonstrate that the magnesium concentrations remain constant with decreasing MW cut-offs, implying the absence of mineral fragment colloids. In the second approach, because Cs+ is easily absorbed by colloids, we spiked MgO hydration and carbonation experiments under the WIPP-relevant conditions with Cs+. Then, we ultra-filtered solutions with a series of MW cut-off filters at 100 κD, 50 κD, 30 κD and 10 κD. The concentrations of Cs do not change as a function of MW cut-offs, indicating the absence of colloids from MgO hydration and carbonation products. Therefore, both approaches demonstrate that the absence of mineral fragment colloids from MgO hydration and carbonation products.
As unmanned systems (UMS) proliferate for security and defense applications, autonomous control system capabilities that enable them to perform tactical operations are of increasing interest. These operations, in which UMS must match or exceed the performance and speed of people or manned assets, even in the presence of dynamic mission objectives and unpredictable adversary behavior, are well beyond the capability of even the most advanced control systems demonstrated to date. In this paper we deconstruct the tactical autonomy problem, identify the key technical challenges, and place them into context with the autonomy taxonomy produced by the US Department of Defense's Autonomy Community of Interest. We argue that two key capabilities beyond the state of the art are required to enable an initial fieldable capability: rapid abstract perception in appropriate environments, and tactical reasoning. We summarize our work to date in tactical reasoning, and present initial results from a new research program focused on abstract perception in tactical environments. This approach seeks to apply semantic labels to a broad set of objects via three core thrusts. First, we use physics-based multi-sensor fusion to enable generalization from imperfect and limited training data. Second, we pursue methods to optimize sensor perspective to improve object segmentation, mapping and, ultimately, classification. Finally, we assess the potential impact of using sensors that have not traditionally been used by UMS to perceive their environment, for example hyperspectral imagers, on the ability to identify objects. Our technical approach and initial results are presented.
ANS IHLRWM 2017 - 16th International High-Level Radioactive Waste Management Conference: Creating a Safe and Secure Energy Future for Generations to Come - Driving Toward Long-Term Storage and Disposal
Numerical simulation of a repository for heatgenerating nuclear waste in fractured crystalline rock requires a method for simulating coupled heat and fluid flow and reactive radionuclide transport in both porous media (bentonite buffer, surface sediments) and fractured rock (the repository host rock). Discrete fracture networks (DFNs), networks of two-dimensional planes distributed in a three-dimensional domain, are commonly used to simulate isothermal fluid flow and particle transport in fractures, but unless coupled to a continuum, are incapable of simulating heat conduction through the rock matrix, and therefore incapable of capturing the effects of thermally driven fluid fluxes or of coupling chemical processes to thermal processes. We present a method for mapping a stochastically generated DFN to a porous medium domain that allows representation of porous and fractured media in the same domain, captures the behavior of radionuclide transport in fractured rock, and allows simulation of coupled heat and fluid flow including heat conduction through the matrix of the fractured rock. We apply the method within Sandia's Geologic Disposal Safety Assessment (GDSA) framework to conduct a post-closure performance assessment (PA) of a generic repository for commercial spent nuclear fuel in crystalline rock. The three-dimensional, kilometer-scale model domain contains approximately 4.5 million grid cells; grid refinement captures the detail of 3, 360 individual waste packages in 42 disposal drifts. Coupled heat and fluid flow and reactive transport are solved numerically with PFLOTRAN, a massively parallel multiphase flow and reactive transport code. Simulations of multiple fracture realizations were run to 1 million years, and indicate that, because of the channeled nature of fracture flow, thermally-driven fluid fluxes associated with peak repository temperatures may be a primary means of radionuclide transport out of the saturated repository. The channeled nature of fracture flow gives rise to unique challenges in uncertainty and sensitivity quantification, as radionuclide concentrations at any given location outside the repository depend heavily on the distribution of fractures in the domain.
ANS IHLRWM 2017 - 16th International High-Level Radioactive Waste Management Conference: Creating a Safe and Secure Energy Future for Generations to Come - Driving Toward Long-Term Storage and Disposal
Humic complexation has the potential to increase actinide mobility and hamper waste isolation in geologic nuclear waste repositories. This study shows that humic complexation of tetravalent actinides (Th(IV), U(IV), Np(IV), and Pu(IV)) has been overestimated in past performance assessments of the Waste Isolation Pilot Plant (WIPP). Major reductions are needed for PHUMSIM and PHUMCIM, the equilibrium concentration ratios of humic-bound aqueous actinide to non-colloidal aqueous actinide. These coefficients are currently set at a value of 6.3 based on Th(IV) measurements in particle size fractions of seawater. Actual humic partitioning is expected to be significantly lower in WIPP brines primarily because pH is higher (∼9) and concentrations of competing cations (e.g., Mg2+) are higher. In this work, data from recent studies of Th(IV)-humic, U(IV)-humic, and Ca2+-humic complexation are used to simulate competitive humic complexation under WIPP repository conditions and to estimate new An(IV) PHUMSIM and PHUMCIM values. The new lower coefficients reduce the humic-bound An(IV) concentrations by more than 99%, causing a reduction in total mobile An(IV) concentrations by 85% to 86%, assuming no other type of An(IV) colloid (i.e., intrinsic, microbial, and mineral fragment colloids) is present in significant concentrations.
ANS IHLRWM 2017 - 16th International High-Level Radioactive Waste Management Conference: Creating a Safe and Secure Energy Future for Generations to Come - Driving Toward Long-Term Storage and Disposal
Technology Readiness Assessment (TRA) is a formal process to aid in defining the remaining R&D needed to bring a new, complex technology system to full technical maturity. A geologic repository for high-level radioactive waste is a prototypical complex system, comprised of novel technologies and complex environmental conditions, but because it is intended to function passively and is comprised of both engineered and geologic barriers, the standard, engineered-system ("hardware") TRA process must be modified. Longstanding precedence employs a Safety Case (or Licensing Case) as the preferred vehicle for assembling all facets of knowledge to make a determination of repository system safety and deployment readiness. However, certain modifications to the established TRA process allow it to be applied advantageously in conjunction with the Safety Case. In particular, an adaptation of the established Features, Events, and Processes (FEPs) methodology can serve as a basis for a "TRA-like" maturity evaluation for various major components and subsystems of a deep geologic repository. The newly proposed Knowledge Readiness Assessment (KRA) process combines the best of both methodologies, i.e., of FEPs analysis and standard TRA evaluation, for establishing confidence in the post-closure performance of major repository components and subsystems.
Following previous experimental evidence of growth and arrest of Richtmyer-Meshkov instabilities in copper, we have used the CTH shock physics code to study and calibrate the effects of material strength at high strain rates. Highly resolved one and two-dimensional simulations were performed using the Johnson-Cook (JC), Mechanical Threshold Stress (MTS), and Preston-Tonks-Wallace (PTW) strength models. The one-dimensional simulations utilized a prescribed homogeneous deformation strain path covering strain rates observed in previous hydrodynamic instability experiments. Spall was modeled using a nominal threshold pressure model (PFRAC) and we use the Mie-Gruneisen equation of state to estimate the volumetric response of the experiments. Our results show good qualitative and quantitative agreement between numerical estimates and prior experiments in the strain rate regimes of interest.
ANS IHLRWM 2017 - 16th International High-Level Radioactive Waste Management Conference: Creating a Safe and Secure Energy Future for Generations to Come - Driving Toward Long-Term Storage and Disposal
Understanding subsurface fracture network properties at the field scale is important for a number of environmental and economic problems, including siting of spent nuclear fuel repositories, geothermal exploration, and many others. This typically encompasses large volumes of fractured rocks with the properties inferred from the observations at rock outcrops and, if available, from the measurements in exploratory boreholes, quarries, and tunnels. These data are inherently spatially limited and a stochastic model is required to extrapolate the fracture properties over the large volumes of rocks. This study (1) describes three different methods of generating fracture networks developed for use in the fractured continuum model (FCM) and (2) provides a few examples of how these methods impact the predictions of simulated groundwater transport. A detailed analysis of the transport simulations using FCM is provided in the separate paper by the same authors (to be presented at IHLRWM 2017 conference). FCM is based on the effective continuum approaches modified to represent fractures. The permeability of discrete fractures is mapped onto a regular three-dimensional grid. The x-, y-, and z effective permeability values of a grid block are calculated from the tensor. The tensor parameters are fracture aperture, dip, strike, and number of fractures in the grid block (spacing). All three methods use the fracture properties listed above to generate corresponding permeability fields. However, the assumptions and conceptual representation of fracture network from which these properties are derived are very different. The Sequential Gaussian Simulation (SGSim) method does not require an assumption regarding the fracture shape. Fracture aperture, spacing, and orientation are defined based on the field observations. Spatially correlated features (continuation of fracture in the direction of the orientation) are created using spatially correlated random numbers generated with SGSIM code. With this method an exact number of fractures cannot be generated. The Ellipsim method assumes that the fractures are two-dimensional elliptical shapes that can be described with radius and aspect ratio. The knowledge of the fracture (ellipse) radius probability distribution is required. The fracture aperture is calculated from the ellipse radius. For this option an exact number of fractures can be generated. The fracture networks generated with SGSim and Ellipsim are not necessarily connected. The connectivity is achieved indirectly via matrix permeability that can be viewed as the permeability of much smaller fractions. The discrete fracture network (DFN) generator assumes elliptical fracture shapes and requires the same parameters as Ellipsim. The principal difference is in connectivity. The DFN method creates the fracture network connectivity via an iterative process in which not connected clusters of fractures are removed. The permeability fields were generated with FCM using three different methods and the same fracture data set loosely based on the data from an existing site in granite rocks. A few examples of transport simulations are provided to demonstrate the major findings of the comparison.
Three-dimensional large eddy simulations (LES) are used to analyze a springtime Arctic mixed-phase stratocumulus observed on 26 April 2008 during the Indirect and Semi-Direct Aerosol Campaign. Two subgrid-scale turbulence parameterizations are compared. The first scheme is a 1.5-order turbulent kinetic energy (1.5-TKE) parameterization that has been previously applied to boundary layer cloud simulations. The second scheme, Cloud Layers Unified By Binormals (CLUBB), provides higher-order turbulent closure with scale awareness. The simulations, in comparisons with observations, show that both schemes produce the liquid profiles within measurement variability but underpredict ice water mass and overpredict ice number concentration. The simulation using CLUBB underpredicted liquid water path more than the simulation using the 1.5-TKE scheme, so the turbulent length scale and horizontal grid box size were increased to increase liquid water path and reduce dissipative energy. The LES simulations show this stratocumulus cloud to maintain a closed cellular structure, similar to observations. The updraft and downdraft cores self-organize into a larger meso-γ-scale convective pattern with the 1.5-TKE scheme, but the cores remain more isotropic with the CLUBB scheme. Additionally, the cores are often composed of liquid and ice instead of exclusively containing one or the other. These results provide insight into traditionally unresolved and unmeasurable aspects of an Arctic mixed-phase cloud. From analysis, this cloud’s updraft and downdraft cores appear smaller than other closed-cell stratocumulus such as midlatitude stratocumulus and Arctic autumnal mixed-phase stratocumulus due to the weaker downdrafts and lower precipitation rates. Plain Language Summary Low-lying clouds in the Arctic are ubiquitous and important to understand for the near-surface energy balance. These clouds are difficult to measure because of the challenging environment in which they reside. High-resolution models are tools that help fill in knowledge gaps about these clouds. In this work, we compare two different ways to represent fine motion within the cloud and see how the macrophysical properties of the cloud are affected. We found that one representation creates a more energetic cloud, and this type of cloud would exist longer than the other. We also are led to believe in these simulations that these clouds have different internal motions when compared to similar-looking clouds formed at lower latitudes or formed in a different season in the Arctic.
In this paper, we address the needed components to create usable engineering and operational user interfaces (UIs) for airborne Synthetic Aperture Radar (SAR) systems. As airborne SAR technology gains wider acceptance in the remote sensing and Intelligence, Surveillance, and Reconnaissance (ISR) communities, the need for effective and appropriate UIs to command and control these sensors has also increased. However, despite the growing demand for SAR in operational environments, the technology still faces an adoption roadblock, in large part due to the lack of effective UIs. It is common to find operational interfaces that have barely grown beyond the disparate tools engineers and technologists developed to demonstrate an initial concept or system. While sensor usability and utility are common requirements to engineers and operators, their objectives for interacting with the sensor are different. As such, the amount and type of information presented ought to be tailored to the specific application.
This paper details modeling of metal fragmentation of pipe-bomb configurations using the Euler-Lagrange code Zapotec. Zapotec couples the hydrocode CTH with the transient-dynamics finite element code Sierra/SM (also known as Presto) through a step-wise interchange of geometry, state data, and pressure. In this work, three experimental studies of pipe-bomb configurations were simulated using Zapotec, where the metal case was modeled using finite elements and the explosive was modeled with CTH. In the three examples, experimental and simulated debris distributions and early-time debris velocities generally showed excellent agreement. These studies both help build confidence in the use of Zapotec for simulating structural response under shock loadings.
Fast, accurate and robust automatic target recognition (ATR) in optical aerial imagery can provide game-changing advantages to military commanders and personnel. ATR algorithms must reject non-targets with a high degree of confidence in a world with an infinite number of possible input images. Furthermore, they must learn to recognize new targets without requiring massive data collections. Whereas most machine learning algorithms classify data in a closed set manner by mapping inputs to a fixed set of training classes, open set recognizers incorporate constraints that allow for inputs to be labelled as unknown. We have adapted two template-based open set recognizers to use computer generated synthetic images of military aircraft as training data, to provide a baseline for military-grade ATR: (1) a frequentist approach based on probabilistic fusion of extracted image features, and (2) an open set extension to the one-class support vector machine (SVM). These algorithms both use histograms of oriented gradients (HOG) as features as well as artificial augmentation of both real and synthetic image chips to take advantage of minimal training data. Our results show that open set recognizers trained with synthetic data and tested with real data can successfully discriminate real target inputs from non-targets. However, there is still a requirement for some knowledge of the real target in order to calibrate the relationship between synthetic template and target score distributions. We conclude by proposing algorithm modifications that may improve the ability of synthetic data to represent real data.
Fully-polarimetric X-band (9.6 GHz center frequency) VideoSAR with 0.125-meter ground resolution flew collections before, during, and after the fifth Source Physics Experiment (SPE-5) underground chemical explosion. We generate and exploit synthetic aperture RADAR (SAR) and VideoSAR products to characterize surface effects caused by the underground explosion. To our knowledge, this has never been done. Exploited VideoSAR products are "movies" of coherence maps, phase-difference maps, and magnitude imagery. These movies show two-dimensional, time-varying surface movement. However, objects located on the SPE pad created unwanted, vibrating signatures during the event which made registration and coherent processing more difficult. Nevertheless, there is evidence that dynamic changes are captured by VideoSAR during the event. VideoSAR provides a unique, coherent, time-varying measure of surface expression of an underground chemical explosion.
This paper details modeling of metal fragmentation of pipe-bomb configurations using the Euler-Lagrange code Zapotec. Zapotec couples the hydrocode CTH with the transient-dynamics finite element code Sierra/SM (also known as Presto) through a step-wise interchange of geometry, state data, and pressure. In this work, three experimental studies of pipe-bomb configurations were simulated using Zapotec, where the metal case was modeled using finite elements and the explosive was modeled with CTH. In the three examples, experimental and simulated debris distributions and early-time debris velocities generally showed excellent agreement. These studies both help build confidence in the use of Zapotec for simulating structural response under shock loadings.
Classical RANS turbulence models have known deficiencies when applied to jets in crossflow. Identifying the linear Boussinesq stress-strain hypothesis as a major contribution to erroneous prediction, we consider and contrast two machine learning frameworks for turbulence model development. Gene Expression Programming, an evolutionary algorithm that employs a survival of the fittest analogy, and a Deep Neural Network, based on neurological processing, add non-linear terms to the stress-strain relationship. The results are Explicit Algebraic Stress Model-like closures. High fidelity data from an inline jet in crossflow study is used to regress new closures. These models are then tested on a skewed jet to ascertain their predictive efficacy. For both methodologies, a vast improvement over the linear relationship is observed.
The thermal decomposition of H2O2 is an important process in hydrocarbon combustion playing a particularly crucial role in providing a source of radicals at high pressure where it controls the 3rd explosion limit in the H2-O2 system, and also as a branching reaction in intermediatetemperature hydrocarbon oxidation. As such, understanding the uncertainty in the rate expression for this reaction is crucial for predictive combustion computations. Raw experimental measurement data, and its associated noise and uncertainty, is typically unreported in most investigations of elementary reaction rates, making the direct derivation of the joint uncertainty structure of the parameters in rate expressions difficult. To overcome this, we employ a statistical inference procedure, relying on maximum entropy and approximate Bayesian computation methods, and using a two-level nested Markov Chain Monte Carlo algorithm, to arrive at a posterior density on rate parameters for a selected case of laser absorption measurements in a shock tube study, subject to the constraints imposed by the reported experimental statistics. The procedure constructs a set of H2O2 concentration decay profiles consistent with these reported statistics. These consistent data sets are then used to determine the joint posterior density on the rate parameters through straightforward Bayesian inference. Broadly, the method also provides a framework for the replication and comparison of missing data from different experiments, based on reported statistics, for the generation of consensus rate expressions.
With the increasing use of hydrocodes in modelling and system design, benchmarking of software against experiments has become even more vital. While substantial work has been done in this regard, comparisons with temperature data within dynamic experiments are sparse due to experimental limitations. However, novel developments in measurement techniques has enabled the in-flight acquisition of hypervelocity projectile temperature, providing a new source for validation. This is achieved by tracking the decay of an induced magnetic field which is related to conductivity and further correlated to material temperature. As such, an AC-14 bare shaped charge with a copper lining is simulated using CTH, and benchmarked against experimental temperature results observed by Uhlig and Hummer. Particular attention was given to the slug temperature profiles after separation, and the effect of varying equation-of-state and strength models. Simulations are in agreement with experimental results, with a best case of under 2% error between the observed and simulated temperatures for this shaped charge setup. This varied notably (around 20% variance) depending on strength model. Jet structures compare well with radiographic images and are consistent with ALEGRA simulations previously conducted. SAND2017-3686C.
Nuclear power plants are increasingly adding digital components for plant operation, safety, and security. These digital components fill a gap with legacy equipment where replacement components no longer exist. They also benefit operation of the plant by increasing efficiency in power generation, monitoring of equipment and plant parameters, as well as aiding operator control. However, the addition of digital components and systems also adds cyber risks with previously unanalyzed failure modes and attack vectors are introduced with these new systems. These risks are difficult to identify, analyze, and mitigate due to the increasingly complex nature of the digital components and the integration of these components with additional plant processes and communication networks. The research presented in this paper develops a new method that addresses the cyber risk to inform appropriate levels of protection. EPRI and Sandia are working under a Cooperative Research and Development Agreement to develop an effective method of evaluating the cyber risk in production nuclear power facilities. The Cyber Hazards Analysis Risk Methodology (CHARM) focuses on ensuring adequate controls are in place for appropriate cyber protection of the plant from radiological release or generation risk. Existing plant hazards analyses (e.g., PRA, FTA) do not account for software deficiencies or adversarial intent. This method leverages existing plant analyses and MIT’s Systems Theoretic Process Analysis (STPA) to create cyber informed fault trees. These new fault trees will provide the basis for comprehensive cyber risk analysis and help ensure potential gaps in cyber security controls are identified and corrected.
While the low cost and strong safety record of lead-acid batteries make them an appealing option compared to lithium-ion technologies for stationary storage, they can be rapidly degraded by the extended periods of high rate, partial state-of-charge operation required in such applications. Degradation occurs primarily through a process called hard sulfation, where large PbSO4 crystals are formed on the negative battery plates, hindering charge acceptance and reducing battery capacity. Various researchers have found that the addition of some forms of excess carbon to the negative active mass in lead-acid batteries can mitigate hard sulfation, but the mechanism through which this is accomplished is unclear. In this work, the effect of carbon composition and morphology was explored by characterizing four discrete types of carbon additives, then evaluating their effect when added to the negative electrodes within a traditional valve-regulated lead-acid battery design. The cycle life for the carbon modified cells was significantly larger than an unmodified control, with cells containing a mixture of graphitic carbon and carbon black yielding the greatest improvement. The carbons also impacted other electrochemical aspects of the battery (e.g., float current, capacity, etc.) as well as physical characteristics of the negative active mass, such as the specific surface area.
When exposed to a strong radiant heat source (>1,000 kW/m2), combustible materials pyrolyze and ignite under certain conditions. Studies of this nature are scarce, yet important for some applications. Pyrolysis models derived at lower flux conditions do not necessarily extrapolate well to high-heat-flux conditions. The material response is determined by a complex interplay of thermal and chemical transport phenomena, which are often difficult to model. To obtain model validation data at high-heat-flux conditions (up to 2500 kW/m2), experiments on a variety of organic and engineered materials were performed at the National Solar Thermal Test Facility at Sandia National Laboratories. Mass loss during the short duration (2-4 sec) heat pulse was determined using the pre- and post-test weight. The mass-loss data were fairly linear in the fluence range of 200-6000 kJ/m2. When divided into subsets based on material types, the mass loss was similar at the peak flux/fluence condition for engineered polymers (≈1 g) and organic materials (≈2.5 g), although some exceptions exist (PMMA, dry pine needles). Statistical correlations were generated and used to evaluate the significance of the observed trends. These results contribute to the validation data for simulating fires and ignition resulting from very high incident heat flux.
With growing use of carbon fiber-epoxy in transportation systems, it is important to understand fire reaction properties of the composite to ensure passenger safety. Recently, a micro-scale pyrolysis study and macro-scale fire tests were performed using carbon fiber-epoxy at Sandia National Laboratories. Current work focuses on numerical modeling of the material conversion, pyrolysis, and gas-phase combustion that replicate the experiments. Large-eddy simulations (LES) and eddy-dissipation concept (EDC) approach are incorporated in the gas phase along with multiple relevant reaction model methods in the solid phase. The numerical methods that use multi-step pyrolysis rate expressions are validated by thermogravimetric analysis (TGA) results. The pyrolyzed fuel components participate in gas-phase combustion using a turbulent combustion model. The multi-phase combustion capability was further assessed using two cases: a single particle reaction and a solid panel exposed to strong radiant heat. The panel fire test indicates that the model accurately reproduces panel temperature profile while a weaker oxidation is predicted.
When a spherical liquid drop is subjected to a step change in relative gas velocity, aerodynamic forces lead to drop deformation and possible breakup into a number of secondary fragments. To investigate this flow, a digital in-line holography (DIH) diagnostic is proposed which enables rapid quantification of spatial statistics with limited experimental repetition. To overcome the high uncertainty in the depth direction experienced in previous applications of DIH, a crossed-beam, two-view configuration is introduced. With appropriate calibration, this diagnostic is shown to provide accurate quantification of fragment sizes, three-dimensional positions and three-component velocities in a large measurement volume. These capabilities are applied to investigate the aerodynamic breakup of drops at two non-dimensional Weber numbers, We, corresponding to the bag (We = 14) and sheet-thinning (We = 55) regimes. Ensemble average results show the evolution of fragment size and velocity statistics during the course of breakup. Results indicate that mean fragment sizes increase throughout the course of breakup. For the bag breakup case, the evolution of a multi-mode fragment size probability density is observed. This is attributed to separate fragmentation mechanisms for the bag and rim structures. In contrast, for the sheet-thinning case, the fragment size probability density shows only one distinct peak indicating a single fragmentation mechanism. Compared to previous related investigations of this flow, many orders of magnitude more fragments are measured per condition, resulting in a significant improvement in data fidelity. For this reason, this experimental dataset is likely to provide new opportunities for detailed validation of analytic and computational models of this flow.
The Integrated Human Event Analysis System for nuclear power plant internal events at-power application (hereafter "IDHEAS AT-POWER") is a new human reliability analysis (HRA) method developed by the U.S. Nuclear Regulatory Commission (NRC) in collaboration with the Electric Power Research Institute (EPRI). It was developed to provide a structured approach to the qualitative and quantitative analysis of operator actions during internal, at-power nuclear power plant events. The IDHEAS AT-POWER method was tested to evaluate whether its guidance can be practically applied to produce consistent HRA results. This paper presents study findings and final conclusions on the method performance. Lessons learned on study methodology and recommendations for method improvement are also presented.
The directed, head-to-tail self-assembly of microtubule filaments may be generalized in the context of Janus colloidal rods. Specifically, their assembly at the tens of micron-length scale involves a careful balance between long-range electrostatic repulsion and short-range attractive forces. Here we show that the addition of counterion salts increases the rate of directed assembly by screening the electrostatic forces and enhancing the effectiveness of short-range interactions at the microtubule ends.
The Reacting Particle and Boundary Layer (RPBL) model computes the transient-state conditions for a spherical, reacting, porous char particle and its reacting boundary layer. RPBL computes the transport of gaseous species with a Maxwell-Stefan multicomponent approach. Mass transfer diffusion coefficients are corrected to account for a non-stagnant bulk flow condition using a factor based on the Sherwood number. The homogeneous gas phase reactions are modeled with a syngas mechanism, and the heterogeneous reactions are calculated with a six-step reaction mechanism. Both homogeneous and heterogeneous reaction mechanisms are implemented in Cantera. Carbon density (burnout) is computed using the Bhatia and Perlmutter model to estimate the evolution of the specific surface area. Energy equations are solved for the gas temperature and the particle temperature. The physical properties of the particle are computed from the fractions of ash, carbon, and voids in the particle. The void fraction is computed assuming a constant diameter particle during the reaction process. RPBL solves a particle momentum equation in order to estimate the position of the particle in a specific reactor. We performed a validation and uncertainty quantification study with RPBL using experimental char oxidation data obtained in an optically accessible, laminar, entrained flow reactor at Sandia National Laboratories. We used a consistency analysis to compare RPBL and experimental data (with its associated uncertainty) for three coal chars over a range of particle sizes. We found consistency for particle temperature and velocity across all experiments.
The proper consideration of the radiation correction for bare-wire thermocouple measurements requires consideration of the convective and radiative heat transfer of the thermocouple with its surroundings, as well as conductive heat transfer between the thermocouple bead and the connecting thermocouple wires. This has rarely been considered in the past, and to do so has involved complex simulation of the complete thermocouple energy balance. This paper reports on a new, easy-to-implement approach for calculating the proper radiant correction for thermocouples, subject to uncertainties associated with the relevant thermocouple and gas properties and limitations to characterizing convective heat transfer to the thermocouple bead and wires via standard correlations. Examples of the radiation correction computed with this new method as a function of temperature and bead and wire size are given, and are compared with traditional approaches considering heat transfer around either the thermocouple bead or the thermocouple wire.
Compressible jet-in-crossflow interactions are poorly simulated using Reynolds-Averaged Navier Stokes (RANS) equations. This is due to model-form errors (physical approximations) in RANS as well as the use of parameter values simply picked from literature (hence- forth, the nominal values of the parameters). Previous work on the Bayesian calibration of RANS models has yielded joint probability densities of C = (Cµ;Cϵ2;Cϵ1), the most influential parameters of the RANS equations. The calibrated values were far more predictive than the nominal parameter values and the advantage held across a range of freestream Mach numbers and jet strengths. In this work we perform Bayesian calibration across a range of Mach numbers and jet strengths and compare the joint densities, with a view of determining whether compressible jet-in-crossflow could be simulated with either a single joint probability density or a point estimate for C. We find that probability densities for ;Cϵ2 agree and also indicate that the range typically used in aerodynamic simulations should be extended. The densities for ;Cϵ1 agree, approximately, with the nominal value. The densities for ;Cµ do not show any clear trend, indicating that they are not strongly constrained by the calibration observables, and in turn, do not affect them much. We also compare the calibrated results to a recently developed analytical model of a jet-in-cross flow interaction. We find that the values of C estimated by the analytical model delivers prediction accuracies comparable to the calibrated joint densities of the parameters across a range of Mach numbers and jet strengths.
Fluid-structure interactions were studied on a store with tunable structural natural frequencies in complex cavity flow. Different leading edge geometries, doors, and internal inserts were used to generate cavity pressure fields that were more representative of an actual aircraft bay. The store loading and response was characterized using point pressure and accelerometer measurements. These data were supplemented with high-frequency pressure-sensitive paint applied to both the store and to the cavity floor to capture the three-dimensional nature of the pressure field in the complex configurations. The natural frequencies of the store were then changed to allow a systematic study of mode matching between the structural natural frequencies and the dominant cavity tone frequencies. In the complex cavities, the store responded to the cavity resonant tones not only in the streamwise and wall-normal directions, but also the spanwise direction. That spanwise response to cavity tones was not observed for previous studies in a simple rectangular cavity, because the flow across the store width in the spanwise direction was uniform. This different behavior highlights the importance of using a representative bay geometry for prediction of the structural response of a store in a flight environment.
The combustion of molten metals is an important area of study with applications ranging from solid aluminized rocket propellants to fireworks displays. This work uses digital in-line holography (DIH) to experimentally quantify the three-dimensional position, size, and velocity of aluminum particles during combustion of ammonium perchlorate (AP) based solid-rocket propellants. In addition, spatially resolved particle temperatures are simultaneously measured using two-color imaging pyrometry. To allow for fast characterization of the properties of tens of thousands of particles, automated data processing routines are proposed. Using these methods, statistics from aluminum particles with diameters ranging from 15 to 900 µm are collected at an ambient pressure of 83 kPa. In the first set of DIH experiments, increasing initial propellant temperature is shown to enhance the agglomeration of nascent aluminum at the burning surface, resulting in ejection of large molten aluminum particles into the exhaust plume. The resulting particle number and volume distributions are quantified. In the second set of simultaneous DIH and pyrometry experiments, particle size and velocity relationships as well as temperature statistics are explored. The average measured temperatures are found to be 2640 ± 282 K, which compares well with previous estimates of the range of particle and gas-phase temperatures. The novel methods proposed here represent new capabilities for simultaneous quantification of the joint size, velocity, and temperature statistics during the combustion of molten metal particles. The proposed techniques are expected to be useful for detailed performance assessment of metalized solid-rocket propellants.
This work outlines a case study of charge-induced damage to SOI wafers that caused gate leakage in discrete transistors and static leakage in packaged integrated circuits (ICs). The consequential yield fallout occurred primarily at wafer center. Electrical, optical, and laser-based failure analysis techniques were used to characterize the damage and determine root cause of electrical failure. The failure mechanism was localized to a rinse step during chemical mechanical planarization (CMP). Furthermore, both current-voltage (IV) sweeps and characteristic spatial patterns generated by thermally-induced voltage alteration (TIVA) were used to capture the trends on both packaged ICs and SOI wafers for this type of charge-induced damage; this.led to quick identification of another source of charge-induced damage that affected the post-fab yield.
We present spatial profiles of temperature and soot-volume-fraction statistics from a sooting, 2-m base diameter turbulent pool fire, burning a 10%-toluene/90%-methanol fuel mixture. Dual-pump coherent anti-Stokes Raman scattering and laser-induced incandescence are utilized for simultaneous point measurements of temperature and soot. The research fuel-blend used here results in a lower soot loading than real transportation fuels, but allows us to apply high-fidelity laser diagnostics for spatially resolved measurements in a fully turbulent, buoyant fire of meter-scale base size. Profiles of mean and rms fluctuations are radially resolved across the fire plume, both within the hydrocarbon-rich vapor-dome region near fuel pool, and higher within the actively burning region of the fire. The spatial evolution of the soot and temperature probability density functions is discussed. Soot fluctuations display significant intermittency across the full extent of the fire plume for the research fuel blend used. Simultaneous, spatially overlapped temperature/soot measurements permit us to obtain estimates of joint statistics that are presented as spatially resolved conditional averages across the fire plume, and in terms of a joint pdf obtained by including measurements from multiple spatial locations. Within the actively burning region of the fire, soot is observed to occupy a limited temperature range between ∼1000 and 2000 K, with peak soot concentration occurring at 1600–1700 K across the full radial extent of the fire plume, despite marked changes in the local temperature pdf across the same spatial extent. A wider range of soot temperatures is observed in the fuel vapor-dome region low in the pool fire, with detectable cold soot persisting into conditionally averaged statistics. The results yield insight into soot temperature across a wide spatial extent of a fully turbulent pool fire of meaningful size, which are valuable for development of soot radiative-emission models and for validation of fire fluid-dynamics codes.
A detailed methodology was used to select the sea states tested in the final stage of the Wave Energy Prize (WEPrize), a public prize challenge sponsored by the U.S. Department of Energy [1]. The winner was selected based on two metrics: a threshold value expressing the benefit to effort ratio (ACE metric) and a second metric which included hydrodynamic performance-related quantities (HPQ). HPQ required additional sea states to query aspects of the techno-economic performance not addressed by ACE. Due to the nature of the WEPrize, limited time was allotted to each contestant for testing and thus a limitation on the total sea states was required. However, the applicability of these sea states was required to encompass seven deployment locations representative of the United States West Coast and Hawaii. A cluster analysis was applied to scatter diagrams in order to determine a subset of sea states that could be scaled to find the average annual power flux at each wave climate for the ACE metric. Four additional sea states were selected, including two highly energetic sea states and two bimodal sea states, to evaluate HPQ. These sea states offer a common experimental testing platform for performance in United States deployment climates.
The thermal decomposition of H2O2 is an important process in hydrocarbon combustion playing a particularly crucial role in providing a source of radicals at high pressure where it controls the 3rd explosion limit in the H2-O2 system, and also as a branching reaction in intermediatetemperature hydrocarbon oxidation. As such, understanding the uncertainty in the rate expression for this reaction is crucial for predictive combustion computations. Raw experimental measurement data, and its associated noise and uncertainty, is typically unreported in most investigations of elementary reaction rates, making the direct derivation of the joint uncertainty structure of the parameters in rate expressions difficult. To overcome this, we employ a statistical inference procedure, relying on maximum entropy and approximate Bayesian computation methods, and using a two-level nested Markov Chain Monte Carlo algorithm, to arrive at a posterior density on rate parameters for a selected case of laser absorption measurements in a shock tube study, subject to the constraints imposed by the reported experimental statistics. The procedure constructs a set of H2O2 concentration decay profiles consistent with these reported statistics. These consistent data sets are then used to determine the joint posterior density on the rate parameters through straightforward Bayesian inference. Broadly, the method also provides a framework for the replication and comparison of missing data from different experiments, based on reported statistics, for the generation of consensus rate expressions.
Dynamic materials properties experiments on Sandia National Laboratories Z Machine require increasingly precise electrical current pulse shaping. In the experiment described here, a copper flyer plate is accelerated from rest to 1,600 m/s over a 40 micron flight gap in 50 ns. This flyer then impacts a cerium sample, shock melting the cerium, before subsequent quasi-isentropic ramping to mega-bar pressures. Through predictive simulations, postdicted analysis, and a new computational tool for characterizing inherent Z Machine timing accuracy, qualitative estimates of pulse controllability and experimental design robustness are arrived upon.
Scattering environment conditions, such as fog, pose a challenge for many detection and surveillance active sensing operations in both ground and air platforms. For example, current autonomous vehicles rely on a range of optical sensors that are affected by degraded visual environments. Real-world fog conditions can vary widely depending on the location and environmental conditions during its creation. In our previous work we have shown benefits for increasing signal and range through scattering environments such as fog utilizing polarized light, specifically circular polarization. In this work we investigate the effect of changing fog particle sizes and distributions on polarization persistence for both circularly and linearly polarized light via simulation. We present polarization tracking Monte Carlo results for a range of realistic monodisperse particle sizes as well as varying particle size distributions as a model of scattering environments. We systematically vary the monodisperse particle size, mean particle size of a distribution, particle size distribution width, and number of distribution lobes (bi-modal), as they affect polarized light transmission through a scattering environment. We show that circular polarization signal persists better than linear polarization signal for most variations of the particle distribution parameters.
Scattering environment conditions, such as fog, pose a challenge for many detection and surveillance active sensing operations in both ground and air platforms. For example, current autonomous vehicles rely on a range of optical sensors that are affected by degraded visual environments. Real-world fog conditions can vary widely depending on the location and environmental conditions during its creation. In our previous work we have shown benefits for increasing signal and range through scattering environments such as fog utilizing polarized light, specifically circular polarization. In this work we investigate the effect of changing fog particle sizes and distributions on polarization persistence for both circularly and linearly polarized light via simulation. We present polarization tracking Monte Carlo results for a range of realistic monodisperse particle sizes as well as varying particle size distributions as a model of scattering environments. We systematically vary the monodisperse particle size, mean particle size of a distribution, particle size distribution width, and number of distribution lobes (bi-modal), as they affect polarized light transmission through a scattering environment. We show that circular polarization signal persists better than linear polarization signal for most variations of the particle distribution parameters.
Crawford, David A.; Susorney, Hannah C.M.; Barnouin, Olivier S.; Stickle, Angela M.; Ernst, Carolyn M.; Cintala, Mark J.
Target heterogeneities, such as cracks, faults, joints, and blocks, are known to influence impact crater morphology on planetary surfaces. We perform a preliminary investigation into how the relationship of target heterogeneity size to projectile size affects the cratering process and final crater morphology for a fixed impact velocity. We use the CTH hydrocode to numerically simulate these impacts into a strong target with idealized heterogeneities where the ratio of the projectile size and heterogeneity size is varied. When the projectile is significantly smaller than the size of the heterogeneities, the pressure field decay is similar to that for a half-space impact into a homogenous target. In contrast, when the projectile size is comparable to or larger than the heterogeneities, we observe more efficient attenuation of the shockwave, resulting in decreased cratering efficiency. The attenuation of the shockwave is caused by rarefaction waves reflecting off of the free surfaces of the heterogeneities and internal energy losses resulting from void space collapse when the target strength is overcome by the impact energy.
Sandia National Laboratories and the National Renewable Energy Laboratory conducted a field campaign at the Scaled Wind Farm Technology (SWiFT) Facility using a customized scanning lidar from the Technical University of Denmark. The results from this field campaign will support the validation of computational models to predict wake dissipation and wake trajectory offset downstream of a stand-alone wind turbine. In particular, regarding the effect of changes in the atmospheric boundary layer inflow state and turbine yaw offset. A key step in this validation process involves quantifying, and reducing, the uncertainty in the wake measurements. The present work summarizes the process that was used to calibrate the alignment of the lidar in order to reduce this source of uncertainty in the experimental data from the SWiFT field test.
Unstructured grid adaptation is a technology that holds the potential to improve the automation and accuracy of computational fluid dynamics and other computational disciplines. Difficulty producing the highly anisotropic elements necessary for simulation on complex curved geometries that satisfies a resolution request has limited this technology's widespread adoption. The Unstructured Grid Adaptation Working Group is an open gathering of researchers working on adapting simplicial meshes to conform to a metric field. Current members span a wide range of institutions including academia, industry, and national laboratories. The purpose of this group is to create a common basis for understanding and improving mesh adaptation. We present our first major contribution: a common set of benchmark cases, including input meshes and analytic metric specifications, that are publicly available to be used for evaluating any mesh adaptation code. We also present the results of several existing codes on these benchmark cases, to illustrate their utility in identifying key challenges common to all codes and important differences between available codes. Future directions are defined to expand this benchmark to mature the technology necessary to impact practical simulation workflows.
Degraded visual environments are a serious concern for modern sensing and surveillance systems. Fog is of interest due to the frequency of its formation along our coastlines disrupting border security and surveillance. Fog presents hurdles in intelligence and reconnaissance by preventing data collection with optical systems for extended periods. We will present recent results from our work in operating optical systems in our controlled fog experimental chamber. This facility is a 180-foot-long, 10-foot-wide, and 10-foot-Tall structure that has over 60 spray nozzles to achieve uniform aerosol coverage with various particle size, distributions, and densities. We will discuss the physical formation of fog in nature and how our generated fog compares. In addition, we will discuss fog distributions and characterization techniques. We will investigate the biases of different methods and discuss the different techniques that are appropriate for realistic environments. Finally, we will compare the data obtained from our characterization studies against accepted models (e.g., MODTRAN) and validate the usage of this unique capability as a controlled experimental realization of natural fog formations. By proving the capability, we will enable the testing and validation of future fog penetrating optical systems and providing a platform for performing optical propagation experimentation in a known, stable, and controlled environment.
The reactions of Criegee intermediates with NO2 have been proposed as a potentially significant source of the important nighttime oxidant NO3, particularly in urban environments where concentrations of ozone, alkenes and NOx are high. However, previous efforts to characterize the yield of NO3 from these reactions have been inconclusive, with many studies failing to detect NO3. In the present work, the reactions of formaldehyde oxide (CH2OO) and acetaldehyde oxide (CH3CHOO) with NO2 are revisited to further explore the product formation over a pressure range of 4-40 Torr. NO3 is not observed; however, temporally resolved and [NO2]-dependent signal is observed at the mass of the Criegee-NO2 adduct for both formaldehyde- and acetaldehyde-oxide systems, and the structure of this adduct is explored through ab initio calculations. The atmospheric implications of the title reaction are investigated through global modelling.
We experimentally demonstrate high-contrast, ultrafast switching of infrared light at 2.1 μm via intraband pumping of a high quality factor perfect absorber made from a highly doped cadmium oxide thin film.
We investigate a novel application of deep neural networks to modeling of errors in prediction of surface pressure fluctuations beneath a compressible, turbulent flow. In this context, the truth solution is given by Direct Numerical Simulation (DNS) data, while the predictive model is a wall-modeled Large Eddy Simulation (LES). The neural network provides a means to map relevant statistical flow-features within the LES solution to errors in prediction of wall pressure spectra. We simulate a number of flat plate turbulent boundary layers using both DNS and wall-modeled LES to build up a database with which to train the neural network. We then apply machine learning techniques to develop an optimized neural network model for the error in terms of relevant flow features.
There has only been one naturally occurring reactor region (Oklo) identified historically. There has to have been other factors that prevented uncontrolled nuclear criticality events. There are higher concentration uranium depositions in the earth's crust than the Oklo region, that did not go critical based on uranium enrichment. There are many papers on the Oklo phenomena which do not address why the uranium did not reach criticality prior to the historical point of 2 billion years ago, nor do they specifically address the lack of radiogenic lead in any of the uranium deposits. Consideration of the lack of lead as a potential indicator of the age of the earth as being a possible factor. Reports which address the leaching effect could consider the reactivity effect of moderation associated with higher enrichment uranium. The lack of radiogenic lead associated with the uranium may or may not be due to leaching. Also, the higher concentration uranium deposits (>15%) were discovered in the 1990s, and reevaluation of the overall effect on a natural reactor criticality were not considered. The high reactivity levels and the low quantity of radiogenic lead identified in uranium tailings, tends to favor a significantly shorter time period or a highly efficient naturally occurring leaching process. A shorter time period would reduce uranium mass and enrichment. Given even a small quantity of moderator would allow an uncontrolled nuclear criticality for high concentration uranium deposits for enrichment between 3 and 8 percent 235 U. The evaluation and analysis of the nuclear criticality safety factors should be evaluated further to document the actual uranium ore grade, and Pb constituents. Identification of the macro-scale quantity (PPM) of radiogenic lead coupled with the NCS factors could be a more useful tool for determining the age of the earth. Further calculations could be considered to determine the impact of different rock formations and materials where uranium is located, and evaluation of the natural leaching of uranium and its decay by-products to associate the effect of radiogenic lead or other materials.
Molecular dynamics simulations of polycrystalline growth of CdTe/CdS heterostructures have been performed. First, CdS was deposited on an amorphous CdS substrate, forming a polycrystalline film. Subsequently, CdTe was deposited on top of the polycrystalline CdS film. Cross-sectional images show grain formation at early stages of the CdS growth. During CdTe deposition, the CdS structure remains almost unchanged. Concurrently, CdTe grain boundary motion was detected after the first 24.4 nanoseconds of CdTe deposition. With the elapse of time, this grain boundary pins along the CdS/CdTe interface, leaving only a small region of epitaxial growth. CdTe grains are larger than CdS grains in agreement with experimental observations in the literature. Crystal phase analysis shows that zinc blende structure dominates over the wurtzite structure inside both CdS and CdTe grains. Composition analysis shows Te and S diffusion to the CdS and CdTe films, respectively. These simulated results may stimulate new ideas for studying and improving CdTe solar cell efficiency.
We demonstrate a silicon photonic transceiver circuit to implement polarization encoding/decoding for DV-QKD. The circuit is capable of encoding BB84 states with >30 dB PER and decoding with >20 dB ER.
The need to avoid SI engine knock often comes with an efficiency penalty, motivating efforts to understand its causes. In this study, the relationship between knock and end-gas autoignition is examined based on experiments in a DISI engine with CR = 12, using three different gasoline fuels. The three gasolines are an alkylate blend (RON=98, MON=97), a blend with high aromatic content (RON=98, MON=88), and a blend of 30% ethanol by volume (RON=98, MON=87). Fuel/air-equivalence ratio (φ) sweeps show that the response of the knock limits to changes in φ varies between the fuels. Furthermore, it is observed that the statistics of knock and heat-release vary in a complex manner between the fuels. Since knock originates from end-gas autoignition, a robust heat-release-based metric of "trace autoignition" is developed to determine knock occurrence. The metric is based on the observation that autoigniting cycles exhibit a faster heat-release rate decay at the end of the combustion event, even if no knock oscillations are detected. In general, the acoustic knock trends match the trends of the "trace autoignition" metric. However, for rich operation, the Alkylate fuel needs to be operated with an average CA50 that is somewhat retarded relative to trace autoignition. Furthermore, the data reveal that the dependence of autoignition on φ varies in manner that relates to the RON-MON octane sensitivity of the fuel. For example, the Alkylate fuel with low octane sensitivity displays no benefit of fuel enrichment, which is in strong contrast to the two high octane-sensitive fuels. Further, the Alkylate fuel shows a strong reduction of its anti-knock quality for lean operation, which correlates with the development of low-temperature heat release.
We experimentally demonstrate amplitude modulators (AMs) with >65 dB extinction across over a 160 nm spectral range. The output optical phase response is also characterized when the amplitude is modulated.
A series of nickel(ii) aryloxide ([Ni(OAr)2(py)x]) precursors was synthesized from an amide-alcohol exchange using [Ni(NR2)2] in the presence of pyridine (py). The H-OAr selected were the mono- and di-ortho-substituted 2-alkyl phenols: alkyl = methyl (H-oMP), iso-propyl (H-oPP), tert-butyl (H-oBP) and 2,6-di-alkyl phenols (alkyl = di-iso-propyl (H-DIP), di-tert-butyl (H-DBP), di-phenyl (H-DPhP)). The crystalline products were solved as solvated monomers and structurally characterized as [Ni(OAr)2(py)x], where x = 4: OAr = oMP (1), oPP (2); x = 3: OAr = oBP (3), DIP (4); x = 2: OAr = DBP (5), DPhP (6). The excited states (singlet or triplet) and various geometries of 1-6 were identified by experimental UV-vis and verified by computational modeling. Magnetic susceptibility of the representative compound 4 was fit to a Curie Weiss model that yielded a magnetic moment of 4.38(3)μB consistent with a Ni2+ center. Compounds 1 and 6 were selected for decomposition studied under solution precipitation routes since they represent the two extremes of coordination. The particle size and crystalline structure were characterized using transmission electron microscopy (TEM) and powder X-ray diffraction (PXRD). The materials isolated from 1 and 6 were found by TEM to form irregular shape nanomaterials (8-15 nm), which by PXRD were found to be Ni0 hcp (PDF: 01-089-7129) and fcc (PDF: 01-070-0989), respectively.
Griffith, Daniel; Loth, Eric; Kaminski, Meghan; Qin, Chao; Fingersh, Lee J.
A scaling methodology is described in the present paper for extreme-scale wind turbines (rated at 10 MW or more) that allow their sub-scale turbines to capture their key blade dynamics and aeroelastic deflections. For extreme-scale turbines, such deflections and dynamics can be substantial and are primarily driven by centrifugal, thrust and gravity forces as well as the net torque. Each of these are in turn a function of various wind conditions, including turbulence levels that cause shear, veer, and gust loads. The 13.2 MW rated SNL100-03 rotor design, having a blade length of 100-meters, is herein scaled to the CART3 wind turbine at NREL using 25% geometric scaling and blade mass and wind speed scaled by gravo-aeroelastic constraints. In order to mimic the ultralight structure on the advanced concept extreme-scale design the scaling results indicate that the gravo-aeroelastically scaled blades for the CART3 are be three times lighter and 25% longer than the current CART3 blades. A benefit of this scaling approach is that the scaled wind speeds needed for testing are reduced (in this case by a factor of two), allowing testing under extreme gust conditions to be much more easily achieved. Most importantly, this scaling approach can investigate extreme-scale concepts including dynamic behaviors and aeroelastic deflections (including flutter) at an extremely small fraction of the full-scale cost.
Amagat and Dalton mixing-models were analyzed to compare their thermodynamic prediction of shock states. Numerical simulations utilized the Sandra National Laboratories (SNL) shock hydrodynamic code CTH [1]. Simulations modeled the University of New Mexico (UNM) shock tube laboratory experimental series shocking a 1:1 molar mixture of helium (He) and sulfur hexafluoride (SF6). Five input parameters were varied for sensitivity analysis: driver section pressure; driver section density; test section pressure; test section density; and mixture ratio (mole fraction). We show via incremental Latin hypercube sampling (LHS) analysis that significant differences exist between Amagat and Dalton mixing-model predictions. The differences observed in predicted shock speeds, temperatures, and pressures grow more pronounced with higher shock speeds.
A parallel, adaptive overlay grid procedure is proposed for use in generating all-hex meshes for stochastic (SVE) and representative (RVE) volume elements in computational materials modeling. The mesh generation process is outlined including several new advancements such as data filtering to improve mesh quality from voxelated and 3D image sources, improvements to the primal contouring method for constructing material interfaces and pillowing to improve mesh quality at boundaries. We show specific examples in crystal plasticity and syntactic foam modeling that have benefitted from the proposed mesh generation procedure and illustrate results of the procedure with several practical mesh examples.
We study the role of carrier mobility in transparent conducting oxides integrated into epsilon-near-zero modulators. High-mobility materials including CdO enable sub-micron length electroabsorption modulators through >4dB/μm extinction ratios.
Percussive hammers are a promising advance in drilling technology for geothermal since they rely upon rock reduction mechanisms that are well-suited for use in the hard, brittle rock characteristic of geothermal formations. Also known as down-the-hole (DTH) hammers, they are also compatible with low-density fluids that are often used for geothermal drilling. Experience in mining and oil and gas drilling has demonstrated their utility for penetrating hard rock. One limitation to more wide-scale deployment is the ability of the tools to operate at high temperatures (∼300°C) due to elastomers used in the construction and the lubrication required for operation. As part of a United States Department of Energy Funding Opportunity Announcement award, Atlas Copco was tasked with developing a high-temperature DTH capable of being used in geothermal environments. A full-scale development effort including design, build, and testing was pursued for the project. This report summarizes the results of the percussive hammer development efforts between Atlas-Copco Secoroc and Sandia National Labs as part of DE-FOA-EE0005502. Certain design details have been omitted due to the proprietary nature of the information.
Lithium-ion batteries are a central technology to our daily lives with widespread use in mobile devices and electric vehicles. These batteries are also beginning to be widely used in electric grid infrastructure support applications which have stringent safety and reliability requirements. Typically, electrochemical performance data is not available for modelers to validate their simulations, mechanisms, and algorithms for lithium-ion battery performance and lifetime. In this paper, we report on the electrochemical performance of commercial 18650 cells at a variety of temperatures and discharge currents. We found that LiFePO4 is temperature tolerant for discharge currents at or below 10 A whereas LiCoO2, LiNixCoyAl1-x-yO2, and LiNi0.80Mn0.15Co0.05O2 exhibited optimal electrochemical performance when the temperature is maintained at 15◦C. LiNixCoyAl1-x-yO2 showed signs of lithium plating at lower temperatures, evidenced by irreversible capacity loss and emergence of a high-voltage differential capacity peak. Furthermore, all cells need to be monitored for self-heating, as environment temperature and high discharge currents may elicit an unintended abuse condition. Overall, this study shows that lithium-ion batteries are highly application-specific and electrochemical behavior must be well understood for safe and reliable operation. Additionally, data collected in this study is available for anyone to download for further analysis and model validation.
Compressible jet-in-crossflow interactions are poorly simulated using Reynolds-Averaged Navier Stokes (RANS) equations. This is due to model-form errors (physical approximations) in RANS as well as the use of parameter values simply picked from literature (hence- forth, the nominal values of the parameters). Previous work on the Bayesian calibration of RANS models has yielded joint probability densities of C = (Cµ;Cϵ2;Cϵ1), the most influential parameters of the RANS equations. The calibrated values were far more predictive than the nominal parameter values and the advantage held across a range of freestream Mach numbers and jet strengths. In this work we perform Bayesian calibration across a range of Mach numbers and jet strengths and compare the joint densities, with a view of determining whether compressible jet-in-crossflow could be simulated with either a single joint probability density or a point estimate for C. We find that probability densities for ;Cϵ2 agree and also indicate that the range typically used in aerodynamic simulations should be extended. The densities for ;Cϵ1 agree, approximately, with the nominal value. The densities for ;Cµ do not show any clear trend, indicating that they are not strongly constrained by the calibration observables, and in turn, do not affect them much. We also compare the calibrated results to a recently developed analytical model of a jet-in-cross flow interaction. We find that the values of C estimated by the analytical model delivers prediction accuracies comparable to the calibrated joint densities of the parameters across a range of Mach numbers and jet strengths.
High performance computing (HPC) is undergoing a dramatic change in computing architectures. Nextgeneration HPC systems are being based primarily on many-core processing units and general purpose graphics processing units (GPUs). A computing node on a next-generation system can be, and in practice is, heterogeneous in nature, involving multiple memory spaces and multiple execution spaces. This presents a challenge for the development of application codes that wish to compute at the extreme scales afforded by these next-generation HPC technologies and systems - the best parallel programming model for one system is not necessarily the best parallel programming model for another. This inevitably raises the following question: how does an application code achieve high performance on disparate computing architectures without having entirely different, or at least significantly different, code paths, one for each architecture? This question has given rise to the term ‘performance portability’, a notion concerned with porting application code performance from architecture to architecture using a single code base. In this paper, we present the work being done at Sandia National Labs to develop a performance portable compressible CFD code that is targeting the ‘leadership’ class supercomputers the National Nuclear Security Administration (NNSA) is acquiring over the course of the next decade.
High performance computing (HPC) is undergoing a dramatic change in computing architectures. Nextgeneration HPC systems are being based primarily on many-core processing units and general purpose graphics processing units (GPUs). A computing node on a next-generation system can be, and in practice is, heterogeneous in nature, involving multiple memory spaces and multiple execution spaces. This presents a challenge for the development of application codes that wish to compute at the extreme scales afforded by these next-generation HPC technologies and systems - the best parallel programming model for one system is not necessarily the best parallel programming model for another. This inevitably raises the following question: how does an application code achieve high performance on disparate computing architectures without having entirely different, or at least significantly different, code paths, one for each architecture? This question has given rise to the term ‘performance portability’, a notion concerned with porting application code performance from architecture to architecture using a single code base. In this paper, we present the work being done at Sandia National Labs to develop a performance portable compressible CFD code that is targeting the ‘leadership’ class supercomputers the National Nuclear Security Administration (NNSA) is acquiring over the course of the next decade.
Proceedings of SPIE - The International Society for Optical Engineering
Jin, Yuan; Wu, Chongzhao; Reno, John L.; Kumar, Sushil
Plasmonic lasers generate coherent long-range or localized surface-plasmon-polaritons (SPPs), where the SPP mode exists at the interface of the metal (or a metallic nanoparticle) and a dielectric. Metallic-cavities sup- porting SPP modes are also utilized for terahertz quantum-cascade lasers (QCLs). Due to subwavelength apertures, plasmonic lasers have highly divergent radiation patterns. Recently, we theoretically and experimentally demonstrated a new technique for implementing distributed-feedback (DFB), which is termed as an antenna- feedback scheme, to establish a hybrid SPP mode in the surrounding medium of a plasmonic laser's cavity with a large wavefront. This technique allows such lasers to radiate in narrow beams without requirement of any specific design considerations for phase-matching. Experimental demonstration is done for terahertz QCLs that show beam-divergence as small as 4-degrees. The antenna-feedback scheme has a characteristic feature in that refractive-index of the laser's surrounding medium affects its radiative frequency in the same vein as refractive- index of the cavity. Hence, any perturbations in the refractive-index of the surrounding medium could lead to large modulation in the laser's emission frequency. Along this line, we report ∼57 GHz reversible, continuous, and mode-hop-free tuning of such QCLs operating at 78 K based on post-process deposition/etching of a dielectric on an already mounted QCL chip. This is the largest tuning range achieved for terahertz QCLs when operating much above the temperature of liquid-Helium. We review the aforementioned experimental results and discuss methods to increase optical power output from terahertz QCLs with antenna-feedback. Peak power output of ∼13 mW is realized for a 3.3 THz QCL operating in a Stirling cooler at 54 K. A new dual-slit photonic structure based on antenna-feedback scheme is proposed to further improve output power as well as provide enhanced tunability.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Curry, Matthew L.; Haddock, Walker; Bangalore, Purushotham V.; Skjellum, Anthony
High-performance computing (HPC) demands high bandwidth and low latency in I/O performance leading to the development of storage systems and I/O software components that strive to provide greater and greater performance. However, capital and energy budgets along with increasing storage capacity requirements have motivated the search for lower cost, large storage systems for HPC. With Burst Buffer technology increasing the bandwidth and reducing the latency for I/O between the compute and storage systems, the back-end storage bandwidth and latency requirements can be reduced, especially underneath an adequately sized modern parallel file system. Cloud computing has led to the development of large, low-cost storage solutions where design has focused on high capacity, availability, and low energy consumption at lowest cost. Cloud computing storage systems leverage duplicates and erasure coding technology to provide high availability at much lower cost than traditional HPC storage systems. Leveraging certain cloud storage infrastructure and concepts in HPC would be valuable economically in terms of cost-effective performance for certain storage tiers. To enable the use of cloud storage technologies for HPC we study the architecture for interfacing cloud storage between the HPC parallel file systems and the archive storage. In this paper, we report our comparison of two erasure coding implementations for the Ceph file system. We compare measurements of various degrees of sharding that are relevant for HPC applications. We show that the Gibraltar GPU Erasure coding library outperforms a CPU implementation of an erasure coding plugin for the Ceph object storage system, opening the potential for new ways to architect such storage systems based on Ceph.
A series of tests have been performed on Sierra White granite subjected to general (true triaxial) states of stress. Tests were performed under constant Lode angle conditions at Lode angles of 23.4, 16.1 and 0°. The constant Lode angle condition was maintained by holding the minimum principal stress constant while increasing the maximum and intermediate principal stress at a predetermined ratio. Tests were performed at minimum principal stresses of 5, 17 and 30 MPa. All of the specimens failed in a brittle manner, with significant dilatant volume strain accumulated, and failure showed a strong dependence on Lode angle. Specimens behaved in a nearly linear elastic manner until approximately 75% of the peak stress was reached. The angle of the failure feature (shear band) was compared to predictions developed by using the Rudnicki and Rice (1975) localization criterion. It was found that there was good agreement (within 7°) between the experimental results and theoretical predictions.
This paper provides a review of current state-of-the-art commercial central receiver systems and emerging technologies intended to increase the outlet temperature to >700 °C. Research on particle-based, gas-based, and liquid-based receiver designs that can achieve these higher temperatures are discussed. Particle-based technologies include directly irradiated designs (free-falling, obstructed, centrifugal) and enclosed designs (gravity fed, fluidized). New gas-based receivers include micro-channel designs and light-trapping configurations that increase the surface area, heat transfer, and solar absorptance to enable higher fluxes and pressures. Liquid-based receivers and materials that are reviewed include high-temperature halide salts (chlorides and fluorides), carbonate salts, and liquid metals (sodium and lead bismuth). Advantages and challenges associated with each of the technologies and receiver designs are presented.
Process-induced residual stresses commonly occur in composite structures composed of dissimilar materials. These residual stresses form due to differences in the composite materials' coefficients of thermal expansion and the shrinkage upon cure exhibited by polymer matrix materials. Depending upon the specific geometric details of the composite structure and the materials' curing parameters, it is possible that these residual stresses could result in interlaminar delamination or fracture within the composite. Therefore, the consideration of potential residual stresses is important when designing composite parts and their manufacturing processes. However, the experimental determination of residual stresses in prototype parts can be time and cost prohibitive. As an alternative to physical measurement, it is possible for computational tools to be used to quantify potential residual stresses in composite prototype parts. Therefore, the objective of this study is the development of a simplistic method for simulating the residual stresses formed in polymer matrix composite structures. Specifically, a simplified approach accounting for both coefficient of thermal expansion mismatch and polymer shrinkage is implemented within the Sandia National Laboratories' developed SIERRA/SolidMechanics code Adagio. Concurrent with the model development, two simple, bi-material structures composed of a carbon fiber/epoxy composite and aluminum, a flat plate and a cylinder, are fabricated and the residual stresses are quantified through the measurement of deformation. Then, in the process of validating the developed modeling approach with the experimental residual stress data, manufacturing process simulations of the two simple structures are developed and undergo a formal verification and validation process, including a mesh convergence study, sensitivity analysis, and uncertainty quantification. The simulations' final results show adequate agreement with the experimental measurements, indicating the validity of a simple modeling approach, as well as a necessity for the inclusion of material parameter uncertainty in the final residual stress predictions.
Challenge scenarios provide an opportunity to assess the blind, quantitative predictive ability of simulation methods against a previously unseen failure problem. Rather than evaluate the predictions of a single simulation approach, the Sandia Fracture Challenges rely on numerous volunteer teams with expertise in computational mechanics to apply a broad range of computational methods, numerical algorithms, and constitutive models to the challenge.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Haddock, Walker; Curry, Matthew L.; Bangalore, Purushotham V.; Skjellum, Anthony
High-performance computing (HPC) demands high bandwidth and low latency in I/O performance leading to the development of storage systems and I/O software components that strive to provide greater and greater performance. However, capital and energy budgets along with increasing storage capacity requirements have motivated the search for lower cost, large storage systems for HPC. With Burst Buffer technology increasing the bandwidth and reducing the latency for I/O between the compute and storage systems, the back-end storage bandwidth and latency requirements can be reduced, especially underneath an adequately sized modern parallel file system. Cloud computing has led to the development of large, low-cost storage solutions where design has focused on high capacity, availability, and low energy consumption at lowest cost. Cloud computing storage systems leverage duplicates and erasure coding technology to provide high availability at much lower cost than traditional HPC storage systems. Leveraging certain cloud storage infrastructure and concepts in HPC would be valuable economically in terms of cost-effective performance for certain storage tiers. To enable the use of cloud storage technologies for HPC we study the architecture for interfacing cloud storage between the HPC parallel file systems and the archive storage. In this paper, we report our comparison of two erasure coding implementations for the Ceph file system. We compare measurements of various degrees of sharding that are relevant for HPC applications. We show that the Gibraltar GPU Erasure coding library outperforms a CPU implementation of an erasure coding plugin for the Ceph object storage system, opening the potential for new ways to architect such storage systems based on Ceph.
Nuclear power plants and facilities have been implementing digital system upgrades into their previously analog systems for well over twenty years. New nuclear facilities’ control, security, and emergency preparedness systems are almost exclusively built on digital architectures with a high degree of communication between the various systems that are often integrated together into a central control station to aid in operation or security of the facility. As digital systems become more widespread in nuclear facility control system architectures, cyber security related issues have become a significant concern to operators, regulators, governments, and other groups. Among the many concerns related to digital systems and cyber security is the area of common cause and common mode failures. This paper introduces, defines, and discusses some sources of common cause failure from a cyber security perspective: common vector access. This refers to specific access points that an adversary can exploit through a single attack sequence that have the potential to provide relational failures through common cause on multiple components, subsystems, systems, or plants. This paper will further discuss interconnected processes where these access points may exist, the importance of limiting or controlling these pinch points, and some methods of protecting common vector access points.
Pulse-burst particle image velocimetry has been used to acquire time-resolved data at 37.5 kHz of the flow over a finite-width rectangular cavity at Mach 0.8. Power spectra of the particle image velocimetry data reveal four resonance modes that match the frequencies detected simultaneously using high-frequency wall pressure sensors, but whose magnitudes exhibit spatial dependence throughout the cavity. Spatiotemporal cross correlations of velocity to pressure were calculated after bandpass filtering for specific resonance frequencies. Cross-correlation magnitudes express the distribution of resonance energy, revealing local maxima and minima at the edges of the shear layer attributable to wave interference between downstream-and upstream-propagating disturbances. Turbulence intensities were calculated using a triple decomposition and are greatest in the core of the shear layer for higher modes, where resonant energies ordinarily are lower. Most of the energy for the lowest mode lies in the recirculation region and results principally from turbulence rather than resonance. Together, the velocity-pressure cross correlations and the triple-decomposition turbulence intensities explain the sources of energy identified in the spatial distributions of power spectra amplitudes.
Process induced residual stresses commonly occur in composite structures composed of dissimilar materials. These residual stresses form due to differences in the composite materials' coefficients of thermal expansion as well as the shrinkage upon cure exhibited by most thermoset polymer matrix materials. Depending upon the specific geometric details of the composite structure and the materials' curing parameters, it is possible that these residual stresses can result in interlaminar delamination and fracture within the composite as well as plastic deformation in the structure's metallic materials. Therefore, the consideration of potential residual stresses is important when designing composite parts and their manufacturing processes. However, the experimental determination of residual stresses in prototype parts can be prohibitive, both in terms of financial and temporal costs. As an alternative to physical measurement, it is possible for computational tools to be used to quantify potential residual stresses in composite prototype parts. A simplified method for simulating residual stresses was previously validated with two simple bi-material structures composed of aluminum and a carbon fiber/epoxy resin composite. Therefore, the objective of this study is to further validate the simplified method for simulating residual stresses for different composites and more complex structures. The simplified method accounts for both the coefficient of thermal expansion mismatch and polymer shrinkage through the calibration to an experimentally-determined stress-free temperature. This was implemented in Sandia National Laboratories' solid mechanics code, SIERRA, to model split rings with temperature independent and dependent material models. The split rings are comprised of two materials: Aluminum with either a carbon fiber/epoxy resin composite or a glass fiber/epoxy resin composite. Concurrent with the computational efforts, structures similar to those modeled are fabricated and the residual stresses are quantified through the measurement of deformations. The simulations' results are compared to the experimentally observed behaviors for model validation. The results of the comparisons indicate that the proposed finite element modeling approach is capable of accurately simulating the formation of residual stresses in composite structures and a temperature independent material model is adequate within the composite's glassy region. Copyright 2017. Used by CAMX - The Composites and Advanced Materials Expo.
Visual inspection research has a long history spanning the 20th century and continuing to the present day. Current efforts in multiple venues demonstrate that visual inspection continues to have a vital role for many different types of tasks in the 21st century. The nature of this role spans the range from traditional human visual inspection to fully automated detection of defects. Consequently, today's practitioners must not only successfully identify and apply lessons learned from the past, but also explore new areas of research in order to derive solutions for modern day issues such as those presented by introducing automation during inspection. A key lesson from past research indicates that the factors that can degrade performance will persist today, unless care is taken to design the inspection process appropriately.
Ovarian cancer (OvCa) is the fifth leading cause of cancer deaths in women and remains the deadliest gynecological cancer. Our study goal is to examine associations between diagnostic patterns and OvCa stages. We used the data from a web-based survey in which more than 500 women diagnosed with OvCa provided both free text responses and staging information. We employed text mining and natural language processing (NPL) to extract information on clinical diagnostic characteristics, together with 21 dichotomous symptomatic variables, patient-centered advocacy, and polytomous disease severity, with internal validation. We conducted multivariate analyses and developed tree-based classification models with the confirmation of Random Forest to determine important factors in the relationships of the clinical diagnostic characteristics with OvCa stages. Models including the symptoms, patient advocacy tendency, disease severity and doctors' responses as predictors, had a much better predictive power than those limited to doctors' responses alone, indicating that OvCa stage at diagnosis depends on more than just doctors' responses. Although effective early stage diagnosis and treatment remains a challenge, our analysis of patient-centered clinical diagnostic characteristics and symptoms shows that self-advocacy is essential for all women. The frontline physician is critically important in ensuring effective follow-up and timely treatment before diagnosis.
There are gaps in understanding how a cyber-attack would manifest itself within power plants and what these events would look like within the control room from an operator’s perspective. This is especially true for nuclear power plants where safety has much broader consequences than nonnuclear plants. The operating and emergency procedures that operators currently use are likely inadequate for targeted cyber-attacks. This research focuses on understanding how a cyber event would affect the operation of the plant, how an operator would perceive the event, and if the operator’s actions would keep the plant in a safe condition. This research is part of Sandia’s Laboratory Directed Research and Development program where a nuclear power plant cyber model of the control system digital architecture is coupled with a generic pressurized water reactor plant training simulator. Cyber event scenarios will be performed on the coupled system with plant operators. The scenarios simulate plant conditions that may exist during a cyber-attack, component failure, or insider sabotage, and provide an understanding of the displayed information and the actual plant conditions. These scenarios will determine if plant operators can 1) recognize that they are under cyber-attack and 2) take appropriate actions to keep the plant safe. This will also provide the opportunity to assess the operator cognitive workload during such events and identify where improvements might be made. Experiments with nuclear power plant operators will be carried out over FY 2018 and results of the research are expected by the end of FY 2018.
A sodium coolant accident analysis code is necessary to provide regulators with a means of performing confirmatory analyses for future sodium reactor licensing submissions. MELCOR and CONTAIN, which have been employed by the U.S. Nuclear Regulatory Commission for light water reactor licensing, have been traditionally used for Level 2 and Level 3 probabilistic analyses as well as containment design basis accident analysis. To meet future regulatory needs, new models are being added to the MELCOR code for simulation of sodium reactor designs by integrating the existing models developed for separate effects codes into the MELCOR architecture. Sodium properties and equations of state, such as from the SAS4A code, have previously been implemented into MELCOR to replace the water properties and equation of state. Additional specific sodium-related models to address design basis accidents are now being implemented into MELCOR from CONTAIN-LMR. Although the codes are very different in the code architecture, the feasibility fit is being investigated, and the models for the sodium spray fire and the sodium pool fire have been integrated into MELCOR. A new package called Sodium Chemistry (NAC) has been added to MELCOR to handle all sodium related chemistry models for sodium reactor safety applications. Although MELCOR code requires the ambient condition to be above the freezing point of the coolant (e.g., sodium or water), the high relative freezing point of sodium requires MELCOR to handle situations, particularly far from the primary circuit, where the ambient temperatures are usually at room temperature. Because only a single coolant can be modeled in a problem at a time, any presence of water in the problem would be treated as a trace material, an aerosol, in MELCOR. This paper addresses and describe the integration of the sodium models from CONTAIN-LMR, and the testing of the sodium chemistry models in the NAC package of MELCOR that handles sodium type reactor accidents, using available sodium experiments on spray fire and pool fire. In addition, we describe the anticipated sodium models to be completed in this year, such as the atmospheric chemistry model and sodiumconcrete interaction model. Code-to-code comparison between MELCOR and CONTAIN-LMR results, in addition to the experiment code validations, will be demonstrated in this year.
ASME 2017 11th International Conference on Energy Sustainability Es 2017 Collocated with the ASME 2017 Power Conference Joint with Icope 2017 the ASME 2017 15th International Conference on Fuel Cell Science Engineering and Technology and the ASME 2017 Nuclear Forum
Previous research at Sandia National Laboratories showed the potential advantages of using light-trapping features which are not currently used in direct tubular receivers. A horizontal bladed receiver arrangement showed the best potential for increasing the effective solar absorptance by increasing the ratio of effective surface area to the aperture footprint. Ray-tracing analyses using SolTrace were performed to understand the light-trapping effects of the bladed receivers, which enable re-reflections between the fins that enhance the effective solar absorptance. A parametric optimization study was performed to determine the best possible configuration with a fixed intrinsic absorptivity of 0.9 and exposed surface area of 1 m2. The resulting design consisted of three vertical panels 0.584 m long and 0.508 m wide and 3 blades 0.508 m long and 0.229 m wide with a downward tilt of 50 degrees from the horizontal. Each blade consisted of two panels which were placed in front of the three vertical panels. The receiver was tested at the National Solar Thermal Test Facility using pressurized air. However, the receiver was designed to operate using supercritical carbon dioxide (sCO2) at 650 °C and 15 MPa for 100,000 hours following the ASME Boiler and Pressure Vessel Code Section VIII Division 1. The air flowed through the leading panel of the blade first, and then recirculated toward the back panel of the blade before flowing through one of the vertical back panels. The test results of the bladed receiver design showed a receiver efficiency increase over a flat receiver panel of ∼5 - 7% (from ∼80% to ∼86%) over a range of average irradiances, while showing that the receiver tubes can withstand temperatures > 800 °C with no issues. Computational fluid dynamics (CFD) modeling using the Discrete Ordinates (DO) radiation model was used to predict the temperature distribution and the resulting receiver efficiencies. The predicted thermal efficiency and surface temperature values correspond to the measured efficiencies and surface temperatures within one standard deviation. In the near future, an sCO2 flow system will be built to expose the receiver to higher pressure and fluid temperatures which could yield higher efficiencies.
Residual stresses can form within composite structures composed of asymmetric laminates during the elevated temperature curing processes common to composite materials. These residual stresses are primarily the result of unbalanced thermal strains that develop throughout the structure due to the composite's orthotropic coefficients of thermal expansion. Furthermore, structures composed of textile, or woven, composite fabrics lend themselves to the formation of these residual stresses, as extreme care must be taken during the lay-up of such parts to ensure that adjacent plies are placed front-to-front or back-to-back, as opposed to front-to-back, to eliminate the potential for any unbalanced thermal strains. Depending upon the specific geometric details of the composite structure of interest, it is possible that these residual stresses could result in fracture within the composite. Therefore, the consideration of potential residual stresses formed throughout the manufacturing process is important. However, the experimental determination of residual stresses in prototype parts can be time and cost prohibitive. As an alternative to physical measurement, it is possible for computational tools to be used to quantify potential residual stresses in composite prototype parts. Therefore, the objectives of this study are two-fold. First, a simplistic method for simulating the residual stresses formed in polymer matrix composite structures is developed within the Sandia National Laboratories' SIERRA/SolidMechanics code Adagio. Subsequently, the required level of model fidelity necessary to provide realistic predictions of a textile composite's residual stress state is determined. Concurrent with the computational activities, asymmetric plates of a woven carbon fiber/epoxy composite are manufactured with varying thicknesses and the residual stresses exhibited by the plates are quantified through the measurement of deformation. The developed computational approach is used to simulate the manufacturing process of these asymmetric plates and final comparisons of the predicted and experimental results show reasonable agreement.
ASME 2017 11th International Conference on Energy Sustainability, ES 2017, collocated with the ASME 2017 Power Conference Joint with ICOPE 2017, the ASME 2017 15th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2017 Nuclear Forum
Supercritical carbon dioxide (sCO2) Brayton power cycles have the potential to significantly improve the economic viability of concentrating solar power (CSP) plants by increasing the thermal to electric conversion efficiency from around 35% using high-temperature steam Rankine systems to above 45% depending on the cycle configuration. These systems are the most likely path toward achieving the Department of Energy's (DOE) Office of Energy Efficiency and Renewable Energy (EERE) SunShot targets for CSP tower thermal to electric conversion efficiency above 50% with dry cooling to air at 40 °C and a power block cost of less than 900 $/kWe. Many studies have been conducted to optimize the performance of various sCO2 Brayton cycle configurations in order to achieve high efficiency, and a few have accounted for drivers of cost such as equipment size in the optimization, but complete techno-economic optimization has not been feasible because there are no validated models relating component performance and cost. Reasonably accurate component cost models exist from several sources for conventional equipment including turbines, compressors, and heat exchangers for use in rough order of magnitude cost estimates when assembling a system of conventional equipment. However, cost data from fabricated equipment relevant to sCO2 Brayton cycles is very limited in terms of both supplier variety and performance level with most existing data in the range of 1 MWe power cycles or smaller systems, a single completed system around 7 MWe by Echogen Power Systems, and numerous ROM estimates based on preliminary designs of equipment for 10 MWe systems. This data is highly proprietary as the publication of individual data by any single supplier would damage their market position by potentially allowing other vendors to undercut their stated price rather than competing on reduced manufacturing costs. This paper describes one approach to develop component cost models in order to enable the techno-economic optimization activities needed to guide further research and development while protecting commercially proprietary information from individual vendors. Existing cost models were taken from literature for each major component used in different sCO2 Brayton cycle configurations and adjusted for their magnitude to fit the limited vendor cost data and estimates available. A mean fit curve was developed for each component and used to calculate updated cost comparisons between previously-reviewed sCO2 Brayton cycle configurations for CSP applications including simple recuperated, recompression, cascaded, and mixed-gas combined bifurcation with intercooling cycles. These fitting curves represent an average of the assembled vendor data without revealing any individual vendor cost, and maintain the scaling behavior with performance expected from similar equipment found in literature.
Fuel and oxidizer mixing is a key parameter influencing combustion and emission performance in diesel engines. At the same time, quantitative mixing measurements in automotive sprays are very challenging such that only a few experimental results are available as targets for the development and tuning of numerical models. The caveat is that the experimental data mainly concern the quasi-steady part of the jet, while it can be argued that the injection process in current alternative thermal engines is mostly transient. This work applies planar laser Rayleigh scattering at high-frequency to resolve the development and mixing of vaporized diesel sprays injected in a highly-pressurized environment. The state-of-the-art equipment employed for these experiments include a purposely-built high-power, high-repetition rate pulsed burst laser, optimized optics and a state-of-the-art high-speed CMOS camera. Advanced image processing methods were developed and implemented to mitigate the negative effects of the extreme environments found in diesel engines at the time of injection. The experiments provided two-dimensional mean and variance of the mixture and temperature quantities. The optical system's high spatial and temporal resolution enables tracking of the mixing field with time and space, from which temporally and spatially correlated mixing quantities can be extracted. Further analysis of the detailed mixture and temperature fields offered information about the turbulent mixing process of high-pressure diesel sprays such as scalar dissipation rates or turbulent length scales. Substantial effort was made to assess the uncertainties and limitations of such experimental results due to the optically challenging environment.
The performance of electronic systems for radio-frequency (RF) spectrum analysis is critical for agile radar and communications systems, ISR (intelligence, surveillance, and reconnaissance) operations in challenging electromagnetic (EM) environments, and EM-environment situational awareness. While considerable progress has been made in size, weight, and power (SWaP) and performance metrics in conventional RF technology platforms, fundamental limits make continued improvements increasingly difficult. Alternatively, we propose employing cascaded transduction processes in a chip-scale nano-optomechanical system (NOMS) to achieve a spectral sensor with exceptional signal-linearity, high dynamic range, narrow spectral resolution and ultra-fast sweep times. By leveraging the optimal capabilities of photons and phonons, the system we pursue in this work has performance metrics scalable well beyond the fundamental limitations inherent to all electronic systems. In our device architecture, information processing is performed on wide-bandwidth RF-modulated optical signals by photon-mediated phononic transduction of the modulation to the acoustical-domain for narrow-band filtering, and then back to the optical-domain by phonon-mediated phase modulation (the reverse process). Here, we rely on photonics to efficiently distribute signals for parallel processing, and on phononics for effective and flexible RF-frequency manipulation. This technology is used to create RF-filters that are insensitive to the optical wavelength, with wide center frequency bandwidth selectivity (1-100GHz), ultra-narrow filter bandwidth (1-100MHz), and high dynamic range (70dB), which we will present. Additionally, using this filter as a building block, we will discuss current results and progress toward demonstrating a multichannel-filter with a bandwidth of < 10MHz per channel, while minimizing cumulative optical/acoustic/optical transduced insertion-loss to ideally < 10dB. These proposed metric represent significant improvements over RF-platforms.
In order to bypass the limitation of bulk metallic glasses fabrication, we synthesized thin film metallic glasses to study the corrosion characteristics of a wide atomic% composition range, Mg(35.9-63%)Ca(4.1-21%)Zn(17.9-58.3%), in simulated body fluid. We highlight a clear relationship between Zn content and corrosion current such that Zn-medium metallic glasses exhibit minimum corrosion. In addition, we found higher Zn content leads to a poor in vitro cell viability. These results showcase the benefit of evaluating a larger alloy compositional space to probe the limits of corrosion resistance and prescreen for biocompatible applications.
A study was performed to optimize the geometry of a point absorber style wave energy converter (WEC). An axisymmetric single-body device, moving in heave only, was considered. Design geometries, generated using a parametric definition, were optimized using genetic algorithms. Each geometry was analyzed using a boundary element model (BEM) tool to obtain corresponding frequency domain models. Based on these models, a pseudo-spectral method was applied to develop a control methodology for each geometry. The performance of each design was assessed using a Bretschneider sea state. The objective of optimization is to maximize harvested energy. In this preliminary investigation, a constraint is imposed on the the geometry to guarantee a linear dynamic model would be valid for all geometries generated by the optimization tool. Numerical results are presented for axisymmetric buoy shapes.
ASME 2017 11th International Conference on Energy Sustainability, ES 2017, collocated with the ASME 2017 Power Conference Joint with ICOPE 2017, the ASME 2017 15th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2017 Nuclear Forum
Particle-based concentrating solar power (CSP) plants have been proposed to increase operating temperature for integration with higher efficiency power cycles using supercritical carbon dioxide (sCO2). The majority of research to date has focused on the development of high-efficiency and high-temperature particle solar thermal receivers. However, system realization will require the design of a particle/sCO2 heat exchanger as well for delivering thermal energy to the power-cycle working fluid. Recent work has identified moving packed-bed heat exchangers as low-cost alternatives to fluidized-bed heat exchangers, which require additional pumps to fluidize the particles and recuperators to capture the lost heat. However, the reduced heat transfer between the particles and the walls of moving packed-bed heat exchangers, compared to fluidized beds, causes concern with adequately sizing components to meet the thermal duty. Models of moving packed-bed heat exchangers are not currently capable of exploring the design trade-offs in particle size, operating temperature, and residence time. The present work provides a predictive numerical model based on literature correlations capable of designing moving packed-bed heat exchangers as well as investigating the effects of particle size, operating temperature, and particle velocity (residence time). Furthermore, the development of a reliable design tool for moving packed-bed heat exchangers must be validated by predicting experimental results in the operating regime of interest. An experimental system is designed to provide the data necessary for model validation and/or to identify where deficiencies or new constitutive relations are needed.
A linear dynamic model for a wave energy converter (WEC) has been developed based on the results of experimental wave tank testing. Based on this model, a model predictive control (MPC) strategy has been designed and implemented. To assess the performance of this control strategy, a deployment environment off the coast of Newport, OR has been selected and the controller has been used to simulate the WEC response in a set of irregular sea states. To better understand the influence of model accuracy on control performance, an uncertainty analysis has been performed by varying the parameters of the model used for the design of the controller (i.e. the control model), while keeping the WEC dynamic model employed in these simulations (i.e. the plant model) unaltered. The results of this study indicate a relative low sensitivity of the MPC control strategy to uncertainties in the controller model for the specific case studied here.
We consider heuristic and optimal solutions to a discrete geometric bin packing problem that arises in a resource allocation problem. An imaging sensor is assigned to collect data over a large area, but some subregions are more valuable than others. To capture these high-value regions with higher fidelity, we can assign some number of non-overlapping rectangular subsets, called “subfootprints.” The sensor image is partitioned into squares called “chips”, and each chip is further partitioned into pixels. Pixels may have different values. Subfootprints are restricted to rectangular collections of chips, but we are free to choose different rectangle heights, widths, and areas. We seek the optimal arrangement over the family of possible rectangle shapes and sizes. We provide a mixed-integer linear program optimization formulation, as well as a greedy heuristic, to solve this problem. For the meta-problem, we have some freedom to align the chip boundaries to different pixels. However, it is too expensive to solve the optimization formulation for each alignment. However, we show that the greedy heuristic can inform which pixel alignments are worth solving the optimization over. We use a variant of k-means clustering to group greedy solutions by their transport shape-similarity. For each cluster, we run the optimization problem over the greedy layout with the highest value. In practice this efficiently explores the geometric configuration space, and produces solutions close to the global optimum. We show a contrived example using surveillance of the Mississippi River. Our software is available as open-source in the Github repository “GeoPlace .
A detailed methodology was used to select the sea states tested in the final stage of the Wave Energy Prize (WEPrize), a public prize challenge sponsored by the U.S. Department of Energy [1]. The winner was selected based on two metrics: a threshold value expressing the benefit to effort ratio (ACE metric) and a second metric which included hydrodynamic performance-related quantities (HPQ). HPQ required additional sea states to query aspects of the techno-economic performance not addressed by ACE. Due to the nature of the WEPrize, limited time was allotted to each contestant for testing and thus a limitation on the total sea states was required. However, the applicability of these sea states was required to encompass seven deployment locations representative of the United States West Coast and Hawaii. A cluster analysis was applied to scatter diagrams in order to determine a subset of sea states that could be scaled to find the average annual power flux at each wave climate for the ACE metric. Four additional sea states were selected, including two highly energetic sea states and two bimodal sea states, to evaluate HPQ. These sea states offer a common experimental testing platform for performance in United States deployment climates.
Information loss from a computation implies energy dissipation due to Landauer’s Principle. Thus, increasing the amount of useful computational work that can be accomplished within a given energy budget will eventually require increasing the degree to which our computing technologies avoid information loss, i.e., are logically reversible. But the traditional definition of logical reversibility is actually more restrictive than is necessary to avoid information loss and energy dissipation due to Landauer’s Principle. As a result, the operations that have traditionally been viewed as the atomic elements of reversible logic, such as Toffoli gates, are not really the simplest primitives that one can use for the design of reversible hardware. Arguably, a complete theoretical framework for reversible computing should provide a more general, parsimonious foundation for practical engineering. To this end, we use a rigorous quantitative formulation of Landauer’s Principle to develop the theory of Generalized Reversible Computing (GRC), which precisely characterizes the minimum requirements for a computation to avoid information loss and the consequent energy dissipation, showing that a much broader range of computations are, in fact, reversible than is acknowledged by traditional reversible computing theory. This paper summarizes the foundations of GRC theory and briefly presents a few of its applications.
Water utilities are vulnerable to a wide variety of human-caused and natural disasters. The Water Network Tool for Resilience (WNTR) is a new open source Python™ package designed to help water utilities investigate resilience of water distribution systems to hazards and evaluate resilience-enhancing actions. In this paper, the WNTR modeling framework is presented and a case study is described that uses WNTR to simulate the effects of an earthquake on a water distribution system. The case study illustrates that the severity of damage is not only a function of system integrity and earthquake magnitude, but also of the available resources and repair strategies used to return the system to normal operating conditions. While earthquakes are particularly concerning since buried water distribution pipelines are highly susceptible to damage, the software framework can be applied to other types of hazards, including power outages and contamination incidents.
Computational imagers fundamentally enable new optical hardware through the use of both physical and algorithmic elements. We report on the creation of a static lensless computational imaging system enabled by this paradigm.
Robust, safe, and reliable grid-scale energy storage continues to be a priority for improved energy surety, expanded integration of renewable energy, and greater system agility required to meet modern dynamic and evolving electrical energy demands. We describe here a new sodium-based battery based on a molten sodium anode, a sodium iodide/aluminum chloride (NaI/AlCl3) cathode, and a high conductivity NaSICON (Na1+xZr2SixP3−xO12) ceramic separator. This NaI battery operates at intermediate temperatures (120–180 °C) and boasts an energy density of >150 Wh kg−1. The energy-dense NaI-AlCl3 ionic liquid catholyte avoids lifetime-limiting plating and intercalation reactions, and the use of earth-abundant elements minimizes materials costs and eliminates economic uncertainties associated with lithium metal. Moreover, the inherent safety of this system under internal mechanical failure is characterized by negligible heat or gas production and benign reaction products (Al, NaCl). Scalability in design is exemplified through evolution from 0.85 to 10 Ah (28 Wh) form factors, displaying lifetime average Coulombic efficiencies of 99.45% and energy efficiencies of 81.96% over dynamic testing lasting >3000 h. This demonstration promises a safe, cost-effective, and long-lifetime technology as an attractive candidate for grid scale storage.
Children with autism spectrum disorders (ASD) and their unaffected siblings (US) are frequent targets of social bullying, which leads to severe physical, emotional, and social consequences. Understanding the risk factors is essential for developing preventative measures. We suggest that one such risk factor may be a difficulty to discriminate different biological body movements (BBM), a task that requires fast and flexible processing and interpretation of complex visual cues, especially during social interactions. Deficits in cognition of BBM have been reported in ASD. Since US display an autism endophenotype we expect that they will also display deficits in social interpretation of BBM. Methods. Participants: 8 US, 8 matched TD children, age 7-14; Tasks/Measurements: Social Blue Man Task: Narrative interpretation with a Latent Dirichlet Allocation [LDA] analysis; Social Experience Questionnaires with children and parents. Results. The US displayed as compared to TD: (i) low self-awareness of social bullying in contrast to high parental reports; (ii) reduced speed in identifying social cues; (iii) lower quality and repetitious wording in social interaction narratives (LDA). Conclusions. US demonstrate social endophenotype of autism reflected in delayed identification, interpretation and verbalization of social cues; these may constitute a high risk factor for becoming a victim of social bullying.
We propose a new post-processing procedure for automatically adjusting node locations of an all-hex mesh to better match the volume of a reference geometry. Hexahedral meshes generated via an overlay grid procedure, where a precise reference geometry representation is unknown or is impractical to use, do not provide for precise volumetric preservation. A discrete volume fraction representation of the reference geometry MI on an overlay grid is compared with a volume fraction representation of a 3D finite element mesh MO. This work proposes a procedure that uses the localized discrepancy between MI and MO to drive node relocation operations to more accurately match a reference geometry. We demonstrate this procedure on a wide range of hexahedral meshes generated with the Sculpt code and show improved volumetric preservation while still maintaining acceptable mesh quality.
We report on the design of a refracting prism array element for use in a computational lensless imaging system. The technique discussed enables creation of a refracting element that maximizes signal on a detector region.
The modeling and simulation of non-traditional imaging systems require holistic consideration of the end-to-end system. We demonstrate this approach through a tolerance analysis of a random scattering lensless imaging system.
The modeling and simulation of non-traditional imaging systems require holistic consideration of the end-to-end system. We demonstrate this approach through a tolerance analysis of a random scattering lensless imaging system.
Data visualizations are used to communicate information to people in a wide variety of contexts, but few tools are available to help visualization designers evaluate the effectiveness of their designs. Visual saliency maps that predict which regions of an image are likely to draw the viewer’s attention could be a useful evaluation tool, but existing models of visual saliency often make poor predictions for abstract data visualizations. These models do not take into account the importance of features like text in visualizations, which may lead to inaccurate saliency maps. In this paper we use data from two eye tracking experiments to investigate attention to text in data visualizations. The data sets were collected under two different task conditions: a memory task and a free viewing task. Across both tasks, the text elements in the visualizations consistently drew attention, especially during early stages of viewing. These findings highlight the need to incorporate additional features into saliency models that will be applied to visualizations.