Publications

Laser engineered net shaping (LENS) is an additive manufacturing process that presents a promising method of creating or repairing metal parts not previously feasible with traditional manufacturing methods. The LENS process involves the directed deposition of metal via a laser power source and a spray of metal powder co-located to create and feed a molten pool (also referred to generically as Directed Energy Deposition, DED). DED technologies are being developed for use in prototyping, repair, and manufacturing across a wide variety of materials including stainless steel, titanium, tungsten carbidecobalt, aluminum, and nickel based superalloys. However, barriers to the successful production and qualification of LENS produced or repaired parts remain. This work proposes a finite element (FE) analysis methodology capable of simulating the LENS process at the continuum length scale (i.e. part length scale). This method incorporates an element activation scheme wherein only elements that exceed the material melt temperature during laser heating are activated and carried through to subsequent analysis steps. Following the initial element activation calculation, newly deposited, or activated elements and the associated geometry, are carried through to thermal and mechanical analyses to calculate heat flow due to radiation, convection, and conduction as well as stresses and displacements. The final aim of this work is to develop a validated LENS process simulation capability that can accurately predict temperature history, final part shape, distribution of strength, microstructural properties, and residual stresses based on LENS process parameters.

Lensless imaging systems have the potential to provide new capabilities for lower size and weight configuration than traditional imaging systems. Lensless imagers frequently utilize computational imaging techniques, which moves the complexity of the system away from optical subcomponents and into a calibration process whereby the measurement matrix is estimated. We report on the design, simulation, and prototyping of a lensless imaging system that utilizes a 3D printed optically transparent random scattering element. Development of end-to-end system simulations, which includes simulations of the calibration process, as well as the data processing algorithm used to generate an image from the raw data are presented. These simulations utilize GPU-based raytracing software, and parallelized minimization algorithms to bring complete system simulation times down to the order of seconds. Hardware prototype results are presented, and practical lessons such as the effect of sensor noise on reconstructed image quality are discussed. System performance metrics are proposed and evaluated to discuss image quality in a manner that is relatable to traditional image quality metrics. Various hardware instantiations are discussed.

We show how to place a set of seed points such that a given piecewise linear complex is the union of some faces in the resulting Voronoi diagram. The seeds are placed on sufficiently small spheres centered at input vertices and are arranged into little circles around each half-edge where every seed is mirrored across the associated triangle. The Voronoi faces common to the seeds of such arrangements yield a mesh conforming to the input complex. If the input contains sharp angles, then additional seeds are needed, analogous to nonobtuse refinement. Finally, we propose local optimizations to reduce the number of seeds and output facets.

Microwave spectroscopy probes the rotational transitions of polar molecules in the gas phase and is a proven technique for the detection and identification of short-lived molecules produced from a variety of molecular sources. In this explorative study, we demonstrate that two prerequisites can be met for microwave spectroscopy to become a quantitative tool for the analysis of high-temperature gas mixtures as found in combustion environments. First, we show that the rotational temperature of the targeted species can be sufficiently cooled to allow for a sensitive detection of low-lying rotational states after sampling from hot (∼2200 K) flames. Second, we show that signal intensity profiles can be assembled which, after correcting for the different flame temperatures at various sampling positions, agree well with mole fraction profiles obtained via flame-sampling molecular-beam mass spectrometry. Based on the described results, it is conceivable that rotational spectroscopy can contribute towards the unraveling of complex, high-temperature reaction networks.

In this work we extend compression-based algorithms for deception detection in text. In contrast to approaches that rely on theories for deception to identify feature sets, compression automatically identifies the most significant features. We consider two datasets that allow us to explore deception in opinion (content) and deception in identity (stylometry). Our first approach is to use unsupervised clustering based on a normalized compression distance (NCD) between documents. Our second approach is to use Prediction by Partial Matching (PPM) to train a classifier with conditional probabilities from labeled documents, followed by arithmetic coding (AC) to classify an unknown document based on which label gives the best compression. We find a significant dependence of the classifier on the relative volume of training data used to build the conditional probability distributions of the different labels. Methods are demonstrated to overcome the data size-dependence when analytics, not information transfer, is the goal. Our results indicate that deceptive text contains structure statistically distinct from truthful text, and that this structure can be automatically detected using compression-based algorithms.

Lithium-ion battery electrodes are composed of active material particles, binder, and conductive additives that form an electrolyte-filled porous particle composite. The mesoscale (particle-scale) interplay of electrochemistry, mechanical deformation, and transport through this tortuous multi-component network dictates the performance of a battery at the cell-level. Effective electrode properties connect mesoscale phenomena with computationally feasible battery-scale simulations. We utilize published tomography data to reconstruct a large subsection (1000+ particles) of an NMC333 cathode into a computational mesh and extract electrode-scale effective properties from finite element continuum-scale simulations. We present a novel method to preferentially place a composite binder phase throughout the mesostructure, a necessary approach due difficulty distinguishing between non-active phases in tomographic data. We compare stress generation and effective thermal, electrical, and ionic conductivities across several binder placement approaches. Isotropic lithiation-dependent mechanical swelling of the NMC particles and the consideration of strain-dependent composite binder conductivity significantly impact the resulting effective property trends and stresses generated. Our results suggest that composite binder location significantly affects mesoscale behavior, indicating that a binder coating on active particles is not sufficient and that more accurate approaches should be used when calculating effective properties that will inform battery-scale models in this inherently multi-scale battery simulation challenge.

Optimizing communication performance is imperative for largescale computing because communication overheads limit the strong scalability of parallel applications. Today's network cards contain rather powerful processors optimized for data movement. However, these devices are limited to fixed functions, such as remote direct memory access. We develop sPIN, a portable programming model to offload simple packet processing functions to the network card. To demonstrate the potential of the model, we design a cycle-accurate simulation environment by combining the network simulator LogGOPSim and the CPU simulator gem5. We implement offloaded message matching, datatype processing, and collective communications and demonstrate transparent full-application speedups. Furthermore, we show how sPIN can be used to accelerate redundant in-memory filesystems and several other use cases. Our work investigates a portable packet-processing network acceleration model similar to compute acceleration with CUDA or OpenCL. We show how such network acceleration enables an eco-system that can significantly speed up applications and system services.

Structural dynamics models with localized nonlinearities can be reduced using Hurty/Craig-Bampton component mode synthesis methods. The interior degrees-of-freedom of the linear subcomponents are reduced with a set of dynamic fixedinterface modes while the static constraint modes preserve the physical coordinates at which the nonlinear restoring forces are applied. For finite element models with a highly refined mesh at the boundary, a secondary modal analysis can be performed to reduce the interface down to a truncated set of local-level characteristic constraint modes. In this research, the cost savings and accuracy of the interface reduction technique are evaluated on a simple example problem involving two elastic blocks coming into contact.

The rapid reaction of the smallest Criegee intermediate, CH2OO, with water dimers is the dominant removal mechanism for CH2OO in the Earth's atmosphere, but its products are not well understood. This reaction was recently suggested as a significant source of the most abundant tropospheric organic acid, formic acid (HCOOH), which is consistently underpredicted by atmospheric models. However, using time-resolved measurements of reaction kinetics by UV absorption and product analysis by photoionization mass spectrometry, we show that the primary products of this reaction are formaldehyde and hydroxymethyl hydroperoxide (HMHP), with direct HCOOH yields of less than 10%. Incorporating our results into a global chemistry-transport model further reduces HCOOH levels by 10-90%, relative to previous modeling assumptions, which indicates that the reaction CH2OO + water dimer by itself cannot resolve the discrepancy between the measured and predicted HCOOH levels.

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.

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.

Neodymium hydroxide, Nd(OH)3, solubility experiments were carried out in duplicate at room temperature over the pH interval of 10 to 13 for up to 670 days. The ionic radii of Nd(III) is similar to that of Pu(III) and Am(III), so that the former is an appropriate analog for the latter radionuclides. Average concentrations of Nd in solution approach a value of 2.0 × 10-7 mol/L and equilibrium concentrations show no dependence on solution pH. Compared to previous work, the data from this investigation form a continuum across pH-space, indicating agreement amongst data sets.

Industry's inability to reduce logic gates' energy consumption is slowing growth in an important part of the worldwide economy. Some scientists argue that alternative approaches could greatly reduce energy consumption. These approaches entail myriad technical and political issues.

The performance of many of the technologies used in physical protection systems that guard high-value assets are heavily influenced by weather and visibility conditions as well as intruder capabilities. This complicates the already difficult problem of optimizing the design of multi-layered physical protection systems. This paper develops an optimization model for the automatic design of these systems with explicit consideration of the impact of weather and visibility conditions as well as intruder capabilities on system performance. An illustrative case study is provided.

Approximate methods for electronic structure, implemented in sophisticated computer codes and married to ever-more powerful computing platforms, have become invaluable in chemistry and materials science. The maturing and consolidation of quantum chemistry codes since the 1980s, based upon explicitly correlated electronic wave functions, has made them a staple of modern molecular chemistry. Here, the impact of first principles electronic structure in physics and materials science had lagged owing to the extra formal and computational demands of bulk calculations.

Although many optical-quality glass materials are available for use in optical systems, the range of polymeric materials is limited. Polymeric materials have some advantages over glass when it comes to large-scale manufacturing and production. In smaller scale systems, they offer a reduction in weight when compared to glass counterparts. This is especially important when designing optical systems meant to be carried by hand. We aimed to expand the availability of polymeric materials by exploring both crown-like and flint-like polymers. In addition, rapid and facile production was also a goal. By using UV-cured thiolene-based polymers, we were able to produce optical materials within seconds. This enabled the rapid screening of a variety of polymers from which we down-selected to produce optical flats and lenses. We will discuss problems with production and mitigation strategies in using UV-cured polymers for optical components. Using UV-cured polymers present a different set of problems than traditional injection-molded polymers, and these issues are discussed in detail. Using these produced optics, we integrated them into a modified direct view optical system, with the end goal being the development of drop-in replacements for glass components. This optical production strategy shows promise for use in lab-scale systems, where low-cost methods and flexibility are of paramount importance.

Steel grades such as A572 and AISI 4140 are often used for applications where high rate or impact loading may occur. A572 is a hot-rolled carbon steel that is used where a high strength to weight ratio is desired. A grade such as AISI 4140 offers decent corrosion resistance due to higher chromium and molybdenum content and is commonly used in firearm parts, pressurized gas tubes, and structural tubing for roll cages. In these scenarios, the material may undergo high rate loading. Thus, material properties including failure and fracture response at relevant loading rates must be understood so that numerical simulations of impact events accurately capture the deformation and failure/fracture behavior of the involved materials. In this study, the high strain rate tensile response of A572 and 4140 steel are investigated. An increase in yield strength of approximately 28% was observed for 4140 steel when comparing 0.001 s-1 strain rate to 3000 s-1 experiments. A572 showed an increase in yield strength of approximately 52% when the strain rate increased from quasi-static to 2750 s-1. Effects on true stress and strain at failure for the two materials are also discussed.

Low carbon, high strength steel alloys such as Vascomax steels are used in a wide variety of extreme environments due to their high strength, high fracture toughness, and stability over a wide range of temperatures. In this study, Vascomax® C250 steel was dynamically characterized in compression using Kolsky compression bar techniques at two strain rates of 1000 and 3000 s-1. A pair of impedance-matched tungsten carbide platens were implemented to protect damage to the bar ends. The tungsten carbide platens were experimentally calibrated as system compliance which was then properly corrected for actual specimen strain measurements. In addition, elastic indentation of the high-strength compression sample into the platens was also evaluated and showed negligible effect on the specimen strain measurements. The Vascomax® C250 steel exhibited strain-rate effects on the compressive stress-strain curves. The dynamic yield strength was approximately 18% higher than quasi-static yield strength obtained from hardness tests. The dynamic true stress-strain curves of the Vascomax® C250 steel in compression were also computed and then compared with the previously obtained true tensile stress-strain curves at the same strain rates. The Vascomax® C250 steel exhibited a reasonable symmetry in dynamic compression and tensile stress-strain response. However, the fracture strains in dynamic compression were smaller than those in dynamic tension probably due to different fracture mechanisms in the different loading modes.

We present a new, non-destructive electrical technique, Power Spectrum Analysis (PSA). PSA as described here uses off-normal biasing, an unconventional way of powering microelectronics devices. PSA with off-normal biasing can be used to detect subtle differences between microelectronic devices. These differences, in many cases, cannot be detected by conventional electrical testing. In this paper, we highlight PSA applications related to aging and counterfeit detection.

Researchers are now considering alternatives to the von Neumann computer architecture as a way to improve performance. The current approach of simulating benchmark applications favors continued use of the von Neumann architecture, but architects can help overcome this bias.

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.

Rather than continue the expensive and time-consuming quest for transistor replacement, the authors argue that 3D chips coupled with new computer architectures can keep Moore's law on its traditional scaling path.

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.

In this work we extend compression-based algorithms for deception detection in text. In contrast to approaches that rely on theories for deception to identify feature sets, compression automatically identifies the most significant features. We consider two datasets that allow us to explore deception in opinion (content) and deception in identity (stylometry). Our first approach is to use unsupervised clustering based on a normalized compression distance (NCD) between documents. Our second approach is to use Prediction by Partial Matching (PPM) to train a classifier with conditional probabilities from labeled documents, followed by arithmetic coding (AC) to classify an unknown document based on which label gives the best compression. We find a significant dependence of the classifier on the relative volume of training data used to build the conditional probability distributions of the different labels. Methods are demonstrated to overcome the data size-dependence when analytics, not information transfer, is the goal. Our results indicate that deceptive text contains structure statistically distinct from truthful text, and that this structure can be automatically detected using compression-based algorithms.

Many applications, such as PDE based simulations and machine learning, apply BLAS/LAPACK routines to large groups of small matrices. While existing batched BLAS APIs provide meaningful speedup for this problem type, a non-canonical data layout enabling cross-matrix vectorization may provide further significant speedup. In this paper, we propose a new compact data layout that interleaves matrices in blocks according to the SIMD vector length. We combine this compact data layout with a new interface to BLAS/LAPACK routines that can be used within a hierarchical parallel application. Our layout provides up to 14 ×, 45 ×, and 27 × speedup against OpenMP loops around optimized DGEMM, DTRSM and DGETRF kernels, respectively, on the Intel Knights Landing architecture. We discuss the compact batched BLAS/LAPACK implementations in two libraries, KokkosKernels and Intel® Math Kernel Library. We demonstrate the APIs in a line solver for coupled PDEs. Finally, we present detailed performance analysis of our kernels.

Fundamental engine research is primarily conducted under steady-state conditions, in order to better describe boundary conditions which influence the studied phenomena. However, light-duty automobiles are operated, and tested, under heavily transient conditions. This mismatch between studied conditions and in-use conditions is deemed acceptable due to the fundamental knowledge gained from steady-state experiments. Nonetheless, it is useful to characterize the conditions encountered during transient operation and determine if the governing phenomena are unduly influenced by the differences between steady-state and transient operation, and further, whether transient behavior can be reasonably extrapolated from steady-state behavior. The transient operation mode used in this study consists of 20 fired cycles followed by 80 motored cycles, operating on a continuous basis. The intention of the cycle is to provide a significant transient condition, namely the change from motored to knock-limited fired operation, while also maintaining a repeatable cycle that allows for the collection of statistics during quasi- steady-state operation. This study investigates the effect of transient operation on Knock-Limited Combustion Phasing (KL-CA50) compared to steady-state operation. Three compositionally dissimilar matched Research Octane Number (RON) = 98 fuels are used in this study, allowing for the assessment of fuel-specific effects on differences between steady-state and transient operation. This study first characterizes the 20/80 firing cycle described above, before comparing the transient KL-CA50 measurements to the steady-state KL-CA50 measurements. Analysis of both the steady-state and transient results are used to gain insights into the effects of transient operation on end-gas autoignition, relative to steady-state operation and as a function of fuel composition. The results of this study indicate the significant effect that transient operation has on KL-CA50 behavior of a fuel. This is both universal, in that all fuels show responses to the differences in compression temperatures of the charge, as well as fuel specific, in that the fuel response varies based on the fuel's sensitivity to temperature, [O2], and trace species. All fuels showed a significant load extension under transient operation, based on tolerance of higher intake pressures. However, transient operation moved operating conditions to "beyond RON" (Octane Index K < 0) conditions, which favored higher-sensitivity fuels. Based on the analysis of system time constants (e.g. cylinder head temperature dynamic response, exhaust gas temperature dynamic response), it is expected that transient operation, and the benefits for knock-limited operation, are highly influential on drive-cycle performance.

AlGaN-channel high electron mobility transistors (HEMTs) are among a class of ultra wide-bandgap transistors that have a bandgap greater than ∼3.4 eV, beyond that of GaN and SiC, and are promising candidates for RF and power applications. Long-channel AlxGa1-xN HEMTs with x = 0.3 in the channel have been built and evaluated across the −50◦C to +200◦C temperature range. Room temperature drain current of 70 mA/mm, absent of gate leakage, and with a modest −1.3 V threshold voltage was measured. A very large Ion/Ioff current ratio, greater than 108 was demonstrated over the entire temperature range, indicating that off-state leakage is below the measurement limit even at 200◦C. Combined with near ideal subthreshold slope factor that is just 1.3× higher than the theoretical limit across the temperature range, the excellent leakage properties are an attractive characteristic for high temperature operation.

This work identifies classes of cool flame intermediates from nheptane low-temperature oxidation (e.g., < 750 K) in a jet-stirred reactor (JSR) and a cooperative fuel research (CFR) engine. The sampled species from the JSR were analyzed using a synchrotron vacuum ultraviolet radiation photoionization time-of-flight molecular-beam mass spectrometer and an atmospheric pressure chemical ionization orbitrap mass spectrometer; the latter was also used to analyze the sampled species from the CFR engine. The products can be classified by species with molecular formulas of C7H14Ox (x=0-5), C7H12Ox (x=0-4), C7H10Ox (x=0-4), CnH2n (n=2-6), CnH2n-2 (n=4-6), CnH2n+2O (n=1-4, 6), CnH2nO (n=1-6), CnH2n-2O (n=2-6), CnH2n-4O (n=4-6), CnH2n+2O2 (n=0-4, 7), CnH2nO2 (n=1-6), CnH2n-2O2 (n=2-6), CnH2n-4O2 (n=4-7), and CnH2nO3 (n=3-6). The identified intermediate species include mainly alkene, dienes, aldehyde/keto compounds, olefinic aldehyde/keto compounds, diones, cyclic ethers, peroxides, acids, and alcohols/ethers. Reaction pathways forming intermediates with the same carbon number as n-heptane are proposed and discussed. These experimental results should be helpful in the development of kinetic models for n-heptane and longer-chain alkanes.

Rechargeable alkaline Zn/MnO2 batteries are being developed for use as cost-effective grid-scale energy storage devices. Previous studies have shown that limiting the depth of discharge (DOD) of the MnO2 cathode extends cell lifetime while still providing a cost-effective battery system. Herein, a comprehensive study of triethanolamine (TEA) as an additive in Zn/MnO2 limited DOD batteries is provided by examining the effect of TEA in full cells as well as independently on the cathode, anode, separator, and electrolyte. Improvement in cycle-ability of the cathode (on average, 80% of cycled capacity remains after 191 cycles without TEA, 568 cycles with TEA) and a decrease in ionic zinc mobility across Celgard 3501 (7.91 × 10-5 cm2/min without TEA, 3.56 × 10-5 cm2/min with TEA) and Cellophane 350P00 (3.26 × 10-5 cm2/min without TEA, 4.74 × 10-6 cm2/min with TEA) separators upon the addition of TEA are demonstrated. However, TEA increased both the reduction potential of Zn (-0.68 V vs. Hg/HgO without TEA, -0.76 V with TEA) and the solubility of Zn2+ (0.813 M without TEA, 1.023 M with TEA). Overall, the addition of TEA extended the lifetime of limited DOD cells on average by 297%.

Designers of direct-injection compression-ignition engines use a variety of strategies to improve the fuel/charge-gas mixture within the combustion chamber for increased efficiency and reduced pollutant emissions. Strategies include the use of high fuel-injection pressures, multiple injections, small injector orifices, flow swirl, long-ignition-delay conditions, and oxygenated fuels. This is the first journal publication on a new mixing-enhancement strategy for emissions reduction: ducted fuel injection. The concept involves injecting fuel along the axis of a small cylindrical duct within the combustion chamber, to enhance the mixture in the autoignition zone relative to a conventional free-spray configuration (i.e., a fuel spray that is not surrounded by a duct). The results described herein, from initial proof-of-concept experiments conducted in a constant-volume combustion vessel, show dramatically lower soot incandescence from ducted fuel injection than from free sprays over a range of charge-gas conditions that are representative of those in modern direct-injection compression-ignition engines.

Dissolved polysulfides, formed during Li-S battery operation, freely migrate and react with both the Li anode and the sulfur cathode. These soluble polysulfides shuttle between the anode and cathode – the so-called shuttle effect – resulting in an infinite recharge process and poor Columbic efficiency. In this study, water present as an additive in the Li-S battery electrolyte is found to reduce the shuttle effect in Li-S batteries. Batteries where water content was below 50 ppm exhibited a substantial shuttle effect and low charge capacity. Alternatively, addition of 250 ppm water led to stable charge/discharge behavior with high Coulombic efficiency. XPS results show that H2O addition results in the formation of solid electrolyte interphase (SEI) film with more LiOH on Li anode which protects the Li anode from the polysulfides. Batteries cycled without water result in a SEI film with more Li2CO3 likely formed by direct contact between the Li metal and the solvent. Intermediate quantities of H2O in the electrolyte result in high cycle efficiency for the first few cycles which then rapidly decays. This suggests that H2O is consumed during battery cycling, likely by interaction with freshly exposed Li metal formed during Li deposition.

Whilst the physics of both classical evaporation and supercritical fluid mixing are reasonably well characterized and understood in isolation, little is known about the transition from one to the other in the context of liquid fuel systems. The lack of experimental data for microscopic droplets at realistic operating conditions impedes the development of phenomenological and numerical models. To address this issue we performed systematic measurements using high-speed long-distance microscopy, for three single-component fuels (n-heptane, n-dodecane, n-hexadecane), into gas at elevated temperatures (700–1200 K) and pressures (2–11 MPa). We describe these high-speed visualizations and the time evolution of the transition from liquid droplet to fuel vapour at the microscopic level. The measurements show that the classical atomization and vaporisation processes do shift to one where surface tension forces diminish with increasing pressure and temperature, but the transition to diffusive mixing does not occur instantaneously when the fuel enters the chamber. Rather, subcritical liquid structures exhibit surface tension in the near-nozzle region and then, after time surrounded by the hot ambient gas and fuel vapour, undergo a transition to a dense miscible fluid. Although there was clear evidence of surface tension and primary atomization for n-dodecane and n-hexadecane for a period of time at all the above conditions, n-heptane appeared to produce a supercritical fluid from the nozzle outlet when injected at the most elevated conditions (1200 K, 10 MPa). This demonstrates that the time taken by a droplet to transition to diffusive mixing depends on the pressure and temperature of the gas surrounding the droplet as well as the fuel properties. We summarise our observations into a phenomenological model which describes the morphological evolution and transition of microscopic droplets from classical evaporation through a transitional mixing regime and towards diffusive mixing, as a function of operating conditions. We provide criteria for these regime transitions as reduced pressure–temperature correlations, revealing the conditions where transcritical mixing is important to diesel fuel spray mixing.

Sandia National Laboratories and Heat Pipes Laboratory of National Technical University of Ukraine «KPI» have developed several methods of improving robustness of the high-temperature heat pipe wick for their application to concentrating solar power systems with Stirling engine. In this case the wick structures must retain high heat pipe performance with robustness for long-term operation. Recent modeling indicates that wicks based on various fiber combinations could provide the robustness combined with sufficient performance. Results of the development, characterization, modeling, and testing of advanced felt metal wicks that addresses durability issues while maintaining sufficient performance are showed in the paper. The project resulted in an ongoing durability bench-scale heat pipe that simulates wick load conditions required for 80kWth throughput solar receiver, including periodic non-destructive evaluation of the wick durability. Two mock-ups of high-temperature heat pipes were made for long life and performance tests: the first sample with wick based on 12 μm fibers; and the second with hybrid wick based on 30 μm fibers and 6.5 μm fibers. The second heat pipe operation has continued unattended at 775 °C vapor temperature for nearly 13,600 h, with no observable loss of performance or change in startup characteristics.

Ignitability is important to characterize pulverized coal combustion, as it is directly related to flame stability. The current work describes a practical test rig for rapid laboratory analysis of pulverized coal cloud ignition properties. The system has been designed for conventional coal combustion conditions using air as the oxidant. In the current work, the measurement principle of the device is described and its adaption to and applicability for oxy-fuel combustion tests is demonstrated. Four coals with different rank were measured in air and in oxy-fuel atmospheres containing 20–35 vol% O2 in CO2. The major influencing factors for the investigated samples were found to be the coal rank and the gas-phase oxygen concentration, while a minor influence of particle size was observed.

Particle accelerators play a key role in a broad set of defense and security applications, including war-fighter and asset protection, cargo inspection, nonproliferation, materials characterization, and stockpile stewardship. Accelerators can replace the high activity radioactive sources that pose a security threat to developing a radiological dispersal device, and, can be used to produce isotopes for medical, industrial, and research purposes. An overview of current and emerging accelerator technologies relevant to addressing the needs of defense and security is presented.

A non-premixed coannular burner in which oxygen concentrations and oxidizer flow rates can be independently varied was developed to investigate the effects of turbulent mixing intensity from oxygen enrichment on soot formation and flame radiation. Local radiation intensities soot concentrations and soot temperatures were measured using a thin-film thermopile planar laser-induced incandescence and two-color imaging pyrometry respectively. The measurements showed that soot formation increased as the oxygen concentration decreases from 100% to 50% helping to moderate a decrease in overall flame radiation. An increase in turbulence intensity had a remarkable effect on flame height soot formation and thermal radiation resulting to decreases in all of these parameters. The soot temperature decreased with a decrease in the oxygen concentration and increased with an increase in turbulent mixing intensity. Thus properly designed oxygen-enriched burners that enhance soot formation for intermediate levels of oxygen purity may be able to achieve thermal radiation intensities as high as 85% of traditional oxy-fuel burners utilizing high-purity oxygen.

Optical coatings with the highest laser damage thresholds rely on clean conditions in the vacuum chamber during the coating deposition process. A low-base pressure in the coating chamber, as well as the ability of the vacuum system to maintain the required pressure during deposition, are important aspects of limiting the amount of defects in an optical coating that could induce laser damage. Our large optics coating chamber at Sandia National Laboratories normally relies on three cryo pumps to maintain low pressures for e-beam coating processes. However, on occasion, one or more of the cryo pumps have been out of commission. In light of this circumstance, we explored how deposition under compromised vacuum conditions resulting from the use of only one or two cryo pumps affects the laser-induced damage thresholds of optical coatings. The coatings of this study consist of HfO2 and SiO2 layer materials and include antireflection coatings for 527 nm at normal incidence and high-reflection coatings for 527 nm at 45-deg angle of incidence in P-polarization.

We present a new meshless method for scalar diffusion equations, which is motivated by their compatible discretizations on primal-dual grids. Unlike the latter though, our approach is truly meshless because it only requires the graph of nearby neighbor connectivity of the discretization points xi. This graph defines a local primal-dual grid complex with a virtual dual grid, in the sense that specification of the dual metric attributes is implicit in the method's construction. Our method combines a topological gradient operator on the local primal grid with a generalized moving least squares approximation of the divergence on the local dual grid. We show that the resulting approximation of the div-grad operator maintains polynomial reproduction to arbitrary orders and yields a meshless method, which attains O(hm) convergence in both L2- and H1-norms, similar to mixed finite element methods. We demonstrate this convergence on curvilinear domains using manufactured solutions in two and three dimensions. Application of the new method to problems with discontinuous coefficients reveals solutions that are qualitatively similar to those of compatible mesh-based discretizations.

Li-air or Li-oxygen batteries promise significantly higher energies than existing commercial battery technologies, yet their development has been hindered by a lack of suitable electrolytes. In this article, we evaluate the physical properties of varied electrolyte compositions to form generalized criteria for electrolyte design. We show that oxygen transport through non-aqueous electrolytes has a critical impact on the discharge rate and capacity of Li-air batteries. Through experiments and molecular dynamics simulations, we highlight that the choice of salt species and concentration have an outsized influence on oxygen solubility, while solvent choice is the major influence on oxygen diffusivity. The stability of superoxide reaction intermediates, key to the oxygen reduction mechanism, is also affected by variations in salt concentration and the choice of solvent. The importance of reactant transport is confirmed through Li-air cell discharge, which demonstrates good agreement between the observed and calculated mass transport-limited currents. These results showcase the impact of electrolyte composition on transport in metal-air batteries and provide guiding principles and simulation-based tools for future electrolyte design.

A “good” speckle pattern enables DIC to make its full-field measurements, but oftentimes this artistic part of the DIC setup takes a considerable amount of time to develop and evaluate for a given optical configuration. A catalog of well-quantified speckle patterns for various fields of view would greatly decrease the time it would take to start making DIC measurements. The purpose of this speckle patterning study is to evaluate various speckling techniques we had readily available in our laboratories for fields of view from around 100 mm down to 5 mm that are common for laboratory-scale experiments. The list of speckling techniques is not exhaustive: spray painting, UV-printing of computer-designed speckle patterns, airbrushing, and particle dispersion. First, we quantified the resolution of our optical configurations for each of the fields of view to determine the smallest speckle we could resolve. Second, we imaged several speckle patterns at each field of view. Third, we quantified the average and standard deviation of the speckle size, speckle contrast, and density to characterize the quality of the speckle pattern. Finally, we performed computer-aided sub-pixel translation of the speckle patterns and ran correlations to examine how well DIC tracked the pattern translations. We discuss our metrics for a “good” speckle pattern and outline how others may perform similar studies for their desired optical configurations.

The breakup of liquid drops is an important phenomenology for many applications. We approach this problem with the objective to improve methods for handling the modeling of the impulse and impact dispersal of liquids in transportation accident scenarios. These scenarios can be distinguished from many other simpler problems, due to the quantity of liquid and the complexity of the intermediate liquid morphology. These differences necessitate alternative approaches to the problem. We have recently implemented a model for inter-particle forces between particles in a Lagrangian/Eulerian CFD code. The inter-particle force model is inspired by molecular dynamics methods, and employs a Lennard-Jones (LJ) attractive force and a spring-based repulsive force. The LJ parameters are related to the bulk fluid properties through a theoretical relationship model. Methods are necessary for modifying the single particle aerodynamic drag term, depending on the new notion of particle connectivity. We want to evaluate these methods for potential utilization in practical simulations. Classical breakup tests for drops in flows suggest a critical Weber number relating to the onset of breakup for a drop. We seek to replicate these data with our model methods as a preliminary step before deploying the method in larger scale practical environments.

Many engineering design problems can be formulated in the framework of partial differential equation (PDE) constrained optimization. The discretization of a PDE leads to multiple levels of resolution with varying degrees of numerical solution accuracy. Coarse discretizations require less computational time at the expense of increased error. Often there are also reduced fidelity models available, with simplifications to the physics models that are computationally easier to solve. This research develops an up to second-order consistent multilevel-multifidelity (MLMF) optimization scheme that exploits the reduced cost resulting from coarse discretization and reduced fidelity to more efficiently converge to the optimum of a fine-grid high-fidelity problem. This scheme distinguishes multilevel approaches applied to discretizations from multifidelity approaches applied to model forms, and navigates both hierarchies to accelerate convergence. Additive, multiplicative, or a combination of both corrections can be applied to the sub-problems to enforce up to second-order consistency with the fine-grid high-fidelity results. The MLMF optimization algorithm is a wrapper around a subproblem optimization solver, and the MLMF scheme is provably convergent if the subproblem optimizer is provably convergent. Heuristics are developed for efficiently tuning optimization tolerances and iterations at each level and fidelity based on relative solution cost. Accelerated convergence is demonstrated for a simple one-dimensional problem and aerodynamic shape optimization of a transonic airfoil.

Vibration and shock qualification testing of components can be an expensive and time-consuming process. If the component is small, often two or more units can be mounted on a fixture and tested simultaneously to reduce test time. There is an inherent danger in simultaneously testing two or more identical components as the fundamental natural frequencies and mode shapes of the individual components will be nearly identical with some slight variation due to manufacturing variability. Testing in this manner can create a situation where closely spaced vibration modes produce unwanted interference between the two units under test. This phenomenon could result in a case where one unit is over-tested while the other is under-tested. This paper presents some experimental results from simultaneously testing pairs of components which show distinct interference between the units. Some analysis will also be presented showing how variations in the components can alter the intended test response, potentially impacting component qualification.

Thin beams and panels subjected to large loadings will behave nonlinearly due to membrane stretch effects as they approach deflections on the order of their thickness; this behavior can be efficiently and accurately modeled using nonlinear reduced order models based on the structure’s linear normal modes. However, the complexity of such reduced order models grows cubically with the number of linear modes in the basis set, making complicated geometries prohibitively expensive to compute. Component mode synthesis techniques may be used to reduce this cost by assembling a set of smaller nonlinear subcomponent models, each of which can be more quickly computed than a nonlinear model of the entire structure. Since geometric nonlinearity is heavily dependent on each structure’s boundary conditions, however, subcomponents of an assembly which are constrained only at their interfaces – such as panels mounted to an underlying frame – prove difficult to treat using existing nonlinear modeling techniques. This work uses Craig-Bampton dynamic substructuring combined with characteristic constraint modes for interface reduction to examine the challenges associated with panel and frame assemblies, with a simple example motivating a discussion of current solutions and future challenges.

Linear structural dynamic models are often used to support system design and qualification. Overall, linear models provide an efficient means for conducting design studies and augmenting test data by recovering un-instrumented or unmeasurable quantities (e.g. stress). Nevertheless, the use of linear models often adds significant conservatism in design and qualification programs by failing to capture critical mechanisms for energy dissipation. Unfortunately, the use of explicit nonlinear models can require unacceptably large efforts in model development and experimental characterization to account for common nonlinearities such as frictional interfaces, macro-slip, and other complex material behavior. The computational requirements are also greater by orders of magnitude. Conversely, modal models are much more computationally efficient and experimentally have shown the ability to capture typical structural nonlinearity. Thus, this work will seek to use modal nonlinear identification techniques to improve the predictive capability of a finite element structural dynamics model. Part I of this paper discusses the experimental aspects of this work. Linear natural frequencies, damping values, and mode shapes are extracted from low excitation level testing. Subsequently, the structure is excited with high level user-defined shaker inputs. The corresponding response data are modally filtered and fit with nonlinear elements to create the nonlinear pseudo-modal model. This is then used to simulate the measured response from a high level excitation experiment which utilized a different type of input. The nonlinear model is then employed in a reduced order, generalized structural dynamics model as discussed in Part II.

Effective mass for a particular mode in a particular direction is classically calculated using a combination of fixed base mode shapes, the mass matrix, and a rigid body mode shape from a finite element model. Recently, an experimental method was developed to calculate effective mass using free experimental mode shapes of a structure on a fixture (the base) along with the measured mass of the fixture and of the test article. The method required three steps. The first step involved constraining all the free modes of the fixture except one rigid body mode in the direction of interest. The second step involved calculating pseudo-modal participation factors for this case. The third step involved constraining the final fixture rigid body degree of freedom and utilizing the constraint matrices with pseudo-modal participation factors to obtain the estimate of the standard modal participation factors which can be converted to effective mass. This work provides a simpler formulation. After the constraint in step one above, the effective masses are calculated directly from the mass normalized mode shapes of the fixture. In most cases this method gives the same answer as the original approach, within experimental error. In some instances, it appears more robust with low signal to noise ratios. It also provides better physical insight as to which modes have significant effective mass in a particular direction. The new approach is illustrated by experimental example.

Linear structural dynamic models are often used to support system design and qualification. Overall, linear models provide an efficient means for conducting design studies and augmenting test data by recovering un-instrumented or unmeasurable quantities (e.g. stress). Nevertheless, the use of linear models often adds significant conservatism in design and qualification programs by failing to capture critical mechanisms for energy dissipation. Unfortunately, the use of explicit nonlinear models can require unacceptably large efforts in model development and experimental characterization to account for common nonlinearities such as frictional interfaces, macro-slip, and other complex material behavior. The computational requirements are also greater by orders of magnitude. Conversely, modal models are much more computationally efficient and experimentally have shown the ability to capture typical structural nonlinearity. Thus, this work will seek to use modal nonlinear identification techniques to improve the predictive capability of a finite element structural dynamics model. Part I of this paper discussed experimental aspects of this work. Part II will consider use of nonlinear modal models in finite element modeling. First, the basic theory and numerical implementation is discussed. Next, the linear structural dynamic model of a configuration of interest is presented and model updating procedures are discussed. Finally, verification exercises are presented for a high level excitation using test data and simulated predictions from a structural dynamics model augmented with models obtained in nonlinear identification efforts.

The 3D Scanning Laser Doppler Vibrometer (3D SLDV) has the ability to scan a large number of points with high accuracy compared to traditional roving hammer or accelerometer tests. The 3D SLDV has disadvantages, however, in that it requires line-of-sight from three scanning laser heads to the point being measured. This means that multiple scans can become necessary to measure large or complex parts, and internal components cannot typically be measured. In the past, large aerospace structures tested at Sandia National Laboratories typically have used a handful of accelerometer stations and instrumented internal components to characterize these test articles. This work describes two case studies that explore the advantages and difficulties in using a 3D SLDV to measure the same test articles with a much higher resolution scan of the exterior. This work proposes strategies for combining a large number of accelerometer channels with a high resolution laser scan. It explores the use of mirrors and laser head mounts to enable efficient re-alignment of the lasers with the test article when many scans are necessary, and it discusses the difficulties and pitfalls inherent with performing such a test.

Metal additive manufacturing (AM) has recently become a desirable process for complex parts across a broad range of applications. However, AM materials often have a varied microstructure due to non-equilibrium solidification conditions. While some adjustments have been made in manufacturing to enhance mechanical traits, very little attention has been directed at understanding the corrosion properties of these materials. The microstructural characteristics of the AM materials may lead to reduction in the corrosion resistance of the AM alloys compared to their conventional counterparts. This presentation explores the corrosion susceptibility of AM stainless steels in aqueous sodium chloride environments as well as industry relevant solutions. Further detailed corrosion studies combined with microstructural characterization provide insight into the microstructural influences on corrosion.

Counting the frequency of small subgraphs is a fundamental technique in network analysis across various domains, most notably in bioinformatics and social networks. The special case of triangle counting has received much attention. Getting results for 4-vertex or 5-vertex patterns is highly challenging, and there are few practical results known that can scale to massive sizes. We introduce an algorithmic framework that can be adopted to count any small pattern in a graph and apply this framework to compute exact counts for all 5-vertex subgraphs. Our framework is built on cutting a pattern into smaller ones, and using counts of smaller patterns to get larger counts. Furthermore, we exploit degree orientations of the graph to reduce runtimes even further. These methods avoid the combinatorial explosion that typical subgraph counting algorithms face. We prove that it suffices to enumerate only four specific subgraphs (three of them have less than 5 vertices) to exactly count all 5-vertex patterns. We perform extensive empirical experiments on a variety of real-world graphs. We are able to compute counts of graphs with tens of millions of edges in minutes on a commodity machine. To the best of our knowledge, this is the first practical algorithm for 5-vertex pattern counting that runs at this scale. A stepping stone to our main algorithm is a fast method for counting all 4-vertex patterns. This algorithm is typically ten times faster than the state of the art 4-vertex counters.

In film cooling flows, it is important to know the temperature distribution resulting from the interaction between a hot main flow and a cooler jet. However, current Reynolds-averaged Navier-Stokes (RANS) models yield poor temperature predictions. A novel approach for RANS modeling of the turbulent heat flux is proposed, in which the simple gradient diffusion hypothesis (GDH) is assumed and a machine learning algorithm is used to infer an improved turbulent diffusivity field. This approach is implemented using three distinct data sets: two are used to train the model and the third is used for validation. The results show that the proposed method produces significant improvement compared to the common RANS closure, especially in the prediction of film cooling effectiveness.

Due to the increasing prevalence of plenoptic imaging it is necessary to explore the volumetric calibration of this imaging system to correct for inaccuracies due to real world lens distortions and thin lens assumptions in current processing methods. An overview of plenoptic imaging is given and methods of volumetric calibration of a plenoptic camera based on a polynomial mapping function are presented. The accuracy and feasibility of these methods are examined. Preliminary results suggest that use of a 3D polynomial mapping function provides a significant increase in reconstruction accuracy. Depth accuracy of particle location in calibrated volumes was measured to be accurate within 1% of the calculated volume size.

Progressive hedging, though an effective heuristic for solving stochastic mixed integer programs (SMIPs), is not guaranteed to converge in this case. Here, we describe BBPH, a branch and bound algorithm that uses PH at each node in the search tree such that, given sufficient time, it will always converge to a globally optimal solution. In addition to providing a theoretically convergent “wrapper” for PH applied to SMIPs, computational results demonstrate that for some difficult problem instances branch and bound can find improved solutions after exploring only a few nodes.

Novel particle release patterns have been proposed as a means to increase the thermal efficiency of high-temperature falling particle receivers. Innovative release patterns offer the ability to utilize light-trapping and volumetric heating effects as a means to increase particle temperatures over a conventional straight-line particle release pattern. The particle release patterns explored in this work include wave-like patterns and a series of parallel curtains normal to the incident irradiation that have shown favorable results in previous numerical studies at lower particle temperatures. A numerical model has recently been developed of an existing falling particle receiver at the National Solar Thermal Test Facility at Sandia National Laboratories to evaluate these patterns at elevated temperatures necessary to evaluate radiative and convective losses. This model has demonstrated that thermal efficiency gains of 2.5-4.6% could be realized using these patterns compared to the conventional planar release depending on the particle mass flow rate. Increasing the number of parallel curtains, increasing the spacing between curtains, and shifting the particle mass flow rate deeper in the receiver cavity was also found to increase the thermal efficiency. These effects became less significant as the particle mass flow rate increased.

Understanding of subsurface fracture opening and closure is of great importance to oil/gas production, geothermal energy extraction, radioactive waste disposal, and carbon sequestration and storage. Fracture opening and closure involve a complex set of thermal, hydrologic, mechanical and chemical (THMC) processes. In this paper, a fully coupled THMC model for fracture opening and closure is formulated by explicitly accounting for the stress concentration on aperture surface, stress-activated mineral dissolution, pressure solution at contacting asperities, and channel flow dynamics. A model analysis, together with reported laboratory observations, shows that a tangential surface stress created by a far-field compressive normal stress may play an important role in controlling fracture aperture evolution in a stressed geologic medium, a mechanism that has not been considered in any existing models. Based on the model analysis, a necessary condition for aperture opening has been derived. The model provides a reasonable explanation for many salient features of fracture evolution in laboratory experiments, including a spontaneous switch from a permeability reduction to a permeability increase in a static limestone experiment. The work may also help develop a new method for estimating in-situ stress in a reservoir.

Single-laser-shot femtosecond rotational coherent anti-Stokes Raman scattering (fs-RCARS) temperature measurements are performed across a 3- mm line in a turbulent, sooting ethylene jet flame to characterize temperature gradients. A 60-fs pulse is used to excite many rotational Raman transitions, and a 160-ps pulse is used to probe the Raman coherence. The spatial resolution of the measurements is 670 μm in the direction of beam propagation, 200 μm in the direction along the 1D line, and 50 μm in the transverse direction. Measurements have been performed at multiple locations in the jet flame, and the measured temperature are similar to previously recorded point measurements.

Single-laser-shot femtosecond rotational coherent anti-Stokes Raman scattering (fs-RCARS) temperature measurements are performed across a 3- mm line in a turbulent, sooting ethylene jet flame to characterize temperature gradients. A 60-fs pulse is used to excite many rotational Raman transitions, and a 160-ps pulse is used to probe the Raman coherence. The spatial resolution of the measurements is 670 μm in the direction of beam propagation, 200 μm in the direction along the 1D line, and 50 μm in the transverse direction. Measurements have been performed at multiple locations in the jet flame, and the measured temperature are similar to previously recorded point measurements.

Fluid-structure interactions were studied on a 7° half-angle cone in the Purdue Boeing/AFOSR Mach 6 Quiet Tunnel. A thin carbon-composite panel was integrated into the cone and its response to boundary-layer disturbances was measured. Under quiet flow, the cone boundary layer remained laminar. A spark perturber was used to create turbulent spots in the boundary layer at frequencies between 0.1 and 10.5 kHz. Isolated turbulent spots excited a directionally dependent panel response which would last much longer than the spot duration. At higher repetition rates, the panel response did not damp out before the subsequent spot. When the excitation frequency matched a structural natural frequency of the panel, resonance would occur in the directions associated with the mode shape. It was harder to excite spanwise vibration at lower frequencies because of the dominant axial and wall-normal forcing created by the controlled turbulent spots. At higher frequencies, spanwise resonance could be more easily excited, likely because the highly coupled mode shapes associated with those frequencies provided a path for energy transfer.

Biological neural networks continue to inspire new developments in algorithms and microelectronic hardware to solve challenging data processing and classification problems. Here, we survey the history of neural-inspired and neuromorphic computing in order to examine the complex and intertwined trajectories of the mathematical theory and hardware developed in this field. Early research focused on adapting existing hardware to emulate the pattern recognition capabilities of living organisms. Contributions from psychologists, mathematicians, engineers, neuroscientists, and other professions were crucial to maturing the field from narrowly-tailored demonstrations to more generalizable systems capable of addressing difficult problem classes such as object detection and speech recognition. Algorithms that leverage fundamental principles found in neuroscience such as hierarchical structure, temporal integration, and robustness to error have been developed, and some of these approaches are achieving world-leading performance on particular data classification tasks. In addition, novel microelectronic hardware is being developed to perform logic and to serve as memory in neuromorphic computing systems with optimized system integration and improved energy efficiency. Key to such advancements was the incorporation of new discoveries in neuroscience research, the transition away from strict structural replication and towards the functional replication of neural systems, and the use of mathematical theory frameworks to guide algorithm and hardware developments.

Second order nonlinearity vanishes for centrosymmetric materials in the dipole approximation. For metamaterial this means second-harmonic-generation is negligible in highly symmetric meta-atoms. We show a new type of meta-atom in which the dipolar approximation breaks down.

The purpose of this article is to explore the dependence of calculated postshock thermodynamic properties in shock tube experiments upon the vibrational state of the test gas and upon the uncertainties inherent to calculation inputs. This paper first offers a comparison between state variables calculated according to a Rankine-Hugoniot-equationbased algorithm, known as FROSH, and those derived from shock tube experiments on vibrationally nonequilibrated gases. It is shown that incorrect vibrational relaxation assumptions could lead to errors in temperature as large as8% for 25% oxygen/argon mixtures at 3500 K. Following this demonstration, this article employs the algorithm to show the importance of correct vibrational equilibration assumptions, noting, for instance, that errors in temperature of up to about 2% at 3500 K may be generated for 10% nitrogen/argon mixtures if vibrational relaxation is not treated properly. Finally, this article presents an extensive uncertainty analysis, showing that postshock temperatures can be calculated with root-of-sum-of-square errors of better than ± 1% given sufficiently accurate experimentally measured input parameters.

Due to the increasing prevalence of plenoptic imaging it is necessary to explore the volumetric calibration of this imaging system to correct for inaccuracies due to real world lens distortions and thin lens assumptions in current processing methods. An overview of plenoptic imaging is given and methods of volumetric calibration of a plenoptic camera based on a polynomial mapping function are presented. The accuracy and feasibility of these methods are examined. Preliminary results suggest that use of a 3D polynomial mapping function provides a significant increase in reconstruction accuracy. Depth accuracy of particle location in calibrated volumes was measured to be accurate within 1% of the calculated volume size.

Ferroelastic domain walls provide opportunities for deterministically controlling mechanical, optical, electrical, and thermal energy. Domain wall characterization in micro- and nanoscale systems, where their spacing may be of the order of 100 nm or less is presently limited to only a few techniques, such as piezoresponse force microscopy and transmission electron microscopy. These respective techniques cannot, however, independently characterize domain polarization orientation and domain wall motion in technologically relevant capacitor structures or in a non-destructive manner, thus presenting a limitation of their utility. In this work, we show how backscatter scanning electron microscopy utilizing channeling contrast yield can image the ferroelastic domain structure of ferroelectric films with domain wall spacing as narrow as 10 nm. Combined with electron backscatter diffraction to identify grain orientations, this technique provides information on domain orientation and domain wall type that cannot be readily measured using conventional non-destructive methods. In addition to grain orientation identification, this technique enables dynamic domain structure changes to be observed in functioning capacitors utilizing electrodes that are transparent to the high-energy backscattered electrons. This non-destructive, high-resolution domain imaging technique is applicable to a wide variety of ferroelectric thin films and a multitude of material systems where nanometer-scale crystallographic twin characterization is required.

We propose an algorithm for recovering sparse orthogonal polynomial expansions via collocation. A standard sampling approach for recovering sparse polynomials uses Monte Carlo sampling, from the density of orthogonality, which results in poor function recovery when the polynomial degree is high. Our proposed approach aims to mitigate this limitation by sampling with respect to the weighted equilibrium measure of the parametric domain and subsequently solves a preconditioned'1-minimization problem, where the weights of the diagonal preconditioning matrix are given by evaluations of the Christoffel function. Our algorithm can be applied to a wide class of orthogonal polynomial families on bounded and unbounded domains, including all classical families. We present theoretical analysis to motivate the algorithm and numerical results that show our method is superior to standard Monte Carlo methods in many situations of interest. Numerical examples are also provided to demonstrate that our proposed algorithm leads to comparable or improved accuracy even when compared with Legendre- and Hermite-specific algorithms.

Substructuring methods have been widely used in structural dynamics to divide large, complicated finite element models into smaller substructures. For linear systems, many methods have been developed to reduce the subcomponents down to a low-order set of equations using a special set of component modes, and these are then assembled to approximate the dynamics of a large-scale model. In this paper, a substructuring approach is developed for coupling geometrically nonlinear structures, where each subcomponent is drastically reduced to a low-order set of nonlinear equations using a truncated set of fixed-interface and characteristic constraint modes. The method used to extract the coefficients of the nonlinear reduced-order model is nonintrusive, in that it does not require any modification to the commercial finite element code but computes the reduced-order model from the results of several nonlinear static analyses. The nonlinear reduced-order models are then assembled to approximate the nonlinear differential equations of the global assembly. The method is demonstrated on the coupling of two geometrically nonlinear plates with simple supports at all edges. The plates are joined at a continuous interface through the rotational degrees of freedom, and the nonlinear normal modes of the assembled equations are computed to validate the models. The proposed substructuring approach reduces a 12,861-degree-of-freedom model down to only 23 degrees of freedom while still accurately reproducing the nonlinear normal modes.

We created a simulation model to investigate potential links between the actions of violent extremist organizations (VEOs), people in the VEO’s home country, and diaspora communities from that country living in the West. We created this model using the DYMATICA framework, which uses a hybrid cognitive system dynamics modeling strategy to simulate behaviors based on psycho-social theory. Initial results of the model are given, focusing on increases to VEO funding and recruiting resulting from an invasion of the VEO’s home country. Western intervention, prejudice, and economic drivers are also considered.

Next generation learning ecosystems will be comprised of intelligent, adaptive environments that utilize one’s cultural footprints to co-create shared narratives and facilitate intercultural understanding. The present paper discusses why digital footprints, cultural signposts, intercultural agents, and transmedia learning are needed to realize relevant learning in virtual environments. The paper introduces notions that may impact the design of culturally-aware information technology for distributed learning are presented.

Economic feasibility of geologic carbon storage demands sustaining large storage rates without damaging caprock seals. Reactivation of pre-existing or newly formed fractures may provide a leakage pathway across caprock layers. In this study, we apply an equivalent continuum approach within a finite element framework to model the fluid-pressure-induced reactivation of pre-existing fractures within the caprock, during high-rate injection of super-critical CO2 into a brine-saturated reservoir in a hypothetical system, using realistic geomechanical and fluid properties. We investigate the impact of reservoir to caprock layer thickness, wellbore orientation, and injection rate on overall performance of the system with respect to caprock failure and leakage. We find that vertical wells result in locally higher reservoir pressures relative to horizontal injection wells for the same injection rate, with high pressure inducing caprock leakage along reactivated opening-mode fractures in the caprock. After prolonged injection, leakage along reactivated fractures in the caprock is always higher for vertical than horizontal injection wells. Furthermore, we find that low ratios of reservoir to caprock thickness favor high excess pressure and thus fracture reactivation in the caprock. Injection into thick reservoir units thus lowers the risk associated with CO2 leakage.

Short circuit current (Isc) depends on the effective irradiance incident upon a PV module. Effective irradiance is highly correlated with broadband irradiance, but can vary slightly as the spectral content of the incident light changes. We explore using a few spectral wavelengths with broadband irradiance to predict Isc for ten modules of varying technologies (silicon, CIGS, CdTe). The goal is to identify a few spectral wavelengths that could be easily (and economically) measured to improve PV performance modeling.

Fungi in the Candida genus are the most common fungal pathogens. They not only cause high morbidity and mortality but can also cost billions of dollars in healthcare. To alleviate this burden, early and accurate identification of Candida species is necessary. However, standard identification procedures can take days and have a large false negative error. The method described in this study takes advantage of hyperspectral confocal fluorescence microscopy, which enables the capability to quickly and accurately identify and characterize the unique autofluorescence spectra from different Candida species with up to 84% accuracy when grown in conditions that closely mimic physiological conditions.

This paper describes methods that a distribution engineer could use to determine advanced inverter settings to improve distribution system performance. These settings are for fixed power factor, volt-var, and volt-watt functionality. Depending on the level of detail that is desired, different methods are proposed to determine single settings applicable for all advanced inverters on a feeder or unique settings for each individual inverter. Seven distinctly different utility distribution feeders are analyzed to simulate the potential benefit in terms of hosting capacity, system losses, and reactive power attained with each method to determine the advanced inverter settings.

PVLIB is a set of open source modeling functions that allow users to simulate most aspects of PV system performance. The functions, in Matlab and Python, are freely available under a BSD 3 clause open source license. The Matlab version is maintained by Sandia and is available on the PV Performance Modeling Collaborative (PVPMC) website (pvpmc.sandia.gov). The Python version is available on GitHub with packages easily installable through conda and pip. New functions were released on the Matlab version 1.3 in January 2016 and are actively being ported to Python.

Fault-tolerance poses a major challenge for future large-scale systems. Active research into coordinated, uncoordinated, and hybrid checkpointing systems has explored how the introduction of asynchrony can address anticipated scalability issues. While fully uncoordinated approaches have been shown to have significant delays, the degree of sychronization required to keep overheads low has not yet been significantly addressed. In this paper, we use a simulation-based approach to show the impact of synchronization on local checkpoint activity. Specifically, we show the degree of synchronization needed to keep the impacts of local checkpointing low is attainable with current technology for a number of key production HPC workloads. Our work provides a critical analysis and comparison of synchronization and local checkpointing. This enables users and system administrators to fine-tune the checkpointing scheme to the application and system characteristics available.

As PV and wind power penetrations in utility balancing areas increase, it is important to understand how they will impact net load. We investigate daily and seasonal trends in solar power generation, wind power generation, and net load. Quantitative metrics are used to compare scenarios with no PV or wind, PV plus wind, only PV, or only wind. PV plus wind scenarios are found to have a larger reduction in maximum net load and smaller ranges between maximum and minimum load than PV only or wind only scenarios, showing that PV plus wind can be a beneficial combination.

The use of the term 'availability' to describe a photovoltaic (PV) system and power plant has been fraught with confusion for many years. A term that is meant to describe equipment operational status is often omitted, misapplied or inaccurately combined with PV performance metrics due to attempts to measure performance and reliability through the lens of traditional power plant language. This paper discusses three areas where current research in standards, contract language and performance modeling is improving the way availability is used with regards to photovoltaic systems and power plants.

Photovoltaic (PV) distributed energy resources (DER) have reached approximately 27 GW in the U.S., and the solar penetration rate continues to increase. This growth is expected to continue, causing challenges for grid operators who must maintain grid stability, reliability, and resiliency. To minimize adverse effects on the performance of electrical power system (EPS) with increasing levels of variable renewable generation, photovoltaic inverters must implement grid-support capabilities, allowing the DER to actively participate in grid support operations and remain connected during short-term voltage and frequency anomalies. These functions include voltage and frequency regulation features that adjust DER active and reactive power at the point of common coupling. To evaluate the risk of these functions conflicting with traditional distribution system voltage regulation equipment, researchers used several methods to quantify EPS-support function response times for autonomous voltage regulation functions (volt-var function). Based on this study, no adverse interactions between PV inverters with volt-var functions and load tap changing transformers or capacitor banks were discovered.

The Sandia Array Performance Model (SAPM), a semi-empirical model for predicting PV system power, has been in use for more than a decade. While several studies have presented laboratory intercomparisons of measurements and analysis, detailed procedures for determining model coefficients have never been published. Independent test laboratories must develop in-house procedures to determine SAPM coefficients, which contributes to uncertainty in the resulting models. In response to requests from commercial laboratories and module manufacturers, Sandia has formally documented the measurement and analysis methods as a supplement to the original model description. In this paper we present a description of the measurement procedures and an example analysis for calibrating the SAPM.

The Sandia Array Performance Model (SAPM), a semi-empirical model for predicting PV system power, has been in use for more than a decade. While several studies have presented laboratory intercomparisons of measurements and analysis, detailed procedures for determining model coefficients have never been published. Independent test laboratories must develop in-house procedures to determine SAPM coefficients, which contributes to uncertainty in the resulting models. In response to requests from commercial laboratories and module manufacturers, Sandia has formally documented the measurement and analysis methods as a supplement to the original model description. In this paper we present a description of the measurement procedures and an example analysis for calibrating the SAPM.

The geological disposal of nuclear waste is based on the multi-barrier concept, comprising various engineered and natural barriers, to confine the radioactive waste and isolate it from the biosphere. Some of the planned repositories for high-level nuclear waste will be hosted in fractured crystalline rock formations. The potential of these formations to act as natural transport barriers is related to two coupled processes: diffusion into the rock matrix and sorption onto the mineral surfaces available in the rock matrix. Different in situ and laboratory experiments have pointed out the ubiquitous heterogeneous nature of the rock matrix: mineral surfaces and pore space are distributed in complex microstructures and their distribution is far from being homogeneous (as typically assumed by Darcy-scale coarse reactive transport models). In this work, we use a synthetically generated fracture–matrix system to assess the implications of grain-scale physical and mineralogical heterogeneity on cesium transport and retention. The resulting grain-scale reactive transport model is solved using high-performance computing technologies, and the results are compared with those derived from two alternative models, denoted as upscaled models, where mineral abundance is averaged over the matrix volume. In the grain-scale model, the penetration of cesium into the matrix is faster and the penetration front is uneven and finger-shaped. The analysis of the cesium breakthrough curves computed at two different points in the fracture shows that the upscaled models provide later first-arrival time estimates compared to the grain-scale model. The breakthrough curves computed with the three models converge at late times. These results suggest that spatially averaged upscaled parameters of sorption site distribution can be used to predict the late-time behavior of breakthrough curves but could be inadequate to simulate the early behavior.

Photovoltaic (PV) distributed energy resources (DER) have reached approximately 27 GW in the U.S., and the solar penetration rate continues to increase. This growth is expected to continue, causing challenges for grid operators who must maintain grid stability, reliability, and resiliency. To minimize adverse effects on the performance of electrical power system (EPS) with increasing levels of variable renewable generation, photovoltaic inverters must implement grid-support capabilities, allowing the DER to actively participate in grid support operations and remain connected during short-term voltage and frequency anomalies. These functions include voltage and frequency regulation features that adjust DER active and reactive power at the point of common coupling. To evaluate the risk of these functions conflicting with traditional distribution system voltage regulation equipment, researchers used several methods to quantify EPS-support function response times for autonomous voltage regulation functions (volt-var function). Based on this study, no adverse interactions between PV inverters with volt-var functions and load tap changing transformers or capacitor banks were discovered.

Fluctuating boundary layer wall shear stress can be an important loading component for structures subjected to turbulent boundary layer flows. While normal force loading via wall pressure fluctuation is relatively well described analytically, there is a dearth of information for wall shear behavior. Starting with an approximate acoustic analogy we derive simple approximate expressions for both wall pressure and wall shear fluctuations behavior utilizing a Taylor hypothesis based analogy between streamwise and temporal fluctuations. Analytical results include longitudinal spatial correlation, autocorrelation, frequency spectrum, RMS intensity and longitudinal and lateral coherence expressions. While coefficients in these expressions usually require some empirical input they nonetheless provide useful predictions for functional behavior. Comparison of the models with available literature data sets suggests reasonable agreement. Dedicated high fidelity numerical computations (direct numerical simulations) for a supersonic boundary layer are used to further explore the efficacy of these models. The analytical models for wall pressure fluctuation and wall shear fluctuation spectral density compare well for low frequency with the simulations when Reynolds number effects are included in the pressure fluctuation intensity. The approximate analytical models developed here provide a physics-based connection between classical empirical expressions and more complete experimental and computational descriptions.

Photovoltaic system monitoring can generate vast amounts of data. Analytical methods are required to post-process this data into useful information. Pecos is open source software designed to address this need. The software was developed at Sandia National Laboratories and is compatible with performance models in PVLIB-Python. The software can be used to automatically run a series of quality control tests and generate reports which include performance metrics, test results, and graphics.

High-frequency solar variability is an important to grid integration studies, but ground measurements are scarce. The high resolution irradiance algorithm (HRIA) has the ability to produce 4-sceond resolution global horizontal irradiance (GHI) samples, at locations across North America. However, the HRIA has not been extensively validated. In this work, we evaluate the HRIA against a database of 10 high-frequency ground-based measurements of irradiance. The evaluation focuses on variability-based metrics. This results in a greater understanding of the errors in the HRIA as well as suggestions for improvement to the HRIA.

High-frequency solar variability is an important to grid integration studies, but ground measurements are scarce. The high resolution irradiance algorithm (HRIA) has the ability to produce 4-sceond resolution global horizontal irradiance (GHI) samples, at locations across North America. However, the HRIA has not been extensively validated. In this work, we evaluate the HRIA against a database of 10 high-frequency ground-based measurements of irradiance. The evaluation focuses on variability-based metrics. This results in a greater understanding of the errors in the HRIA as well as suggestions for improvement to the HRIA.

The goal of this effort was to assess the effect of high penetration solar deployment on the small signal stability of the western North American power system (wNAPS). Small signal stability is concerned with the system response to small disturbances, where the system is operating in a linear region. The study area consisted of the region governed by the Western Electricity Coordinating Council (WECC). General Electric's Positive Sequence Load Flow software (PSLF®) was employed to simulate the power system. A resistive brake insertion was employed to stimulate the system. The data was then analyzed in MATLAB1® using subspace methods (Eigensystem Realization Algorithm). Two different WECC base cases were analyzed: 2022 light spring and 2016 heavy summer. Each base case was also modified to increase the percentage of wind and solar. In order to keep power flows the same, the modified cases replaced conventional generation with renewable generation. The replacements were performed on a regional basis so that solar and wind were placed in suitable locations. The main finding was that increased renewable penetration increases the frequency of inter-area modes, with minimal impact on damping. The slight increase in mode frequency was consistent with the loss of inertia as conventional generation is replaced with wind and solar. Then, distributed control of renewable generation was assessed as a potential mitigation, along with an analysis of the impact of communications latency on the distributed control algorithms.

This paper describes methods that a distribution engineer could use to determine advanced inverter settings to improve distribution system performance. These settings are for fixed power factor, volt-var, and volt-watt functionality. Depending on the level of detail that is desired, different methods are proposed to determine single settings applicable for all advanced inverters on a feeder or unique settings for each individual inverter. Seven distinctly different utility distribution feeders are analyzed to simulate the potential benefit in terms of hosting capacity, system losses, and reactive power attained with each method to determine the advanced inverter settings.

A control algorithm is designed to smooth the variability of PV power output using distributed batteries. The tradeoff between smoothing and battery size is shown. It is also demonstrated that large numbers of highly distributed current, voltage, and irradiance sensors can be utilized to control the distributed storage in a more optimal manner. It is also demonstrated that centralized energy storage control for PV ramp rate smoothing requires very fast communication, typically less than a 15-second update rate. Finally, advanced inverter dynamic reactive current is shown to provide voltage variability smoothing, hence reducing the number of voltage regulator tap changes without energy storage.

A control algorithm is designed to smooth the variability of PV power output using distributed batteries. The tradeoff between smoothing and battery size is shown. It is also demonstrated that large numbers of highly distributed current, voltage, and irradiance sensors can be utilized to control the distributed storage in a more optimal manner. It is also demonstrated that centralized energy storage control for PV ramp rate smoothing requires very fast communication, typically less than a 15-second update rate. Finally, advanced inverter dynamic reactive current is shown to provide voltage variability smoothing, hence reducing the number of voltage regulator tap changes without energy storage.

The research presented in this paper compares five real-time control strategies for the power output of a large number of distributed PV systems in a large distribution feeder circuit. Both real and reactive power controls are considered with the goal of minimizing network over-voltage violations caused by high penetrations of PV generation. The control parameters are adjusted to maximize the effectiveness of each control. The controls are then compared based on their ability to achieve multiple objectives. These objectives include minimizing the total number of voltage violations, minimizing the total amount of PV energy curtailed or reactive power generated, and maximizing the fairness of any control action among all PV systems. The controls are simulated on the OpenDSS platform using time series load and spatially-distributed irradiance data.

PVLIB is a set of open source modeling functions that allow users to simulate most aspects of PV system performance. The functions, in Matlab and Python, are freely available under a BSD 3 clause open source license. The Matlab version is maintained by Sandia and is available on the PV Performance Modeling Collaborative (PVPMC) website (pvpmc.sandia.gov). The Python version is available on GitHub with packages easily installable through conda and pip. New functions were released on the Matlab version 1.3 in January 2016 and are actively being ported to Python.

Determination of module temperature coefficients for voltage, current and power requires measuring the average of cell temperatures. Conventional practice is to place thermocouples or resistive temperature devices (RTDs) at a few locations on a module's back surface and to average the readings, which may not accurately represent the average temperature over all cells. We investigate the suitability of averaging RTDs, which measure average temperature along a 1m length, to accurately measure the average cell temperature when determining temperature coefficients outdoors.

Current-voltage (I-V) curve traces of photovoltaic (PV) systems can provide detailed information for diagnosing fault conditions. The present work implemented an in situ, automatic I-V curve tracer system coupled with Support Vector Machine and a Gaussian Process algorithms to classify and estimate abnormal and normal PV performance. The approach successfully identified normal and fault conditions. In addition, the Gaussian Process regression algorithm was used to estimate ideal I-V curves based on a given irradiance and temperature condition. The estimation results were then used to calculate the lost power due to the fault condition.

A two-dimensional direct numerical simulation of the ignition at diesel engine-relevant conditions was performed at 40 atm and at 900 K ambient temperature using dimethyl ether (DME) as the fuel with a 30 species reduced chemical mechanism. At these conditions similar to diesel fuel DME exhibited two-stage ignition. The low-temperature chemistry analysis revealed a "spotty" first-stage autoignition in lean regions which transitions to a diffusively supported cool-flame and then propagates up the local mixture fraction gradient towards richer regions. The cool-flame speed was much faster than can be attributed to spatial gradients in first-stage ignition delay time in homogeneous reactors and it caused a shortening of the second-stage ignition delay times compared to a homogeneous reactor wherein the shortening became more pronounced at richer mixtures. Multiple high-temperature ignition kernels were noted over a range of rich mixtures that are much richer than the homogeneous most reactive mixture and most kernels formed much earlier than suggested by the homogeneous ignition delay time of the corresponding local mixture.

Monitoring of photovoltaic (PV) systems can maintain efficient operations. However, extensive monitoring of large quantities of data can be a cumbersome process. The present work introduces a simple, inexpensive, yet effective data monitoring strategy for detecting faults and determining lost revenues automatically. This was achieved through the deployment of Raspberry Pi (RPI) device at a PV system's combiner box. The RPI was programmed to collect PV data through Modbus communications, and store the data locally in a MySQL database. Then, using a Gaussian Process Regression algorithm the RPI device was able to accurately estimate string level current, voltage, and power values. The device could also detect system faults using a Support Vector Novelty Detection algorithm. Finally, the RPI was programmed to output the potential lost revenue caused by the abnormal condition. The system analytics information was then displayed on a user interface. The interface could be accessed by operations personal to direct maintenance activity so that critical issues can be solved quickly.

The effect of uncertainty in the energy partition function on the silicon displacement damage metric is presented. Through the use of a Total Monte Carlo approach, the effect of uncertainty in the underlying electronic and nuclear ion interaction potentials, which are used to define the damage partition function, is propagated into an uncertainty in the silicon damage metric. This uncertainty is expressed as an energy-dependent covariance matrix which permits this uncertainty component to be combined with other uncertainty components, e.g. uncertainty due to the knowledge of the nuclear interaction data or to the treatment of the damage in the threshold displacement region. This approach provides a rigorous treatment of uncertainty due to the damage metric which can then be propagated in uncertainty estimates for various applications, e.g. when examining damage equivalence between different neutron sources. A strong energy-dependent correlation is found in this uncertainty component.

The capability to characterize the neutron energy spectrum and fluence received by a test object is crucial to understanding the damage effects observed in electronic components. For nuclear research reactors and high energy density physics facilities this can pose exceptional challenges, especially with low level neutron fluences. An ASTM test method for characterizing neutron environments utilizes the 2N2222A transistor as a 1-MeV equivalent neutron fluence sensor and is applicable for environments with 1 × 1012 - 1 × 1014 1 -MeV(Si)-Eqv.-n/cm2. In this work we seek to extend the range of this test method to lower fluence environments utilizing the 2N1486 transistor. The 2N1486 is shown to be an effective neutron displacement damage sensor as low as 1 × 1010 1-MeV(Si)-Eqv.-n/cm2.

We studied the effect of light ion and heavy ion irradiations on pnp Si BJTs. A mismatch in DLTS deep peak amplitude for devices with same final gain but irradiated with different ion species was observed. Also, different ions cause different gain degradation when the DLTS spectra are matched. Pre-dosed ion-irradiated samples show that ion induced ionization does not account for the differences in DLTS peak height but isochronal annealing studies suggest that light ions produce more VP defects than heavy ions to compensate for the lack of clusters that heavy ions produce. The creation of defect clusters by heavy ions is evident by the higher content of E4 and V2∗ defects compared to light ions.

Total ionizing dose results are provided, showing the effects of different threshold adjust implant processes and irradiation bias conditions of 14-nm FinFETs. Minimal radiation-induced threshold voltage shift across a variety of transistor types is observed. Off-state leakage current of nMOSFET transistors exhibits a strong gate bias dependence, indicating electrostatic gate control of the sub-fin region and the corresponding parasitic conduction path are the largest concern for radiation hardness in FinFET technology. The high-Vth transistors exhibit the best irradiation performance across all bias conditions, showing a reasonably small change in off-state leakage current and Vth, while the low-Vth transistors exhibit a larger change in off-state leakage current. The "worst-case" bias condition during irradiation for both pull-down and pass-gate nMOSFETs in static random access memory is determined to be the on-state (Vgs = Vdd). We find the nMOSFET pull-down and pass-gate transistors of the SRAM bit-cell show less radiation-induced degradation due to transistor geometry and channel doping differences than the low-Vth transistor. Near-threshold operation is presented as a methodology for reducing radiation-induced increases in off-state device leakage current. In a 14-nm FinFET technology, the modeling indicates devices with high channel stop doping show the most robust response to TID allowing stable operation of ring oscillators and the SRAM bit-cell with minimal shift in critical operating characteristics.

Despite the known degrading impact of high nuisance and false alarm rates (NAR/FAR) on operator performance, analyses of security systems often ignores operator performance. We developed a model to analyze the impact of nuisance alarm rates on operator performance and on overall system performance. The model demonstrates that current methods that do not account for operator performance produce optimistic estimates of system performance. As shown in our model, even low NAR/FAR levels and the associated alarm queueing effect can increase operator detect and response time, which in turn reduces the amount of time the response force has to interrupt the intruder. An illustrative analysis shows that alarm processing times can be higher than the assessment time due to queue wait times and that systems with only one or two operators can become overwhelmed as NAR increases, decreasing system performance.

Turbulent fluctuations of the scalar dissipation rate have a major impact on extinction in non-premixed combustion. Recently, an unsteady extinction criterion has been developed (Hewson, 2013) that predicts extinction dependent on the duration and the magnitude of dissipation rate fluctuations exceeding a critical quenching value; this quantity is referred to as the dissipation impulse. The magnitude of the dissipation impulse corresponding to unsteady extinction is related to the difficulty with which a flamelet is exintguished, based on the steady-state S-curve. In this paper we evaluate this new extinction criterion for more realistic dissipation rates by evolving a stochastic Ornstein-Uhlenbeck process for the dissipation rate. A comparison between unsteady flamelet evolution using this dissipation rate and the extinction criterion exhibit good agreement. The rate of predicted extinction is examined over a range of Damköhler and Reynolds numbers and over a range of the extinction difficulty. The results suggest that the rate of extinction is proportional to the average dissipation rate and the area under the dissipation rate probability density function exceeding the steady-state quenching value. It is also inversely related to the actual probability that this steady-state quenching dissipation rate is observed and the difficulty of extinction associated with the distance between the upper and middle branches of the S-curve.

The formation of one- and two-ring aromatic species in near atmospheric- pressure opposed-flow diffusion flames of 1,3-butadiene (1,3-C4 H6 ) was studied. The chemical structures of two different 1,3-C4 H6 /Ar-O2/Ar flames were studied using flame-sampling molecular-beam mass spectrometry with both electron and single-photon ionization. Generally a very good agreement was observed between the experimental and modelling data, allowing for a meaningful reaction path analysis. In the formation of aromatic species up to naphthalene, it was essential to improve the fulvene and the C5 chemistry description in the mechanism. Benzene was formed mainly via fulvene through the reactions of the C4H5 isomers with C2H2. The n-C4H5 radical reacted with CH3 forming 1,3-pentadiene (C5H8), which was subsequently oxidized to form the naphthalene precursor cyclopentadienyl (C5H5). Oxidation of naphthalene is predicted to be a contributor to the formation of phenylacetylene (C8H6), implying that consumption reactions can be of the same importance as molecular growth reactions.

The Waste Isolation Pilot Plant (WIPP), located in southeastern New Mexico of the United States (U.S.), has been developed by the U.S. Department of Energy (DOE) for the geologic disposal of transuranic (TRU) waste. The DOE demonstrates compliance with the WIPP containment requirements by means of performance assessment (PA) calculations. WIPP PA calculations estimate the probability and consequence of potential radionuclide releases from the repository to the accessible environment for a regulatory period of 10,000 years after facility closure. WIPP PA models are used (in part) to support the repository recertification process that occurs at five-year intervals following the receipt of the first waste shipment at the site in 1999. The PA executed in support of the 2014 Compliance Recertification Application (CRA-2014) for WIPP includes a number of parameter, implementation, and repository feature changes. Among these changes are the incorporation of a new panel closure system design, additional mined volume in the north end of the repository, a refinement to the PA representation of WIPP waste shear strength, and a gas generation rate refinement. These changes are briefly discussed, as is their cumulative impact on regulatory compliance for the facility. The federal recertification status of the WIPP is also discussed.

Except in extreme weather conditions, Synthetic aperture radar (SAR) is a remote sensing technology that can operate day or night. SAR can provide surveillance by making multiple passes over a wide area. For object-based intelligence, it is convenient to use these multiple passes to segment and classify the SAR images into objects that identify various terrains and man-made structures that we call "static-features." Our approach is unique in that we have multiple SAR passes of an area over a long period of time (on the order of weeks). From these many SAR images of the same area, we can combine SAR images from different times to create a variety of SAR products. For example, we introduce a novel SAR image product that captures how different regions decorrelate at different rates. From these many SAR products, we exact superpixels or groups of connected pixels that describe a homogenous region. Using pixels contained within a superpixel we develop a series of one-class classification algorithms using a goodness-of-fit metric that classifies terrains of interest in each SAR product for each superpixel. To combine the results from many SAR products we use P-value fusion. The result is a classification and a confidence about the different classes. To enforce spatial consistency, we represent the confidence labeling of the superpixels as a conditional random field and infer the most likely labeling by maximize the posterior probability of the random field. The result is a colorized SAR image where each color represents a different terrain class.

This work has applied a suite of long-term-reliability accelerated tests to a variety of module-level power electronics (MLPE) devices (such as microinverters and optimizers) from five different manufacturers. This dataset is one of the first (only the paper by Parker et al. entitled 'Dominant factors affecting reliability of alternating current photovoltaic modules,' in Proc. 42nd IEEE Photovoltaic Spec. Conf. , 2015, is reported for reliability testing in the literature), as well as the largest, experimental sets in public literature, both in the sample size (five manufacturers including both dc/dc and dc/ac units and 20 units for each test) and the number of experiments (six different experimental test conditions) for MLPE devices. The accelerated stress tests (thermal cycling test per IEC 61215 profile, damp heat test per IEC 61215 profile, and static temperature tests at 100 and 125 °C) were performed under powered and unpowered conditions. The first independent long-term experimental data regarding damp heat and grid transient testing, as well as the longest term (>9 month) testing of MLPE units reported in the literature for thermal cycling and high-temperature operating life, are included in these experiments. Additionally, this work is the first to show in situ power measurements, as well as periodic efficiency measurements over a series of experimental tests, demonstrating whether certain tests result in long-term degradation or immediate catastrophic failures. The result of this testing highlights the performance of MLPE units under the application of several accelerated environmental stressors.

The dentate gyrus forms a critical link between the entorhinal cortex and CA3 by providing a sparse version of the signal. Concurrent with this increase in sparsity, a widely accepted theory suggests the dentate gyrus performs pattern separation-similar inputs yield decorrelated outputs. Although an active region of study and theory, few logically rigorous arguments detail the dentate gyrus's (DG) coding.We suggest a theoretically tractable, combinatorial model for this action. The model provides formal methods for a highly redundant, arbitrarily sparse, and decorrelated output signal. To explore the value of this model framework, we assess how suitable it is for two notable aspects of DG coding: how it can handle the highly structured grid cell representation in the input entorhinal cortex region and the presence of adult neurogenesis, which has been proposed to produce a heterogeneous code in the DG.We find tailoring themodel to grid cell input yields expansion parameters consistent with the literature. In addition, the heterogeneous coding reflects activity gradation observed experimentally. Finally,we connect this approach with more conventional binary threshold neural circuit models via a formal embedding.

An underserved niche exists for data mining tools in complex analytical environments. We propose three attributes of analytical tool development that facilitates rapid operationalization of new tools into complex, dynamic environments: accessibility, adaptability, and extendibility. Accessibility we define as the ability to load data into an analytical system quickly and seamlessly. Adaptability we define as the ability to apply a tool rapidly to new, unanticipated use cases. Extendibility we define as the ability to create new functionality “in the field” where it is being used and, if needed, harden that new functionality into a new, more permanent user interface. Distributed “big data” systems generally do not optimize for these attributes, creating an underserved niche for new analytical tools. In this paper we will define the problem, examine the three attributes, and describe the architecture of an example system called Citrus that we have built and use that is especially focused on these three attributes.

Additively manufactured (AM) austenitic stainless steels are intriguing candidates for the storage of gaseous hydrogen isotopes because complex vessel geometries can be built more easily than by using conventional machining options. Parts built with AM stainless steel tend to have excellent mechanical properties (with tensile strength, ductility, fatigue crack growth, and fracture toughness comparable to or exceeding that of wrought austenitic stainless steel). However, the solidification microstructures produced by AM processing differ substantially from the microstructures of wrought material. Some features may affect permeability, including some amount of porosity and a greater amount of ferrite. Because the diffusivity of hydrogen in ferrite is greater than in austenite (six orders of magnitude at ambient temperature), care must be taken to retain the performance that is taken for granted due to the base alloy chemistry. Furthermore, AM parts tend to have greater dislocation densities and greater amounts of carbon, nitrogen, and oxygen. These features, along with the austenite/ferrite interfaces, may contribute to greater hydrogen trapping. We report the results of our studies of deuterium transport in various austenitic (304L, 316, and 316L) steels produced by AM. Manufacturing by Powder Bed Fusion (PBF) and two different blown powder methods are considered here (Laser Engineered Net Shaping® (LENS®) and a Direct Laser Powder Deposition (DLPD) method with a higher laser power)). The hydrogen permeability (an equilibrium property) changes negligibly (less than a factor of 2), regardless of chemistry and processing method, when tested between 150 and 500°C. This is despite increases in ferrite content up to FN=2.7. However, AM materials exhibit greater hydrogen isotope trapping, as measured by permeation transients, thermal desorption spectra, and inert gas fusion measurement. The trapping energies are likely modest (<10 kJ/mol), but may indicate a larger population of trap sites than in conventional 300-series stainless steels.

Flexible open celled foams are commonly used for energy absorption in packaging. Over time polymers can suffer from aging by becoming stiffer and more brittle. This change in stiffness can affect the foam’s performance in a low velocity impact event. In this study, the compressive properties of new open-cell flexible polyurethane foam were compared to those obtained from aged open-cell polyurethane foam that had been in service for approximately 25 years. The foams tested had densities of 10 and 15 pcf. These low density foams provided a significant challenge to machine cylindrical compression specimens that were 1 “in height and 1” in diameter. Details of the machining process are discussed. The compressive properties obtained for both aged and new foams included testing at various strain rates (0.05. 0.10, 5 s-1) and temperatures (-54, RT, 74 °C). Results show that aging of flexible polyurethane foam does not have much of an effect on its compressive properties.

The Waste Isolation Pilot Plant (WIPP), located in southeastern New Mexico of the United States (U.S.), has been developed by the U.S. Department of Energy (DOE) for the geologic disposal of transuranic (TRU) waste. The DOE demonstrates compliance with the WIPP containment requirements by means of performance assessment (PA) calculations. WIPP PA calculations estimate the probability and consequence of potential radionuclide releases from the repository to the accessible environment for a regulatory period of 10,000 years after facility closure. WIPP PA models are used (in part) to support the repository recertification process that occurs at five-year intervals following the receipt of the first waste shipment at the site in 1999. The PA executed in support of the 2014 Compliance Recertification Application (CRA-2014) for WIPP includes a number of parameter, implementation, and repository feature changes. Among these changes are the incorporation of a new panel closure system design, additional mined volume in the north end of the repository, a refinement to the PA representation of WIPP waste shear strength, and a gas generation rate refinement. These changes are briefly discussed, as is their cumulative impact on regulatory compliance for the facility. The federal recertification status of the WIPP is also discussed.

Shales have small pore and throat sizes ranging from nano to micron scales, low porosity and limited permeability. The poor permeability and complex pore connectivity of shales pose technical challenges to (a) understanding flow and transport mechanisms in such systems and, (b) in predicting permeability changes under dynamic saturation conditions. This study presents quantitative experimental evidence of the migration of water through a generic shale core plug using micro CT imaging. In addition, in-situ measurements of gas permeability were performed during counter-current spontaneous imbibition of water in nano-darcy permeability Marcellus and Haynesville core plugs. It was seen that water blocks severely reduced the effective permeability of the core plugs, leading to losses of up to 99.5% of the initial permeability in experiments lasting 30 days. There was also evidence of clay swelling which further hindered gas flow. When results from this study were compared with similar counter-current gas permeability experiments reported in the literature, the initial (base) permeability of the rock was found to be a key factor in determining the time evolution of effective gas permeability during spontaneous imbibition. With time, a recovery of effective permeability was seen in the higher permeability rocks, while becoming progressively detrimental and irreversible in tighter rocks. These results suggest that matrix permeability of ultra-tight rocks is susceptible to water damage following hydraulic fracturing stimulation and, while shut-in/soaking time helps clearing-up fractures from resident fluid, its effect on the adjacent matrix permeability could be detrimental.

Conventional structural metals suffer from fatigue-crack initiation through dislocation activity which forms persistent slip bands leading to notch-like extrusions and intrusions. Ultrafine-grained and nanocrystalline metals can potentially exhibit superior fatigue-crack initiation resistance by suppressing these cumulative dislocation activities. Prior studies on these metals have confirmed improved high-cycle fatigue performance. In the case of nano-grained metals, analyses of subsurface crack initiation sites have indicated that the crack nucleation is associated with abnormally large grains. However, these post-mortem analyses have led to only speculation about when abnormal grain growth occurs (e.g., during fatigue, after crack initiation, or during crack growth). In this study, a recently developed synchrotron X-ray diffraction technique was used to detect the onset and progression of abnormal grain growth during stress-controlled fatigue loading. This study provides the first direct evidence that the grain coarsening is cyclically induced and occurs well before final fatigue failure—our results indicate that the first half of the fatigue life was spent prior to the detectable onset of abnormal grain growth, while the second half was spent coarsening the nanocrystalline structure and cyclically deforming the abnormally large grains until crack initiation. Post-mortem fractography, coupled with cycle-dependent diffraction data, provides the first details regarding the kinetics of this abnormal grain growth process during high-cycle fatigue testing. Precession electron diffraction images collected in a transmission electron microscope after the in situ fatigue experiment also confirm the X-ray evidence that the abnormally large grains contain substantial misorientation gradients and sub-grain boundaries.

The Waste Isolation Pilot Plant (WIPP) transuranic waste repository located east of Carlsbad, New Mexico, USA, consists of 10 waste panels located in the southern end and operations and experimental areas located in the northern end. Waste panels are to be separated from each other and from the northern areas by panel closure systems that consist of run-of-mine-salt that will compact and reconsolidate over time along with the creep closure of open areas of the repository. To more fully assess the sensitivity of predicted repository releases to currently implemented material parameters, the application of modified parameters in the operations and experimental (non-waste) areas of the repository is undertaken to simulate an accelerated (instantaneous) creep closure, the inclusion of capillary pressure effects on relative permeability, and an increase in initial/residual brine saturation and residual gas saturation in the operations and experimental areas of the repository. The resulting sensitivity analysis (CRA14-SEN2) is then compared to the most recent compliance recertification application results presented for CRA-2014 PA (CRA14). The modifications to the repository model result in increased pressures and decreased brine saturations in waste areas and increased pressures and brine saturations in the operations and experimental areas. The slight pressure increases in repository waste regions yield very slightly decreased brine saturations (on average) in those areas. Brine flows up the borehole during a hypothetical drilling intrusion are nearly identical to those found in the CRA14. Brine flows up the repository shaft are decreased as compared to CRA14 due to restricted flow within the operations and experimental areas. The modified operations and experimental area parameters essentially halt the flow of gas from the southern waste areas of the repository to the northern non-waste areas, except as transported through the marker beds and anhydrite layers. The combination of slightly increased waste region pressure (on average) and very slightly decreased brine saturations result in a modest increase in spallings and no significant effect on direct brine releases due to the pressure/saturation trade-off. Total releases from the Culebra and cuttings and cavings releases are not affected. Overall, the effects on total high-probability (P(R) > 0.1) mean releases from the repository are entirely insignificant, with total low-probability (P(R) > 0.001) mean releases minimally increased (~4%) and the associated 95% confidence level on the mean reduced (~20%). It is concluded that the baseline modeling assumptions associated with the operations and experimental areas of the repository have an insignificant effect on the prediction of total releases from the repository and/or adequacy of the current (CRA14) model to demonstrate compliance with the regulatory limits.

In this work we use estimates of ionic transport properties obtained from molecular dynamics to rank lithium electrolytes of different compositions. We develop linear response methods to obtain the Onsager diffusivity matrix for all chemical species, its Fickian counterpart, and the mobilities of the ionic species. We apply these methods to the well-studied propylene carbonate/ethylene carbonate solvent with dissolved LiBF4 and O2. The results show that, over a range of lithium concentrations and carbonate mixtures, trends in the transport coefficients can be identified and optimal electrolytes can be selected for experimental focus; however, refinement of these estimation techniques is necessary for a reliable ranking of a large set of electrolytes.

The MagLIF (Magnetized Liner Inertial Fusion) concept [Slutz et al., Phys. Plasmas 17, 056303 (2010)] has demonstrated fusion-relevant plasma conditions [Gomez et al., Phys. Rev. Lett. 113, 155003 (2014)] on the Z accelerator using external field coils to magnetize the fuel before compression. We present a novel concept (AutoMag), which uses a composite liner with helical conduction paths separated by insulating material to provide fuel magnetization from the early part of the drive current, which by design rises slowly enough to avoid electrical breakdown of the insulators. Once the magnetization field is established, the drive current rises more quickly, which causes the insulators to break down allowing the drive current to follow an axial path and implode the liner in the conventional z-pinch manner. There are two important advantages to AutoMag over external field coils for the operation of MagLIF. Low inductance magnetically insulated power feeds can be used to increase the drive current, and AutoMag does not interfere with diagnostic access. Also, AutoMag enables a pathway to energy applications for MagLIF, since expensive field coils will not be damaged each shot. Finally, it should be possible to generate Field Reversed Configurations (FRC) by using both external field coils and AutoMag in opposite polarities. This would provide a means to studying FRC liner implosions on the 100 ns time scale.

Bolted joints are prevalent in most assembled structures; however, predictive models for their behavior do not exist. Calibrated models, such as the Iwan model, are able to predict the response of a jointed structure over a range of excitations once calibrated at a nominal load. The Iwan model, though, is not widely adopted due to the high computational expense of implementation. To address this, an analytical solution of the Iwan model is derived under the hypothesis that for an arbitrary load reversal, there is a new distribution of dry friction elements, which are now stuck, that approximately resemble a scaled version of the original distribution of dry friction elements. The dry friction elements internal to the Iwan model do not have a uniform set of parameters and are described by a distribution of parameters, i.e., which internal dry friction elements are stuck or slipping at a given load, that ultimately governs the behavior of the joint as it transitions from microslip to macroslip. This hypothesis allows the model to require no information from previous loading cycles. Additionally, the model is extended to include the pinning behavior inherent in a bolted joint. Modifications of the resulting framework are discussed to highlight how the constitutive model for friction can be changed (in the case of an Iwan–Stribeck formulation) or how the distribution of dry friction elements can be changed (as is the case for the Iwan plasticity model). The reduced Iwan plus pinning model is then applied to the Brake–Reuß beam in order to discuss methods to deduce model parameters from experimental data.

Abstract not provided.

We discuss upsets in erased floating gate cells, due to large threshold voltage shifts, using statistical distributions collected on a large number of memory cells. The spread in the neutral threshold voltage appears to be too low to quantitatively explain the experimental observations in terms of simple charge loss, at least in SLC devices. The possibility that memories exposed to high energy protons and heavy ions exhibit negative charge transfer between programmed and erased cells is investigated, although the analysis does not provide conclusive support to this hypothesis.

Abstract not provided.

Abstract not provided.

Abstract not provided.

The development of scramjet engines is an important research area for advancing hypersonic and orbital flights. Progress towards optimal engine designs requires both accurate flow simulations as well as uncertainty quantification (UQ). However, performing UQ for scramjet simulations is challenging due to the large number of uncertain parameters involved and the high computational cost of flow simulations. We address these difficulties by combining UQ algorithms and numerical methods to the large eddy simulation of the HIFiRE scramjet configuration. First, global sensitivity analysis is conducted to identify influential uncertain input parameters, helping reduce the stochastic dimension of the problem and discover sparse representations. Second, as models of different fidelity are available and inevitably used in the overall UQ assessment, a framework for quantifying and propagating the uncertainty due to model error is introduced. These methods are demonstrated on a non-reacting scramjet unit problem with parameter space up to 24 dimensions, using 2D and 3D geometries with static and dynamic treatments of the turbulence subgrid model.

Materials subject to cyclic loading have been studied extensively and experimentally determined comparisons of stress to number of cycles are used to estimate fatigue life under various loading scenarios. Fatigue data are traditionally presented in the form of S-N curves. Normally, S-N data are derived from cyclic loading but the S-N results are also applicable to random vibration loading and, to some extent, shock. This paper presents an alternate presentation of fatigue data in terms of input energy and number of cycles to failure. In conjunction with this study, a series of shock tests was conducted on 3D printed cantilever beams using a 6-DOF shaker table. All of the beams were tested to failure at shock levels in the low-cycle fatigue regime. From these data, a nominal fatigue curve in terms of input energy and number of shocks to failure was generated and compared with the theoretical developments.

Abstract not provided.

Abstract not provided.

The efficiency of discrete ordinates transport sweeps depends on the scheduling algorithm, the domain decomposition, the problem to be solved, and the computational platform. Sweep scheduling algorithms may be categorized by their approach to several issues. In this paper we examine the strategy of domain overloading for mesh partitioning as one of the components of such algorithms. In particular, we extend the domain overloading strategy, previously defined and analyzed for structured meshes, to the general case of unstructured meshes. We also present computational results for both the structured and unstructured domain overloading cases. We find that an appropriate amount of domain overloading can greatly improve the efficiency of parallel sweeps for both structured and unstructured partitionings of the test problems examined on up to 105 processor cores.

As MIL-STD-810G, Environmental Engineering Considerations and Laboratory Tests, and subsequent versions have incorporated multiple-degree-of-freedom (MDOF) vibration test methodologies, it is important to understand the history and factors that drove the original decision in MIL-STD-810 to focus on single-degree-of-freedom (SDOF) vibration testing. Examining the thought process behind early MIL-STD-810 vibration test methods is useful when considering MDOF testing now that it is feasible with today's technology and documented in MIL-STD-810. This paper delves into the details of the decision made in the 1960s to develop the SDOF vibration testing standards in MIL-STD-810 beyond the limitations of technology at the time. This paper also considers the implications for effective test planning today considering the advances in test capabilities and improvements in understanding of the operational environment.

The 3D Scanning Laser Doppler Vibrometer (3D SLDV) has the ability to scan a large number of points with high accuracy compared to traditional roving hammer or accelerometer tests. The 3D SLDV has disadvantages, however, in that it requires line-of-sight from three scanning laser heads to the point being measured. This means that multiple scans can become necessary to measure large or complex parts, and internal components cannot typically be measured. In the past, large aerospace structures tested at Sandia National Laboratories typically have used a handful of accelerometer stations and instrumented internal components to characterize these test articles. This work describes two case studies that explore the advantages and difficulties in using a 3D SLDV to measure the same test articles with a much higher resolution scan of the exterior. This work proposes strategies for combining a large number of accelerometer channels with a high resolution laser scan. It explores the use of mirrors and laser head mounts to enable efficient re-alignment of the lasers with the test article when many scans are necessary, and it discusses the difficulties and pitfalls inherent with performing such a test.

Researchers present a Li-ion synaptic transistor for analog computation (LISTA). LISTA is an all solidstate, nonvolatile redox transistor (NVRT) with a resistance switching mechanism based upon the intercalation of Li-ion dopants into a channel of Li1-xCoO2. The researchers also demonstrate that an NVRT device is advantageous for neuromorphic applications because it utilizes the low energy process of ion insertion/extraction for resistance switching while maintaining nonvolatility.

Using III-V dielectric metasurfaces, we experimentally demonstrate resonantly enhanced harmonic generations up to the 4th order. Moreover, we observe large enhancements and spectral tailoring of the photoluminescence of quantum dots embedded inside dielectric metasurfaces.

Emerging novel architectures for shared memory parallel computing are incorporating increasingly creative innovations to deliver higher memory performance. A notable exemplar of this phenomenon is the Multi-Channel DRAM (MCDRAM) that is included in the Intel® XeonPhi™ processors. In this paper, we examine techniques to use OpenMP to exploit the high bandwidth of MCDRAM by staging data. In particular, we implement double buffering using OpenMP sections and tasks to explicitly manage movement of data into MCDRAM. We compare our double-buffered approach to a non-buffered implementation and to Intel’s cache mode, in which the system manages the MCDRAM as a transparent cache. We also demonstrate the sensitivity of performance to parameters such as dataset size and the distribution of threads between compute and copy operations.

Accident scenarios in nuclear power plants that bypass containment have the potential for large and early releases of radionuclides. They are typically guarded against using means such as redundant valves arranged in series and interlocks for systems that interface with the high pressure reactor coolant system. Some of these preventative arrangements rely on active systems that may fail in unique ways with the introduction of digital instrumentation and control. A hypothetical scenario in a pressurized water reactor plant is examined in which the digital controllers for the residual heat removal system intake valves are subjected to a common cause failure. This failure may cause simultaneous unintended valve opening while the reactor is at power, which has the potential to overpressurize and damage piping in the residual heat removal system and cause a leak of primary system water past containment into the auxiliary building (interfacing system loss of coolant accident). If the controllers are in a persistent fault condition, plant personnel will have to traverse the potentially contaminated auxiliary building to override at least one controller and close its associated valve. A dynamic case is assembled and run using the ADAPT dynamic event tree driver and the MELCOR severe accident analysis code in which uncertainties in the progression of the accident as well as mitigating operator actions are explored for an interfacing systems loss of coolant accident initiator. The results are assessed using recently-developed tools to gain insight into the likely outcomes and key events.

We experimentally investigate a new class of quasi-aperiodic structures for improving the emission pattern in nanowire arrays. Efficient normal emission, as well as lasing, can be obtained from III-nitride photonic crystal (PhC) nanowire arrays that utilize slow group velocity modes near the G-point in reciprocal space. However, due to symmetry considerations, the emitted far-field pattern of such modes are often 'donut'-like. Many applications, including lighting for displays or lasers, require a more uniform beam profile in the far-field. Previous work has improved far-field beam uniformity of uncoupled modes by changing the shape of the emitting structure. However, in nanowire systems, the shape of nanowires cannot always be arbitrarily changed due to growth or etch considerations. Here, we investigate breaking symmetry by instead changing the position of emitters. Using a quasi-aperiodic geometry, which changes the emitter position within a photonic crystal supercell (2x2), we are able to linearize the photonic bandstructure near the G-point and greatly improve emitted far-field uniformity. We realize the III-nitride nanowires structures using a top-down fabrication procedure that produces nanowires with smooth, vertical sidewalls. Comparison of room-temperature micro-photoluminescence (μ-PL) measurements between periodic and quasi-aperiodic nanowire arrays reveal resonances in each structure, with the simple periodic structure producing a donut beam in the emitted far-field and the quasi-aperiodic structure producing a uniform Gaussian-like beam. We investigate the input pump power vs. output intensity in both systems and observe the simple periodic array exhibiting a non-linear relationship, indicative of lasing. We believe that the quasi-aperiodic approach studied here provides an alternate and promising strategy for shaping the emission pattern of nanoemitter systems.

We have integrated an ultrahigh mobility twodimensional electron gas with a high-quality-factor terahertz photonic cavity. With a quantizing magnetic field and at low temperatures, we demonstrated collective nonperturbative coupling of the electron cyclotron resonance with terahertz cavity photons with a high cooperativity. Due to the suppression of superradiance-induced broadening of cyclotron resonance by the high-quality-factor cavity, our hybrid quantum system exhibited unprecedentedly sharp polariton lines and a large vacuum Rabi splitting simultaneously.

Time-resolved particle image velocimetry (PIV) was conducted at 40 kHz using a pulse-burst laser in the supersonic wake of a wall-mounted hemisphere. Velocity fields suggest a recirculation region with two lobes in which flow moves away from the wall near centerline and recirculates back towards the hemisphere off centerline. Spatio-temporal cross-correlations and conditional ensemble averages relate the characteristic behavior of the unsteady shock motion to the flapping of the shear layer. At Mach 1.5, oblique shocks form associated with vortical structures in the shear layer and convect downstream in tandem; a weak periodicity is observed. Shock motion at Mach 2.0 appears somewhat different, wherein multiple weak disturbances propagate from shear layer turbulent structures to form an oblique shock that ripples as these vortices pass by. Bifurcated shock feet coalesce and break apart without evident periodicity. Power spectra show a preferred frequency of shear layer flapping and shock motion for Mach 1.5, but at Mach 2.0 a weak preferred frequency is found only for the oblique shock motion and not the shear layer unsteadiness.

Optical coatings deposited using electron beam evaporation are subject to aging effects that change the spectral characteristics of the optical coating. The aim of this study was to determine whether aging effects can also negatively impact the laser damage resistance of an optical coating. Maintaining high resistance to laser damage is particularly important for the performance of high fluence laser systems. In 2013, we deposited different high reflection coatings for 1054 nm containing HfO2/TiO2/SiO2 layers. For this study, we re-measured the laser damage thresholds of these coatings at 3.5 ns to determine if aging effects cause the laser damage threshold to decline, and to compare whether HfO2 or TiO2 is superior in terms of long-term laser damage resistance.

With the growing complexity and scale of high performance computing (HPC) systems, application performance variation has become a significant challenge in efficient and resilient system management. Application performance variation can be caused by resource contention as well as software- and firmware-related problems, and can lead to premature job termination, reduced performance, and wasted compute platform resources. To effectively alleviate this problem, system administrators must detect and identify the anomalies that are responsible for performance variation and take preventive actions. However, diagnosing anomalies is often a difficult task given the vast amount of noisy and high-dimensional data being collected via a variety of system monitoring infrastructures. In this paper, we present a novel framework that uses machine learning to automatically diagnose previously encountered performance anomalies in HPC systems. Our framework leverages resource usage and performance counter data collected during application runs. We first convert the collected time series data into statistical features that retain application characteristics to significantly reduce the computational overhead of our technique. We then use machine learning algorithms to learn anomaly characteristics from this historical data and to identify the types of anomalies observed while running applications. We evaluate our framework both on an HPC cluster and on a public cloud, and demonstrate that our approach outperforms current state-of-the-art techniques in detecting anomalies, reaching an F-score over 0.97.

The Craig-Bampton approach for component mode synthesis in structural dynamics has been widely used to reduce the order of large, detailed finite element models made from linear elastic materials. This methodology separates the full order model into smaller subcomponents and reduces the equations of motion with a truncated set of fixed-interface modes and static constraint modes. A drawback of this approach is that the model has one constraint mode for every interface degree-of-freedom, which may result in a large and prohibitively costly superelement. Previous work has addressed this issue via characteristic constraint modes, which reduces the number of interface degrees-of-freedom by performing a secondary modal analysis on the interface partition. The current work extends the Craig-Bampton approach with interface reduction to include subcomponents with linear viscoelastic materials modeled using a Prony series. For substructures containing materials such as foams or polymers, the viscoelastic constitutive law more accurately represents the material energy dissipation compared to traditional viscous or modal damping. The new approach will be demonstrated on the assembly of two composite plates with fixed boundary conditions along one edge.

Abstract not provided.

During 2016, nuclear criticality safety (NCS) practitioners from SNL and code developers from LANL collaborated in several areas of interest to the DOE/NNSA Nuclear Criticality Safety Program (NCSP). This collaboration involved. Testing of the preliminary release of the MCNP6- Whisper methodology, with feedback to the developers, Sharing of the benchmark catalogs (the collection of MCNP input files and benchmark results), with 1101 cases from LANL and 866 cases from SNL, Comparison and analysis of 357 benchmarks common to both catalogs, Investigation of the impact of the different benchmark catalogs on sensitivity-uncertainty based NCS validation results from MCNP6-Whisper, Investigation of the impact of randomized selections from the benchmark catalog on sensitivity-uncertainty based validation results from MCNP6-Whisper. Investigation of the use of MCNP6-Whisper in selecting benchmarks for use in NCS validation for unique, nonstandard, legacy fuel applications. This paper summarizes the collaboration work and initial results. It must be noted that the results described herein are preliminary and need further research and detailed analysis. However, the initial results are very interesting, and it is important to share them with the NCSP community.

The reaction of OH with H2 is a crucial chain-propagating step in the H2-O2 system thus making the specification of its rate, and its uncertainty, important for predicting the high-temperature combustion of hydrocarbons. In order to obtain an uncertain representation of this reaction rate in the absence of actual experimental data, we perform an inference procedure employing maximum entropy and approximate Bayesian computation methods to discover hypothetical data from a target shock-tube experiment designed to measure the reverse reaction rate. This method attempts to invert the fitting procedure from noisy measurement data to parameters, with associated uncertainty specifications, to arrive at candidate noisy data sets consistent with these reported parameters and their uncertainties. The uncertainty structure of the Arrhenius parameters is obtained by fitting each hypothetical data set in a Bayesian framework and pooling the resulting joint parameter posterior densities to arrive at a consensus density. We highlight the advantages of working with a data-centric representation of the experimental uncertainty with regards to model choice and consistency, and the ability for combining experimental evidence from multiple sources. Finally, we demonstrate the utility of knowledge of the joint Arrhenius parameter density for performing predictive modeling of combustion systems of interest.

Optical coatings deposited using electron beam evaporation are subject to aging effects that change the spectral characteristics of the optical coating. The aim of this study was to determine whether aging effects can also negatively impact the laser damage resistance of an optical coating. Maintaining high resistance to laser damage is particularly important for the performance of high fluence laser systems. In 2013, we deposited different high reflection coatings for 1054 nm containing HfO2/TiO2/SiO2 layers. For this study, we re-measured the laser damage thresholds of these coatings at 3.5 ns to determine if aging effects cause the laser damage threshold to decline, and to compare whether HfO2 or TiO2 is superior in terms of long-term laser damage resistance.

Although many optical-quality glass materials are available for use in optical systems, the range of polymeric materials is limited. Polymeric materials have some advantages over glass when it comes to large-scale manufacturing and production. In smaller scale systems, they offer a reduction in weight when compared to glass counterparts. This is especially important when designing optical systems meant to be carried by hand. We aimed to expand the availability of polymeric materials by exploring both crown-like and flint-like polymers. In addition, rapid and facile production was also a goal. By using UV-cured thiolene-based polymers, we were able to produce optical materials within seconds. This enabled the rapid screening of a variety of polymers from which we down-selected to produce optical flats and lenses. We will discuss problems with production and mitigation strategies in using UV-cured polymers for optical components. Using UV-cured polymers present a different set of problems than traditional injection-molded polymers, and these issues are discussed in detail. Using these produced optics, we integrated them into a modified direct view optical system, with the end goal being the development of drop-in replacements for glass components. This optical production strategy shows promise for use in lab-scale systems, where low-cost methods and flexibility are of paramount importance.

Here we report for the first time the feasibility of using metal-organic frameworks (MOFs) as electrodes for aqueous Na-ion batteries. We show that Fe-MIL-100, a known redox-active MOF, is electrochemically active in a Na aqueous electrolyte, under various compositions. Emphasis was placed on investigating the electrode-electrolyte interface, with a focus on identifying the relationship between additives in the composition of the working electrode, particle size and overall performance. We found that the energy storage capacity is primarily dependent on the binder additive in the composite; the best activity for this MOF is obtained with Nafion as a binder, owing to its hydrophilic and ion conducting nature. Kynar-bound electrodes are clearly less effective, due to their hydrophobic character, which impedes wetting of the electrode. The binder-free systems show the poorest electrochemical activity. There is little difference in the overall performance as function of particle size (micro vs. nano), implying the storage capacities in this study are not limited by ionic and/or electronic conductivity. Excellent reversibility and high coulombic efficiency are achieved at higher potential ranges, observed after cycle 20. That is despite progressive capacity decay observed in the initial cycles. Importantly, structural analyses of cycled working electrodes confirm that the long range crystallinity remains mainly unaltered with cycling. These findings suggest that limited reversibility of the intercalated Na ions in the lower potential range, together with the gradual lack of available active sites in subsequent cycles is responsible for the rapid decay in capacity retention.

The intent of this work is to highlight the role of differential and integral data evaluation to address issues in connection with criticality safety applications. Demonstration is made by using, as an example, differential data measurements and evaluation, and the benchmark integral experiments for titanium. Energy-differential data are measured analyzed and evaluated to produce nuclear data libraries for criticality safety applications. Alternatively, integral experiments are performed at critical facilities, small experimental reactors, and play an important part in the validation of the differential nuclear data. The demonstration provided here for titanium gives its importance to criticality safety. Titanium is an effective neutron absorber that serves as baseline material for chemical separation in high-activity waste solutions in US. Titanium has not been considered for use in nuclear applications such as reactor design and analysis. Rather, it appears as a structural material that may be present in fuel cycle facilities or canisters for transport and disposition of nuclear waste. Criticality safety evaluations of systems in which titanium is present require an understanding of the nuclear data and its uncertainty.

A simple procedure has been developed to create palladium (Pd) films on the surface of several common polymers used in commercial fused deposition modeling (FDM) and stereolithography (SLA) based three-dimensional (3D) printing by an electroless deposition process. The procedure can be performed at room temperature, with equipment less expensive than many 3D printers, and occurs rapidly enough to achieve full coverage of the film within a few minutes. 3D substrates composed of dense logpile or cubic lattices with part sizes in the mm to cm range, and feature sizes as small as 150 μm were designed and printed using commercially available 3D printers. The deposition procedure was successfully adapted to show full coverage in the lattice substrates. The ability to design, print, and metallize highly ordered three-dimensional microscale structures could accelerate development of a range of optimized chemical and mechanical engineering systems.

Manufacturing of integrated circuits (ICs) using a split foundry process expands design space in IC fabrication by employing unique capabilities of multiple foundries and provides added security for IC designers [1] Defect localization and root cause analysis is critical to failure identification and implementation of corrective actions. In addition to split-foundry fabrication, the device addressed in this publication is .comprised of 8 metal layers, aluminum test pads, and tungsten thru-silicon vias (TSVs) making the circuit area > 68% metal. This manuscript addresses the failure analysis efforts involved in root cause analysis, failure analysis findings, and the corrective actions implemented to eliminate these failure mechanisms from occurring in future product.

Abstract not provided.

One of the more common forms of passive vibration isolation in mechanical systems has been the use of elastomeric or foam pads. Cellular silicone foam is one such example which has been used for vibration isolation and mitigating the effects of mechanical shock. There are many desirable properties of cellular silicone, including its resilience and relative insensitivity to environmental extremes. However, there is very little test data that is useful for understanding its dynamic characteristics or for the development of a predictive finite element model. The problem becomes increasingly difficult since foam materials typically exhibit nonlinear damping and stiffness characteristics. In this paper we present a test fixture design and method for extraction of a few dynamic properties of one type of cellular silicone foam pad. The nonlinear damping characteristics derived from the experimental testing are then used to attempt to improve the predictive capability of a linear finite element model of the system. Difficulties and lessons learned are also presented.

One nearly ubiquitous, but often overlooked, source of measurement error in Digital Image Correlation (DIC) arises from imaging through heat waves. “Heat waves” is a colloquial term describing a heterogeneous refractive index field caused by temperature (and thus density) gradients in air. Many sources of heat waves exist in a typical DIC experiment, including hot lights, a heated sample, sunlight, or even a hot camera. This paper presents a detailed description of the error introduced to DIC measurements as a result of heat sources being present in the system. We present characteristic spatial and temporal frequencies of heat waves, and explore the relationships between the location of the heat source, the focal length of the lens, and the stand-off distance between the camera and the imaged object. Finally, we conclude with suggested methods of mitigating the effects of heat waves first by careful design of the experiment and second through data processing. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy’s National Nuclear Security Administration under contract No. DE-AC04-94AL85000.

Predicted lateral power device performance as a function of alloy composition is characterized by a standard lateral device figure-of-merit (LFOM) that depends on mobility, critical electric field, and sheet carrier density. The paper presents calculations of AlGaN electron mobility in lateral devices such as HEMTs across the entire alloy composition range. Alloy scattering and optical polar phonon scattering are the dominant mechanisms limiting carrier mobility. Due to the significant degradation of mobility from alloy scattering, at room temperature Al fractions greater than about 85% are required for improved LFOM relative to GaN using a conservative sheet charge density of 1 × 1013 cm−2. However, at higher temperatures at which AlGaN power devices are anticipated to operate, this “breakeven” composition decreases to about 65% at 500 K, for example. For high-frequency applications, the Johnson figure-of-merit (JFOM) is the relevant metric to compare potential device performance across materials platforms. At room temperature, the JFOM for AlGaN alloys is predicted to surpass that of GaN for Al fractions greater than about 40%.

The finite element method has revolutionized structural analysis since its inception over 50 years ago, by enabling the computer analysis of geometrically complex structures. The main requirement of the finite element method is that an appropriate partition, or mesh, of the structure be created first. The elements of the partition typically have standard shapes, such as the hexahedron, pentahedron, and tetrahedron. While this small library of standard element shapes is sufficient for many applications, there is a growing need for more general polyhedral shapes, ones that can have an arbitrary number of vertices, edges, and faces, and ones that can be non-convex. In this chapter, we discuss current and possible future applications of polyhedral finite elements in solid mechanics. These applications include rapid engineering analysis through novel meshing and discretization techniques, and fracture and fragmentation modeling. Several finite element formulations of general polyhedra have been developed. In this chapter we use a polyhedral formulation based on the use of harmonic shape functions. Harmonic shape functions are one example of several possible generalized barycentric coordinates, as discussed in Chapter 1.

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.

Broad bandwidth coatings allow angle of incidence flexibility and accommodate spectral shifts due to aging and water absorption. Higher refractive index materials in optical coatings, such as TiO2, Nb2O5, and Ta2O5, can be used to achieve broader bandwidths compared to coatings that contain HfO2 high index layers. We have identified the deposition settings that lead to the highest index, lowest absorption layers of TiO2, Nb2O5, and Ta2O5, via e-beam evaporation using ion-assisted deposition. We paired these high index materials with SiO2 as the low index material to create broad bandwidth high reflection coatings centered at 1054 nm for 45 deg angle of incidence and P polarization. High reflection bandwidths as large as 231 nm were realized. Laser damage tests of these coatings using the ISO 11254 and NIF-MEL protocols are presented, which revealed that the Ta2O5/SiO2 coating exhibits the highest resistance to laser damage, at the expense of lower bandwidth compared to the TiO2/SiO2 and Nb2O5/SiO2 coatings.

When an optical coating is damaged, deposited incorrectly, or is otherwise unsuitable, the conventional method to restore the optic often entails repolishing the optic surface, which can incur a large cost and long lead time. We propose three alternative options to repolishing, including (i) burying the unsuitable coating under another optical coating, (ii) using ion milling to etch the unsuitable coating completely from the optic surface and then recoating the optic, and (iii) using ion milling to etch through a number of unsuitable layers, leaving the rest of the coating intact, and then recoating the layers that were etched. Repairs were made on test optics with dielectric mirror coatings according to the above three options. The mirror coatings to be repaired were quarter wave stacks of HfO2 and SiO2 layers for high reflection at 1054 nm at 45 deg incidence in P-polarization. One of the coating layers was purposely deposited incorrectly as Hf metal instead of HfO2 to evaluate the ability of each repair method to restore the coating's high laser-induced damage threshold (LIDT) of 64.0 J/cm2. The repaired coating with the highest resistance to laser-induced damage was achieved using repair method (ii) with an LIDT of 49.0 to 61.0 J/cm2.

When an optical coating is damaged, deposited incorrectly, or is otherwise unsuitable, the conventional method to restore the optic often entails repolishing the optic surface, which can incur a large cost and long lead time. We propose three alternative options to repolishing, including (i) burying the unsuitable coating under another optical coating, (ii) using ion milling to etch the unsuitable coating completely from the optic surface and then recoating the optic, and (iii) using ion milling to etch through a number of unsuitable layers, leaving the rest of the coating intact, and then recoating the layers that were etched. Repairs were made on test optics with dielectric mirror coatings according to the above three options. The mirror coatings to be repaired were quarter wave stacks of HfO2 and SiO2 layers for high reflection at 1054 nm at 45 deg incidence in P-polarization. One of the coating layers was purposely deposited incorrectly as Hf metal instead of HfO2 to evaluate the ability of each repair method to restore the coating's high laser-induced damage threshold (LIDT) of 64.0 J/cm². The repaired coating with the highest resistance to laser-induced damage was achieved using repair method (ii) with an LIDT of 49.0 to 61.0 J/cm².

A conceptual model for turbulent ignition in high-pressure spray flames is presented. The model is motivated by first-principles simulations and optical diagnostics applied to the Sandia n-dodecane experiment. The combined analysis established a conceptual model for turbulent ignition in high-pressure spray flames which is based on a set of identified characteristic time scales. The suddenly forming steep gradients from successful high-temperature ignition initiate the propagation of a turbulent flame. It rapidly ignites the entire spray head on time scales which are generally significantly smaller than the corresponding cool flame wave time scales.

We propose, theoretically investigate, and numerically validate an algorithm for the Monte Carlo solution of least-squares polynomial approximation problems in a collocation framework. Our investigation is motivated by applications in the collocation approximation of parametric functions, which frequently entails construction of surrogates via orthogonal polynomials. A standard Monte Carlo approach would draw samples according to the density defining the orthogonal polynomial family. Our proposed algorithm instead samples with respect to the (weighted) pluripotential equilibrium measure of the domain, and subsequently solves a weighted least-squares problem, with weights given by evaluations of the Christoffel function. We present theoretical analysis to motivate the algorithm, and numerical results that show our method is superior to standard Monte Carlo methods in many situations of interest.

Motivated by applications in risk management of computational systems, we focus our attention on a special case of the partial vertex cover problem, where the underlying graph is assumed to be a tree. Here, we consider four possible versions of this setting, depending on whether vertices and edges are weighted or not. Two of these versions, where edges are assumed to be unweighted, are known to be polynomial-time solvable. However, the computational complexity of this problem with weighted edges, and possibly with weighted vertices, has not been determined yet. The main contribution of this paper is to resolve these questions by fully characterizing which variants of partial vertex cover remain intractable in trees, and which can be efficiently solved. In particular, we propose a pseudo-polynomial DP-based algorithm for the most general case of having weights on both edges and vertices, which is proven to be NP-hard. This algorithm provides a polynomialtime solution method when weights are limited to edges, and combined with additional scaling ideas, leads to an FPTAS for the general case. A secondary contribution of this work is to propose a novel way of using centroid decompositions in trees, which could be useful in other settings as well.

Ubiquitous in rotating machinery, flywheels smooth the flow of energy in rotary systems ranging from small engines to large reciprocating machines. A new class of standalone flywheel energy storage system has been in use since the late 20th century. These systems are electrically connected to the applications that they serve. They may be found in applications as diverse as uninterruptible power supplies, racecars, and large physics research facilities. This chapter presents the theoretical and practical foundations of flywheel design, the history of flywheels from ancient times to the present, flywheel subsystem technology, and a survey of applications where flywheel energy storage systems are currently in service.

Product formation, in particular ketohydroperoxide formation and decomposition, were investigated in time-resolved, Cl-atom initiated neopentane oxidation experiments in the temperature range 550-675 K using a photoionization time-of-flight mass spectrometer. Ionization light was provided either by Advanced Light Source tunable synchrotron radiation or ∼10.2 eV fixed energy radiation from a H2-discharge lamp. Experiments were performed both at 1-2 atm pressure using a high-pressure reactor and also at ∼9 Torr pressure employing a low-pressure reactor for comparison. Because of the highly symmetric structure of neopentane, ketohydroperoxide signal can be attributed to a 3-hydroperoxy-2,2-dimethylpropanal isomer, i.e. from a γ-ketohydroperoxide (γ-KHP). The photoionization spectra of the γ-KHP measured at low- and high pressures and varying oxygen concentrations agree well with each other, further supporting they originate from the single isomer. Measurements performed in this work also suggest that the "Korcek" mechanism may play an important role in the decomposition of 3-hydroperoxy-2,2-dimethylpropanal, especially at lower temperatures. However, at higher temperatures where γ-KHP decomposition to hydroxyl radical and oxy-radical dominates, oxidation of the oxy-radical yields a new important channel leading to acetone, carbon monoxide, and OH radical. Starting from the initial neopentyl + O2 reaction, this channel releases altogether three OH radicals. A strongly temperature-dependent reaction product is observed at m/z = 100, likely attributable to 2,2-dimethylpropanedial.

Energy storage (ES) is a pivotal technology for dealing with the challenges caused by the integration of renewable energy sources. It is expected that a decrease in the capital cost of storage will eventually spur the deployment of large amounts of ES. These devices will provide transmission services, such as spatiotemporal energy arbitrage, i.e., storing surplus energy from intermittent renewable sources for later use by loads while reducing the congestion in the transmission network. This paper proposes a bilevel program that determines the optimal location and size of storage devices to perform this spatiotemporal energy arbitrage. This method aims to simultaneously reduce the system-wide operating cost and the cost of investments in ES while ensuring that merchant storage devices collect sufficient profits to fully recover their investment cost. The usefulness of the proposed method is illustrated using a representative case study of the ISO New England system with a prospective wind generation portfolio.

In this column, the guest editors introduce the six articles in the special issue on Architectures for the Post-Moore Era.

In various applications with recirculation, liquid droplets can be immersed in gases that may have a wide range of possible compositions, from pure air to hot combustion products. In order to gain fundamental understanding of the behaviour of individual droplets in vitiated air, numerical simulations of kerosene single droplet evaporation, autoignition, and combustion in conditions relevant to gas turbines have been performed. The droplet autoignition behaviour has been analysed in both physical and mixture fraction space for a wide range of vitiated air compositions and initial droplet diameters. Results show that the autoignition time delay decreases with increasing level of dilution with hot combustion products and decreasing initial droplet diameter. Chemistry is confined up to a radius of almost 10 initial droplet diameters and the location of autoignition is influenced by both the initial droplet diameter and the level of dilution. The time evolution of species in the gaseous phase after autoignition shows similar trends for all the diameters and dilution levels investigated here with the peak of temperature and OH mass fraction moving towards the droplet surface as a consequence of the balance between fuel production and consumption. In mixture fraction space, the location of the peaks of temperature and OH mass fraction after autoignition do not change in time whereas other intermediate species such as CH2O and pyrolysis products still exhibit a quite variable behaviour. The long-time flame structure has been compared with gaseous laminar counterflow simulations and, although qualitatively similar, the flame structure in the two configurations has differences with implications for flamelet combustion models used in spray combustion. The droplet evaporation, autoignition, and combustion behaviour has been summarized through a regime diagram showing the evaporation and autoignition time delays as a function of both initial droplet diameter and vitiated air dilution. This allows the identification of different states in the droplet combustion scenario and the introduction of critical values of dilution and initial droplet diameter beyond which single droplet rather than cloud combustion can occur, which can be exploited in the design of lean burn gas turbine combustion systems. The approach presented here can be easily extended to other conditions and fuels allowing the generation of regime diagrams for various operating conditions.

The synthesis of a series of lanthanide trifluoroacetic acid (H-TFA) derivatives which contain only the TFA and its conjugate acid has been developed. From the reaction of Ln(N(SiMe3)2)3 with an excess amount of H-TFA, the products were identified as: [Ln(μ-TFA)3(H-TFA)2]n (Ln = Y, Ce, Sm, Eu, Gd, Tb, Dy), [Ln(μ-TFA)3(μ-H-TFA)]n·solv (Ln·solv = Pr·2 H-TFA, H3O+, Ho·2py, Er·py, Yb·py, H-TFA), 3[H][(TFA)La(μ-TFA)3La(TFA)(μ-TFA)2(μc-TFA)2]n ½(H2O) ½(H2O, H-TFA) (La·½(H2O) ½(H2O, H-TFA)), [(k2-TFA)Nd(μ-TFA)3]n·H-py+ (Nd·H-py+), [(py)2Tm(μ-TFA)3]n (Tm), or [Lu(μ-TFA)4Lu(μ-TFA)3·H3O+]n (Lu·H3O+). The majority of samples formed long chain polymers with 3 or 4 μ-TFA ligands. Tm was isolated with py coordinated to the metal, whereas Ho, Er, and Yb were isolated with py located within the lattice. Select samples from this set of compounds were used to generate nanomaterials under solvothermal (SOLVO) conditions using pyridine (py) or octylamine at 185 °C for 24 h. The SOLVO products were isolated as: (i) from py: La – fluocerite (LaF3, PDF 98-000-0214, R = 9.64%, 35(0) nm), Tb – terbium fluoride (TbF3, PDF 00-037-1487, R = 4.76%, 21(2) nm), Lu lutetium oxy fluoride (LuOF, PDF 00-052-0779, R = 8.24%, 8(2) nm); (ii) from octylamine: La – fluocerite/lanthanum oxide carbonate (LaF3, PDF 98-000-0214, R = 7.47%, 5(0) nm; La2O2(CO3), PDF 01-070-5539, R = 12.32%, 12(0) nm), Tb – terbium oxy fluoride (TbOF, PDF 00-008-0230, R = 7.01%, 5(0) nm); Lu – lutetium oxide (Lu2O3, PDF 00-012-0728, R = 6.52%, 6(1) nm).

A detailed kinetic model comprising low- and high-temperature reaction pathways capable of predicting the combustion characteristics of cyclopentane was studied. The simulations reproduced the unique reactivity trend of cyclopentane and the measured concentration profiles of intermediate and product species. Simulation results agreed with the experiments and both showed an increase in reactivity with increasing temperature at φ = 0.5 1.0 and 1.5. For richer conditions cyclopentane concentration profiles exhibit inhibition of reactivity between 850 and 1000 K.

SymPy is an open source computer algebra system written in pure Python. It is built with a focus on extensibility and ease of use, through both interactive and programmatic applications. These characteristics have led SymPy to become a popular symbolic library for the scientific Python ecosystem. This paper presents the architecture of SymPy, a description of its features, and a discussion of select domain specific submodules. The supplementary materials provide additional examples and further outline details of the architecture and features of SymPy.

Transported probability density function (TPDF) methods are an attractive modeling approach for turbulent flames as chemical reactions appear in closed form. However, molecular micro-mixing needs to be modeled and this modeling is considered a primary challenge for TPDF methods. In the present study, a new algebraic mixing rate model for TPDF simulations of turbulent premixed flames is proposed, which is a key ingredient in commonly used molecular mixing models. The new model aims to properly account for the transition in reactive scalar mixing rate behavior from the limit of turbulence-dominated mixing to molecular mixing behavior in flamelets. An a priori assessment of the new model is performed using direct numerical simulation (DNS) data of a lean premixed hydrogen–air jet flame. The new model accurately captures the mixing timescale behavior in the DNS and is found to be a significant improvement over the commonly used constant mechanical-to-scalar mixing timescale ratio model. An a posteriori TPDF study is then performed using the same DNS data as a numerical test bed. The DNS provides the initial conditions and time-varying input quantities, including the mean velocity, turbulent diffusion coefficient, and modeled scalar mixing rate for the TPDF simulations, thus allowing an exclusive focus on the mixing model. The new mixing timescale model is compared with the constant mechanical-to-scalar mixing timescale ratio coupled with the Euclidean Minimum Spanning Tree (EMST) mixing model, as well as a laminar flamelet closure by Pope and Anand (1984). It is found that the laminar flamelet closure is unable to properly capture the mixing behavior in the thin reaction zones regime while the constant mechanical-to-scalar mixing timescale model under-predicts the flame speed. The EMST model coupled with the new mixing timescale model provides the best prediction of the flame structure and flame propagation among the models tested, as the dynamics of reactive scalar mixing across different flame regimes are appropriately accounted for.

The mechanism(s) of low salinity water flooding (LSWF) must be better understood at high temperatures and pressures if the method is to be applied in high T/P kaolinite-bearing sandstone reservoirs. We measured contact angles between a sandstone and an oil (acid number, AN = 3.98 mg KOH/g, base number, BN = 1.3 mg KOH/g) from a reservoir in the Tarim Field in western China in the presence of various water chemistries. We examined the effect of aqueous ionic solutions (formation brine, 100X diluted formation brine, and softened water), temperature (60, 100 and 140 °C) and pressure (20, 30, 40, and 50 MPa) on the contact angle. We also measured the zeta potential of the oil/water and water/rock interfaces to calculate oil/brine/rock disjoining pressures. A surface complexation model was developed to interpret contact angle measurements and compared with DLVO theory predictions. Contact angles were greatest in formation water, followed by the softened water, and low salinity water at the same pressure and temperature. Contact angles increased slightly with temperature, whereas pressure had little effect. DLVO and surface complexation modelling predicted similar wettability trends and allow reasonably accurate interpretation of core-flood results. Water chemistry has a much larger impact on LSWF than reservoir temperature and pressure. Low salinity water flooding should work in high temperature and high pressure kaolinite-bearing sandstone reservoirs.

Mg(BH4)2 is a promising solid-state hydrogen storage material, releasing 14.9 wt% hydrogen upon conversion to MgB2. Although several dehydrogenation pathways have been proposed, the hydrogenation process is less well understood. Here, we present a joint experimental-theoretical study that elucidates the key atomistic mechanisms associated with the initial stages of hydrogen uptake within MgB2. Fourier transform infrared, X-ray absorption, and X-ray emission spectroscopies are integrated with spectroscopic simulations to show that hydrogenation can initially proceed via direct conversion of MgB2 to Mg(BH4)2 complexes. The associated energy landscape is mapped by combining ab initio calculations with barriers extracted from the experimental uptake curves, from which a kinetic model is constructed. The results from the kinetic model suggest that initial hydrogenation takes place via a multi-step process: molecular H2 dissociation, likely at Mg-terminated MgB2 surfaces, is followed by migration of atomic hydrogen to defective boron sites, where the formation of stable B-H bonds ultimately leads to the direct creation of Mg(BH4)2 complexes without persistent BxHy intermediates. Implications for understanding the chemical, structural, and electronic changes upon hydrogenation of MgB2 are discussed.

In recent years a rich variety of emergent phenomena have been observed when suspensions of magnetic particles are subjected to alternating magnetic fields. These particle assemblies often exhibit vigorous dynamics due to the injection of energy from the field. These assemblies include surface and interface phenomena, such as highly organized, segmented "snakes" that can be induced to swim by structural symmetry breaking, and "asters" and "anti-asters," particle assemblies that can be manipulated to capture and transport cargo. In bulk suspensions of magnetic platelets subjected to multiaxial alternating fields, advection lattices and even vortex lattices have been created, and a variety of biomimetic dynamics-serpents, bees and amoebas-have been discovered in magnetic fluids suspended in an immiscible liquid. In this paper several new driven phases are presented, including flying chevrons, dense spinning clusters, filaments, and examples of phase coexistence in driven phases. These observations broaden the growing field of driven magnetic suspensions and present new challenges to those interested in simulating the dynamics of these complex systems.

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. We also provide plausible explanations for what could be the origin of the anomalous pressure.

Robust time-averaged molecular dynamics has been developed to calculate finiteerature elastic constants of a single crystal. We find that when the averaging time exceeds a certain threshold, the statistical errors in the calculated elastic constants become very small. We applied this method to compare the elastic constants of Pd and PdH0.6 at representative low (10 K) and high (500 K) temperatures. The values predicted for Pd match reasonably well with ultrasonic experimental data at both temperatures. In contrast, the predicted elastic constants for PdH0.6 only match well with ultrasonic data at 10 K; whereas, at 500 K, the predicted values are significantly lower. We hypothesize that at 500 K, the facile hydrogen diffusion in PdH0.6 alters the speed of sound, resulting in significantly reduced values of predicted elastic constants as compared to the ultrasonic experimental data. Literature mechanical testing experiments seem to support this hypothesis.

Ionic liquids containing lanthanide halide anions give the opportunity to investigate magnetic behaviour in non-ordered systems. Reported herein is the synthesis and characterization of ionic liquids containing a series of lanthanide halide anions, with the resulting materials displaying unusual behaviour below 50 K. Specifically, the ionic liquid structural glass formation appears to drive magnetic behaviour due to cluster formation of the anions during rapid cooling. This system presents a possible probe to study the dynamics of glass forming materials.

Time-resolved particle image velocimetry recently has been demonstrated in high-speed flows using a pulse-burst laser at repetition rates reaching 50 kHz. Turbulent behavior can be measured at still higher frequencies if the field of view is greatly reduced and lower laser pulse energy is accepted. Current technology allows image acquisition at 400 kHz for sequences exceeding 4,000 frames, but for an array of only 128 × 120 pixels, giving the moniker of “postage-stamp PIV.” The technique has been tested far downstream of a supersonic jet exhausting into a transonic crossflow. Two-component measurements appear valid until 100 kHz at which point a noise floor emerges dependent upon the reduction of peak locking. Stereoscopic measurement offers three-component data for turbulent kinetic energy spectra, but exhibits a reduced signal bandwidth and higher noise in the out-of-plane component due to the oblique camera images. The resulting spectra reveal two regions exhibiting power-law dependence describing the turbulent decay. One is the well-known inertial subrange with a slope of -5/3 at high frequencies. The other displays a -1 power-law dependence for a decade of mid-range frequencies corresponding to the energetic eddies measured by PIV, which appears to have been previously unrecognized for high-speed free shear flows.

The purpose of this report is to briefly survey the major contributions of the FY14- FY16 LDRD project titled “An Advanced Decision Framework for Power Grid Resiliency”. The primary contributions of the project are described in detailed technical reports and journal articles, references to which we provide in a bibliography.

The objective of this project is to measure the hydrogen-affected fracture properties of structural welded metals exposed to hydrogen isotopes. The main goal of FY16 was to evaluate low-temperature effects on fracture properties of stainless steel welds pre-charged with hydrogen. Forged stainless steels consisting of 316L, 304L, and 21-6-9 welded with 308L filler metal were pre-charged and tested at 223 K at select displacement rates to evaluate fracture behavior over the lower STS temperature range. Reductions in fracture thresholds were observed for all stainless steel welds when samples were precharged with hydrogen; however, temperature effects were not observed in the 304L and 21-6-9 welds. Only 316L exhibited enhanced degradation at 223 K. In addition to fracture testing, tensile specimens were extracted from the weld region and tested at 296 K and 223 K in the hydrogen pre-charged condition. A slight increase in yield strength was measured in the pre-charged condition at 296K and 223 K for the three different welds. A reduction in total elongation of 3-11% was observed at 296 K, whereas reductions in total elongation from 50-64% were observed at 223 K. Microhardness and ferrite numbers were measured in the weld regions to try to elucidate the factors affecting fracture. Lastly, in collaboration with Savannah River National Laboratory (SRNL), weld and heat-affected zone bend specimens extracted from forged 304L and 21-6-9 stainless steel were supplied to SRNL and are in the final stages of sample preparation for subsequent tritium exposure, aging, and fracture testing. The collection of testing completed and planned between Sandia and SRNL contributes to the development of a comprehensive database of properties for materials as a function of hydrogen-isotope concentrations.

The objectives of this work are to (1) Develop a detailed understanding of the performance characteristics of current chromate conversion coatings utilized in the stockpile, (2) Develop a detailed understanding of the performance characteristics of non-chromate conversion coatings proposed to replace their chromate containing counterparts, (3) Provide an informed assessment of the aforementioned coatings and a recommended course of action for the replacement of chromate containing coatings, and (4) establish subject matter expertise in the area of replacement coatings to provide as a resource to the systems organization. These tasks will be accomplished by performing a battery of traditional corrosion performance tests (in accordance with the relevant MIL specifications governing chemical conversion coatings), combined with more detailed analytical evaluation of the materials. Coatings will be evaluated in the as-received and artificially aged condition. Four different coating systems were evaluated on four different aluminum alloys in FY16. The focus this year was to continue populating the test matrix initiated in previous years, evaluating key coatings in the as received and thermally stressed condition, as compared to the baseline chromate conversion coating (Bonderite (formerly Alodine) 1200S). The non-chromate conversion coatings included Bonderite T 5900, Chemeon TCP-HF, Luster-On Aluminescent, and MacDermid-Enthone Iridite NCP. A second effort that was completed this year was to address a bottleneck that existed for the electrical evaluation of the coatings, assessing their conformance with the MIL specification. An electromechanical test system was assembled and automated, eliminating the need to rely on an already heavily utilized mechanical test system and operator in Materials Mechanics and Tribology.

The overall objectives are to provide the science-base needed by industry to understand how emerging alternative fuels impact highly efficient DISI light-duty engines being developed by industry and how engine design and operation can be optimized for most efficient use of future fuels.

The overall objectives are to provide the science-base needed by industry stakeholders to understand how engine design and operation can be co-optimized with future fuels for highest overall system efficiency.

This report requests a non-explosive hazard classification of trace explosives in solution. UN Series 1 and 2 explosive hazard classification tests were performed on a simulated worst-case waste stream of five (5) percent by weight of explosive (CL-20) dissolved in a solvent solution (acetone) for transport and storage. The explosive hazard classification test results reported the sample to be non-explosive and the report provides the necessary data for the Department of Transportation to determine and assign the appropriate hazard class for five (5) percent or less of trace explosive in solvent solutions when being shipped and/or stored. Based on the test results, this report requests that the Department of Transportation assign a hazard class of 3, Desensitized explosive liquid, n.o.s. for this type of substance.

The Bird project explored the use of big data analytics tool to improve the findability of information within the Sandia internal network. We were able to perform query classification utilizing the supervised learning algorithms in the Apache Spark library. By relying on the distributed processing capabilities provided by the Apache Hadoop framework, we successfully processed the large query log files needed to train the models in this effort. The capabilities developed in this project are being used to enhance the effectiveness of the enterprise search engine.

This report summarizes the outcome of an expert panel review of a key degradation phenomenon identified for atmospherically exposed austenitic stainless steel containers used for the interim dry storage of used nuclear fuel - specifically, chloride induced stress corrosion cracking due to the presence of atmospherically deposited salts. The expert panel consisted of Dr. Peter Andresen (GE Corp Research & Development), Dr. Robert G. Kelly (University of Virginia), Dr. John R. Scully (University of Virginia), and Dr. Alan Turnbull (National Physical Laboratory) and was moderated by Dr. David G. Enos (Sandia National Laboratories). In addition to the above subject matter experts, participants from Sandia National Laboratories, Savannah River National Laboratory, Pacific Northwest National Laboratory, and the Southwest Research Institute will be present. Input from the panel members for a series of preliminary questions dealing with the subject area, along with the meeting minutes, presentation materials, and final recommendations are included here.

This document describes a conceptual Data Model for use in the IDC Re-Engineering development project.

The thermal degradation of two polyurethane elastomers was investigated via thermal gravimetric analysis coupled with gas chromatography/ma ss spectrometry. Decomposition occur s in a multi - step fashion with similar onset temperatures for both materials. Apparent activation energy plots were calculated inside Model - Free Kinetics software and utilized to construct conversion and isothermal conversion tables . These tables predicted material degradation as a function of temperature and time. Isothermal experiments were performed and found to be in good agreement with the predictions made from the Model - Free Kinetic s software package. Volatile products evolved during the multistep decomposition were captured at various times and analyzed using the coupled gas chromatography/mass spectrometry system . This analysis demonstrated strong correlation between the degradation products and known decomposition mechanisms for polyurethanes.

Abstract not provided.

We recently developed an enzymatically active, ultra-thin, nano-stabilized liquid membrane for CO₂ separation from a mixture of gases, which was recognized by an international R&D 100 Award in 2015. The separation membrane is an approximately 18-nm thick water layer stabilized by capillary condensation within a hydrophilic mesoporous silica film and embedded with the metallo-enzyme carbonic anhydrase. The enzyme speeds CO₂ uptake and release from the membrane by catalyzing the rapid inter-conversion of carbon dioxide and water to bicarbonate and a proton. The membrane separates CO₂ from 1:1 gas mixtures at a rate of 2600 GPU with CO₂/N₂ and CO₂/H₂ selectivities exceeding 788 and 1500, the highest combined flux and selectivity yet reported. That membrane performance exceeds, for the first time, the U.S. Department of Energy standards for CO₂ capture technology. CO₂ flux depends sensitively on nanopore surface chemistry in the active region. To understand that dependence, we applied molecular simulations to interrogate enzyme behavior in the presence of varied surface chemistries. The results indicate that a polar surface chemistry within the membrane nanopores prevents aggregation of enzymes that would otherwise occur in both bulk liquid solution and non-polar nanopores. Additionally, the enzyme active site maintains a stable structure, even when the overall protein structure deforms within the nanopores. In summary, confinement in the ultra-thin layer of water within mesoporous silica nanopores facilitates a 15x higher enzyme concentration than in bulk conditions, without affecting the structure of the enzyme active site, when the nanopore surfaces are covered with polar functional groups. Thus, confinement of the carbonic enzymes in the membrane water-filled nanopores facilitates higher rates of CO₂ uptake and release than achievable in bulk solutions.

SNL’s IDC Reengineering Phase 2 team developed 12 Use Case Realizations (UCRs) during the Elaboration phase. This document describes the changes made to these UCRs after their initial delivery to the IDC.

Sandia National Laboratories has a large cybersecurity research program supporting the Department of Energy as well as other federal departments and agencies. Fundamental research helps us stay ahead of threats. Sandia’s research efforts in cybersecurity are focused in three broad areas: 1. Trusted hardware, software, and systems 2. Networks and systems architectures and analysis 3. Effective cyber defense systems Research is conducted in state-of-the-art facilities with extensive computing and information science capabilities, which range from architectures and algorithms to advanced modeling and simulation. Three areas of active research most applicable to connected vehicle security are: Red Team Assessments, Emulytics™, and Supply Chain Risk Management.

Lithium niobate, due to its material properties, is often used for optical waveguides, optical modulators, and other linear and nonlinear optical applications. In this research, we present monolithically integrated microdisk resonators with an integrated ground plane fabricated from a commercially purchased lithium niobate on insulator wafer. Using this architecture, we demonstrate excitation of a 167MHz mechanical resonance as well as electro-optic modulation of a 1.93THz optical mode in a free-standing whispering gallery mode (WGM) resonator. By hovering a signal probe above the disk while grounding the device using the integrated ground plane, an electric field can be applied across the device which both induces an electro-optic effect as well as drives mechanical motion via the piezoelectric effect. Detection of the mechanical mode and electro-optic shift was performed by coupling to the high quality factor (Q = 454,000) optical modes of the microresonator using a tapered optical fiber.

Understanding the stability of the zircaloy-4 liner, which is used in the Tritium- Producing Burnable Absorber Rod, is important for predicting the maximium reasonable life time and failure mechanisms of this essential component for tritium production. In this year-long study, a combination of in-situ ion irradiation transmission electron microscopy and thermal desorption measurements were used to explore the structural stability of Zr-4 as a function of sequential and concurrent displacement damage, helium implantation, and molecular deuterium implantation at the temperature of interest for reactor operation. Under the limited conditions explored, the liner alloy appeared to be relatively stable based on the direct TEM observation of the microstructure.

This study examined a concept for improving the nation's ability to detect unauthorized transport of radiological and nuclear material that involves detecting not the radiological or nuclear material itself, but rather the anomalous presence of materials, such as lead and tungsten, typically used to shield such illicit materials from detection. Specifically, the project studied a potentially inexpensive, non-intrusive, and fast method of detecting anomalous shielding: use of magnetic induction sensors to measure currents induced in conductors by a driver coil. The first phase of this work, documented in this report, identified the signatures of materials of interest, assessed the usefulness of measured signatures for discrimination between materials, and then benchmarked models and calculations. The next task involved assessing the strength of these signatures when the materials of interest were enclosed within other materials, such as aluminum and steel, of various thicknesses. A final task mimicked a real-world scenario by testing the ability to detect material signatures of interest at a scale of a vehicle or cargo vessel against a cluttered backdrop, with and without the shielding of another material, such as aluminum or steel. This final task raised doubts regarding whether this detection scheme will be useful under real-world conditions.

The Sandia National Laboratories, California (SNL/CA) site comprises approximately 410 acres and is located in the eastern portion of Livermore, Alameda County, California. The property is owned by the United States Department of Energy and is being operated by Sandia Corporation. The facility location is shown on the Site Map(s) in Appendix A. This Stormwater Pollution Prevention Plan (SWPPP) is designed to comply with California’s General Permit for Stormwater Discharges Associated with Industrial Activities (General Permit) Order No. 2014-0057-DWQ (NPDES No. CAS000001) issued by the State Water Resources Control Board (State Water Board) (Ref. 6.1). This SWPPP has been prepared following the SWPPP Template provided on the California Stormwater Quality Association Stormwater Best Management Practice Handbook Portal: Industrial and Commercial (CASQA 2014).

Abstract not provided.

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The purpose of this document is to give further details on modeling than requested in the Excel sheets To analyze the results and draw any conclusion with respect to the vibration modeling purpose.

Abstract not provided.

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This document contains the system specifications derived to satisfy the system requirements found in the IDC System Requirements Document for the IDC Re-Engineering Phase 2 project. This System Specification Document (SSD) defines waveform data processing requirements for the International Data Centre (IDC) of the Comprehensive Nuclear Test Ban Treaty Organization (CTBTO). The routine processing includes characterization of events with the objective of screening out events considered to be consistent with natural phenomena or non-nuclear, man-made phenomena. This document does not address requirements concerning acquisition, processing and analysis of radionuclide data but does include requirements for the dissemination of radionuclide data and products.

This System Requirements Document (SRD) defines waveform data processing requirements for the International Data Centre (IDC) of the Comprehensive Nuclear Test Ban Treaty Organization (CTBTO). The IDC applies, on a routine basis, automatic processing methods and interactive analysis to raw International Monitoring System (IMS) data in order to produce, archive, and distribute standard IDC products on behalf of all States Parties. The routine processing includes characterization of events with the objective of screening out events considered to be consistent with natural phenomena or non-nuclear, man-made phenomena. This document does not address requirements concerning acquisition, processing and analysis of radionuclide data, but includes requirements for the dissemination of radionuclide data and products.