Publications

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The How To Manual supplements the User’s Manual and the Theory Manual. The goal of the How To Manual is to reduce learning time for complex end to end analyses. These documents are intended to be used together. See the User’s Manual for a complete list of the options for a solution case. All the examples are part of the Sierra/SD test suite. Each runs as is. The organization is similar to the other documents: How to run, Commands, Solution cases, Materials, Elements, Boundary conditions, and then Contact. The table of contents and index are indispensable. The Geometric Rigid Body Modes section is shared with the Users Manual.

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The object of this study is to provide an estimate of bounding radionuclide releases from a nuclear power plant accident. The time frame of interest is the release phase from the initiating event through 30 days. The maximum credible initiating event includes an initial failure of the containment function with a primary system leak. All estimates include a complete loss-of-onsite power and no successful mitigative actions. The active safety injection systems are also assumed failed. The review considers the following commonly deployed reactor designs in the following order of interest: RBMK 1000, VVER-440, VVER-1000, 1000 MWe PWR, 1000 MWe BWR, BN-800, and the 600 MWe CANDU/PHWR. The review also considers spent fuel pool accident scenarios.

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In late 2004, the U.S. Nuclear Regulatory Commission (NRC) initiated a project to analyze the relative efficacy of alternative protective action strategies in reducing consequences to the public from a spectrum of nuclear power plant core melt accidents. The study is documented in NUREG/CR-6953, “Review of NUREG-0654, Supplement 3, ‘Criteria for Protective Action Recommendations for Severe Accidents,’” Volumes 1, 2, and 3. The Protective Action Recommendations (PAR) study provided a technical basis for enhancing the protective action guidance contained in Supplement 3, “Guidance for Protective Action Strategies,” to NUREG-0654/FEMA-REP-1, Rev. 1, “Criteria for Preparation and Evaluation of Radiological Emergency Response Plans and Preparedness in Support of Nuclear Power Plants, ” dated November 2011. In the time since, a number of important changes and additions have been made to the MACCS code suite, the nuclear accident consequence analysis code used to perform the study. The purpose of this analysis is to determine whether the MACCS results used in the PAR study would be different given recent changes to the MACCS code suite and input parameter guidance. Updated parameters that were analyzed include cohorts, keyhole evacuation, shielding and exposure parameters, compass sector resolution, and a range of source terms from rapidly progressing accidents. Results indicate that using updated modeling assumptions and capabilities may lead to a decrease in predicted health consequences for those within the emergency planning zone compared to the original PAR study.

In assessing the initial spatial distribution of defects from neutron or heavy ion irradiation, it is useful to have a reliable, automated, and fast-running tool to evaluate characteristic metrics such as the number of sub-clusters or the overall cluster volume. The latter metric, for instance, can be utilized to estimate a reference neutron fluence level at which inter-cluster interaction effects begin to become significant. This paper details a methodology to fit an arbitrarily complex defect map with a set of ellipsoids (one per identified sub-cluster) in which the constituent defects of a sub-cluster are determined using fuzzy degree-of-membership analysis. Specifically, a parameterized model is developed for point defects in gallium arsenide. Cluster volume calculations based on the model are compared against convex hull and single- ellipsoid representations. Results show that the parameterized sub-cluster model begins to deviate from the two reference models at a recoil energy of about 100 keV in GaAs, with the convex hull and single-ellipsoid representations increasingly overestimating the volume thereafter.

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This report summarizes Fiscal Year 2021 accomplishments from Sandia National Laboratories Wind Energy Program. The portfolio consists of funding provided by the DOE EERE Wind Energy Technologies Office (WETO), Advanced Research Projects Agency-Energy (ARPA-E), DOE Small Business Innovation Research (SBIR), and the Sandia Laboratory Directed Research and Development (LDRD) program. These accomplishments were made possible through capabilities investments by WETO, internal Sandia investment, and partnerships between Sandia and other national laboratories, universities, and research institutions around the world.

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Magnesium borohydride (Mg(BH4)2) is a promising candidate for material-based hydrogen storage due to its high hydrogen gravimetric/volumetric capacities and potential for dehydrogenation reversibility. Currently, slow dehydrogenation kinetics and the formation of intermediate polyboranes deter its application in clean energy technologies. In this study, a novel approach for modifying the physicochemical properties of Mg(BH4)2 is described, which involves the addition of reactive molecules in the vapor phase. This process enables the investigation of a new class of additive molecules for material-based hydrogen storage. The effects of four molecules (BBr3, Al2(CH3)6, TiCl4, and N2H4) with varying degrees of electrophilicity are examined to infer how the chemical reactivity can be used to tune the additive-Mg(BH4)2 interaction and optimize the release of hydrogen at lower temperatures. Control over the amounts of additive exposure to Mg(BH4)2 is shown to prevent degradation of the bulk γ-Mg(BH4)2 crystal structure and loss of hydrogen capacity. Trimethylaluminum provides the most encouraging results on Mg(BH4)2, maintaining 97% of the starting theoretical Mg(BH4)2 hydrogen content and demonstrating hydrogen release at 115 °C. These results firmly establish the efficacy of this approach toward controlling the properties of Mg(BH4)2 and provide a new path forward for additive-based modification of hydrogen storage materials.

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National Technology & Engineering Solutions of Sandia, LLC (NTESS) has recently amended the NTESS Savings and Income (401(k) Plan). The updated Summary Plan Description (SPD) for the 401(k) Plan effective January 1, 2022 is provided.

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This report outlines the development of load-mitigating feedback control for wave energy converters. A simple, self-tuning multi-objective controller is demonstrated in simulation for a 3-DOF (surge, heave, pitch) point absorber. In previous work, the proposed control architecture has been shown to be effective in experiment for a variety of device archetypes for the single objective of the maximization of electrical power capture: here this architecture is extended to reduce device loading as well. In particular, PTO actuation forces and the minimization of fatigue damage (determined from the sum of wave-exerted and PTO forces) are considered as additional objectives for the self-tuning controller. This controller is demonstrated for two similar, but distinct systems: one described by the identified linear models from physical testing of the WaveBot device, and another based upon a WEC-Sim simulation that expands upon boundary element method data from the WaveBot device. In both cases, because the power surface is consistently fairly flat in the vicinity of control parameters that maximize power capture in contrasting sea-states, it is found to be generally possible to mitigate either fatigue damage or PTO load. However, PTO load is found to conflict with fatigue damage in some sea-states, limiting the efficacy of control objectives that attempt to mitigate both simultaneously. Additionally, coupling between the surge and pitch DOFs also limits the extent to which fatigue damage can be mitigated for both DOFs in some sea-states. Because control objectives can be considered a function of the sea-state (e.g., load mitigation may not be a concern until the sea is sufficiently large) a simple transition strategy is proposed and demonstrated. This transition strategy is found to be effective with some caveats: firstly, it cannot circumvent the aforementioned objective contradictions. Secondly, this objective transition is too slow to act as a system constraint, and objective thresholds must thus be considered quite conservatively. Improvement of the adjustment strategy is demonstrated through the addition of an integral term. Selection of well-performing transition parameters can be a function of sea-state. While a simple selection procedure is proposed, it is non-optimal, and a more robust selection procedure is suggested for future work.

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The electric grid has undergone rapid, revolutionary changes in recent years; from the addition of advanced smart technologies to the growing penetration of distributed energy resources (DERs) to increased interconnectivity and communications. However, these added communications, access interfaces, and third-party software to enable autonomous control schemes and interconnectivity also expand the attack surface of the grid. To address the gap of DER cybersecurity and secure the grid-edge to motivate a holistic, defense-in-depth approach, a proactive intrusion detection and mitigation system (PIDMS) device was developed to secure PV smart inverter communications. The PIDMS was developed as a distributed, flexible bump-in-the-wire (BITW) solution for protecting PV smart inverter communications. Both cyber (network traffic) and physical (power system measurements) are processed using network intrusion monitoring tools and custom machinelearning algorithms for deep packet analysis and cyber-physical event correlation. The PIDMS not only detects abnormal events but also deploys mitigations to limit or eliminate system impact; the PIDMS communicates with peer PIDMSs at different locations using the MQTT protocol for increased situational awareness and alerting. The details of the PIDMS methodology and prototype development are detailed in this report as well as the evaluation results within a cyber-physical emulation environment and subsequent industry feedback.

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Understanding of semiconductor breakdown under high electric fields is an important aspect of materials’ properties, particularly for the design of power devices. For decades, a power-law has been used to describe the dependence of material-specific critical electrical field (Ecrit) at which the material breaks down and bandgap (Eg). The relationship is often used to gauge tradeoffs of emerging materials whose properties haven’t yet been determined. Unfortunately, the reported dependencies of Ecrit on Eg cover a surprisingly wide range in the literature. Moreover, Ecrit is a function of material doping. Further, discrepancies arise in Ecrit values owing to differences between punch-through and non-punch-through device structures. We report a new normalization procedure that enables comparison of critical electric field values across materials, doping, and different device types. An extensive examination of numerous references reveals that the dependence Ecrit ∝ Eg1.83 best fits the most reliable and newest data for both direct and indirect semiconductors. Graphical abstract: [Figure not available: see fulltext.].

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The Savannah River Site plans to reprocess defense spent nuclear fuel currently stored in their L-Basin via the Accelerated Basin Deinventory (ABD) Program. The previous plan for the L-Basin spent nuclear fuel was to dispose of it directly in the federal repository without reprocessing. Implementing the ABD Program will result in final disposal of approximately 900 fewer canisters of defense spent nuclear fuel and the production of approximately 521 more canisters of vitrified high-level waste glass with some specific differences from the planned high-level waste glass. Because the 235U in the L-Basin spent nuclear fuel is not intended to be recovered, the fissile mass loading of the vitrified high-level glass waste form to be produced must be increased above the current value of 897 g/m³ to a maximum of 2,500 g/m³. Therefore, implementing the ABD Program would produce a variant of high-level waste glass—the ABD glass—that needs to be evaluated for future repository licensing, which includes both preclosure safety and postclosure performance. This report describes the approach to and summarizes the results of an evaluation of the potential effects of implementing the ABD Program at the Savannah River Site on the technical basis for future repository licensing for a generic repository that is similar to Yucca Mountain and for one that is fully generic. This evaluation includes the effects on preclosure safety analyses and postclosure performance assessment for both repository settings. The license application for the proposed Yucca Mountain repository (DOE 2008), which is serving as a framework for this evaluation, concluded that the proposed Yucca Mountain repository would meet all applicable regulatory requirements. The evaluation documented in this report found that implementing the ABD Program is not expected to change that conclusion for a generic repository similar to Yucca Mountain or for a generic repository with respect to the preclosure safety analyses. With respect to the postclosure performance of a generic repository, no concerns were identified.

Filtration, pressure drop and quantitative fit of N95 respirators were robust to several decontamination methods including vaporous hydrogen peroxide, wet heat, bleach, and ultraviolet light. Bleach may not have penetrated the hydrophobic outer layers of the N95 respirator. Isopropyl alcohol and detergent both severely degraded the electrostatic charge of the electret filtration layer. First data in N95 respirators that the loss of filtration efficiency was directly correlated with loss of surface potential on the filtration layer. The pressure drop was unchanged, so loss of filtration efficacy would not be apparent during a user seal check. Mechanical straps degrade with repeated mechanical cycling during extended use. Decontamination did not appear to degrade the elastic straps. Significant loss of strap elasticity would be apparent during a user negative pressure seal check.

A myriad of phenomena in materials science and chemistry rely on quantum-level simulations of the electronic structure in matter. While moving to larger length and time scales has been a pressing issue for decades, such large-scale electronic structure calculations are still challenging despite modern software approaches and advances in high-performance computing. The silver lining in this regard is the use of machine learning to accelerate electronic structure calculations – this line of research has recently gained growing attention. The grand challenge therein is finding a suitable machine-learning model during a process called hyperparameter optimization. This, however, causes a massive computational overhead in addition to that of data generation. We accelerate the construction of machine-learning surrogate models by roughly two orders of magnitude by circumventing excessive training during the hyperparameter optimization phase. We demonstrate our workflow for Kohn-Sham density functional theory, the most popular computational method in materials science and chemistry.

Here, we explore the dimensionality of the U.S. Department of Agriculture’s household food security survey module among households with children. Using a novel methodological approach to measuring food security, we find that there is multidimensionality in the module for households with children that is associated with the overall household, adult, and child dimensions of food security. Additional analyses suggest official estimates of food security among households with children are robust to this multidimensionality. However, we also find that accounting for the multidimensionality of food security among these households provides new insights into the correlates of food security at the household, adult, and child levels of measurement.

The objective of this project was to develop a novel capability to generate synthetic data sets for the purpose of training Machine Learning (ML) algorithms for the detection of malicious activities on satellite systems. The approach experimented with was to a) generate sparse data sets using emulation modeling and b) enlarge the sparse data using Generative Adversarial Networks (GANs). We based our emulation modeling on the Open Source NASA Operational Simulator for Small Satellites (NOS3) developed by the Katherine Johnson Independent Verification and Validation (IV&V) program in West Virginia. Significant new capabilities on NOS3 had to be developed for our data set generation needs. To expand these data sets for the purpose of training ML, we experimented with a) Extreme Learning Machines (ELMs) and b) Wasserstein-GANs (WGAN-GP).

The core function of many neural network algorithms is the dot product, or vector matrix multiply (VMM) operation. Crossbar arrays utilizing resistive memory elements can reduce computational energy in neural algorithms by up to five orders of magnitude compared to conventional CPUs. Moving data between a processor, SRAM, and DRAM dominates energy consumption. By utilizing analog operations to reduce data movement, resistive memory crossbars can enable processing of large amounts of data at lower energy than conventional memory architectures.

For isolated white dwarf (WD) stars, fits to their observed spectra provide the most precise estimates of their effective temperatures and surface gravities. Even so, recent studies have shown that systematic offsets exist between such spectroscopic parameter determinations and those based on broadband photometry. These large discrepancies (10% in Teff, 0.1 M⊙ in mass) provide scientific motivation for reconsidering the atomic physics employed in the model atmospheres of these stars. Recent simulation work of ours suggests that the most important remaining uncertainties in simulation-based calculations of line shapes are the treatment of 1) the electric field distribution and 2) the occupation probability (OP) prescription. We review the work that has been done in these areas and outline possible avenues for progress.

The role of a solid surface for initiating gas-phase reactions is still not well understood. The hydrogen atom (H) is an important intermediate in gas-phase ethane dehydrogenation and is known to interact with surface sites on catalysts. However, direct measurements of H near catalytic surfaces have not yet been reported. Here, we present the first H measurements by laser-induced fluorescence in the gas-phase above catalytic and noncatalytic surfaces. Measurements at temperatures up to 700 °C show H concentrations to be at the highest above inert quartz surfaces compared to stainless steel and a platinum-based catalyst. Additionally, H concentrations above the catalyst decreased rapidly with time on stream. These newly obtained observations are consistent with the recently reported differences in bulk ethane dehydrogenation reactivity of these materials, suggesting H may be a good reporter for dehydrogenation activity.

In global atmospheric modeling, the differences between nonhydrostatic (NH) and hydrostatic (H) dynamical cores are negligible in dry simulations when grid spacing is larger than 10 km. However, recent studies suggest that those differences can be significant at far coarser resolution when moisture is included. To better understand how NH and H differences manifest in global fields, we perform and analyze an ensemble of 28 and 13 km seasonal simulations with the NH and H dynamical cores in the Energy Exascale Earth System Model global atmosphere model, where the differences between H and NH configurations are minimized. A set of idealized rising bubble experiments is also conducted to further investigate the differences. Although NH and H differences are not significant in global statistics and zonal averages, significant differences in precipitation amount and patterns are observed in parts of the tropics. The most prominent differences emerge near India and the Western Pacific in the boreal summer, and the central-southern Indian Ocean and Pacific in the boreal winter. Tropical differences influence surrounding regions through modification of the regional circulation and can propagate to the extratropics, leading to significant temperature and geopotential differences over the middle to high latitudes. While the dry bubble experiments show negligible deviation between H and NH dynamics until grid spacing is below 6.25 km, precipitation amount and vertical velocity are different in the moist case even at 25 km resolution.

We introduce a robust verification tool for computational codes, which we call Stochastic Robust Extrapolation based Error Quantification (StREEQ). Unlike the prevalent Grid Convergence Index (GCI) [1] method, our approach is suitable for both stochastic and deterministic computational codes and is generalizable to any number of discretization variables. Building on ideas introduced in the Robust Verification [2] approach, we estimate the converged solution and orders of convergence with uncertainty using multiple fits of a discretization error model. In contrast to Robust Verification, we perform these fits to many bootstrap samples yielding a larger set of predictions with smoother statistics. Here, bootstrap resampling is performed on the lack-of-fit errors for deterministic code responses, and directly on the noisy data set for stochastic responses. This approach lends a degree of robustness to the overall results, capable of yielding precise verification results for sufficiently resolved data sets, and appropriately expanding the uncertainty when the data set does not support a precise result. For stochastic responses, a credibility assessment is also performed to give the analyst an indication of the trustworthiness of the results. This approach is suitable for both code and solution verification, and is particularly useful for solution verification of high-consequence simulations.

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This presentation provides details regarding integral experiments at Sandia National Laboratory for fiscal year 2021. The experiments discussed are as follows: IER 230: Characterize the Thermal Capabilities of the 7uPCX; IER 304: Temperature Dependent Critical Benchmarks; IER 305: Critical Experiments with UO₂ Rods and Molybdenum Foils; IER 306: Critical Experiments with UO₂ Rods and Rhodium Foils ; IER 441: Epithermal HEX Lattices with SNL 7uPCX Fuel for Testing Nuclear Data; IER 452: Inversion Point of the Isothermal Reactivity Coefficient; and IER 523: Critical Experiments with ACRR UO₂-BeO Fuel.

This work presents a new multiscale method for coupling the 3D Maxwell's equations to the 1D telegrapher's equations. While Maxwell's equations are appropriate for modeling complex electromagnetics in arbitrary-geometry domains, simulation cost for many applications (e.g. pulsed power) can be dramatically reduced by representing less complex transmission line regions of the domain with a 1D model. By assuming a transverse electromagnetic (TEM) ansatz for the solution in a transmission line region, we reduce the Maxwell's equations to the telegrapher's equations. We propose a self-consistent finite element formulation of the fully coupled system that uses boundary integrals to couple between the 3D and 1D domains and supports arbitrary unstructured 3D meshes. Additionally, by using a Lagrange multiplier to enforce continuity at the coupling interface, we allow for an absorbing boundary condition to also be applied to non-TEM modes on this boundary. We demonstrate that this feature reduces non-physical reflection and ringing of non-TEM modes off of the coupling boundary. By employing implicit time integration, we ensure a stable coupling, and we introduce an efficient method for solving the resulting linear systems. We demonstrate the accuracy of the new method on two verification problems, a transient O-wave in a rectilinear prism and a steady-state problem in a coaxial geometry, and show the efficiency and weak scalability of our implementation on a cold test of the Z-machine MITL and post-hole convolute.

Sandia National Labs has access to unused ACRR fuel, which is unique in its enrichment 35% and material composition BeO. ACRR fuel is available in quantities well above what is needed for experiments. Two experiment concepts have been investigated: UO₂BeO fuel elements and pellets with 7uPCX fuel. The worth of UO₂BeO is large enough to be well above the anticipated experiment uncertainties.

This presentation discusses activities related to the Nuclear Criticality Safety Program (NCSP) at Sandia National Laboratory in fiscal year 2021. This includes NCSP funding, integral experiment requests, integral experiment spending, highlights, and COVID-19 impacts.

In situ analysis of surfaces during high-flux plasma exposure represents a long-standing challenge in the study of plasma-material interactions. While post-mortem microscopy can provide a detailed picture of structural and compositional changes, in situ techniques can capture the dynamic evolution of the surface. In this study, we demonstrate how spectroscopic ellipsometry can be applied to the real-time characterization of W nanostructure (also known as "fuzz") growth during exposure to low temperature, high-flux He plasmas. Strikingly, over a wide range of sample temperatures and helium fluences, the measured ellipsometric parameters (ψ, Δ) collapse onto a single curve that can be directly correlated with surface morphologies characterized by ex situ helium ion microscopy. The initial variation in the (ψ, Δ) parameters appears to be governed by small changes in surface roughness (<50 nm) produced by helium bubble nucleation and growth, followed by the emergence of 50 nm diameter W tendrils. This basic behavior appears to be reproducible over a wide parameter space, indicating that the spectroscopic ellipsometry may be of general practical use as a diagnostic to study surface morphologies produced by high-flux He implantation in refractory metals. An advantage of the methods outlined here is that they are applicable at low incident ion energies, even below the sputtering threshold. As an example of this application, we apply in situ ellipsometry to examine how W fuzz growth is affected both by varying ion energy and the temperature of the surface.

Here, we utilize electrically detected magnetic resonance (EDMR) measurements to compare high-field stressed, and gamma irradiated Si/SiO₂ metal–oxide–silicon (MOS) structures. We utilize spin-dependent recombination (SDR) EDMR detected using the Fitzgerald and Grove dc I-V approach to compare the effects of high-field electrical stressing and gamma irradiation on defect formation at and near the Si/SiO₂ interface. As anticipated, both greatly increase the concentration of P_b centers (silicon dangling bonds at the interface) densities. The irradiation also generated a significant increase in the dc I-V EDMR response of E' centers (oxygen vacancies in the SiO₂ films), whereas the generation of an E' EDMR response in high-field stressing is much weaker than in the gamma irradiation case. These results likely suggest a difference in their physical distribution resulting from radiation damage and high electric field stressing.

The reactivity of carbonyl oxides has previously been shown to exhibit strong conformer and substituent dependencies. Through a combination of synchrotron-multiplexed photoionization mass spectrometry experiments (298 K and 4 Torr) and high-level theory [CCSD(T)-F12/cc-pVTZ-F12//B2PLYP-D3/cc-pVTZ with an added CCSDT(Q) correction], we explore the conformer dependence of the reaction of acetaldehyde oxide (CH3CHOO) with dimethylamine (DMA). The experimental data support the theoretically predicted 1,2-insertion mechanism and the formation of an amine-functionalized hydroperoxide reaction product. Tunable-vacuum ultraviolet photoionization probing of anti- or anti- + syn-CH3CHOO reveals a strong conformer dependence of the title reaction. The rate coefficient of DMA with anti-CH3CHOO is predicted to exceed that for the reaction with syn-CH3CHOO by a factor of ∼34,000, which is attributed to submerged barrier (syn) versus barrierless (anti) mechanisms for energetically downhill reactions.

CPU/GPU heterogeneous compute platforms are an ubiquitous element in computing and a programming model specified for this heterogeneous computing model is important for both performance and programmability. A programming model that exposes the shared, unified, address space between the heterogeneous units is a necessary step in this direction as it removes the burden of explicit data movement from the programmer while maintaining performance. GPU vendors, such as AMD and NVIDIA, have released software-managed runtimes that can provide programmers the illusion of unified CPU and GPU memory by automatically migrating data in and out of the GPU memory. However, this runtime support is not included in GPGPU-Sim, a commonly used framework that models the features of a modern graphics processor that are relevant to non-graphics applications. UVM Smart was developed, which extended GPGPU-Sim 3.x to in- corporate the modeling of on-demand pageing and data migration through the runtime. This report discusses the integration of UVM Smart and GPGPU-Sim 4.0 and the modifications to improve simulation performance and accuracy.

Enhancing the efficiency of second-harmonic generation using all-dielectric metasurfaces to date has mostly focused on electromagnetic engineering of optical modes in the meta-atom. Further advances in nonlinear conversion efficiencies can be gained by engineering the material nonlinearities at the nanoscale, however this cannot be achieved using conventional materials. Semiconductor heterostructures that support resonant nonlinearities using quantum engineered intersubband transitions can provide this new degree of freedom. By simultaneously optimizing the heterostructures and meta-atoms, we experimentally realize an all-dielectric polaritonic metasurface with a maximum second-harmonic generation power conversion factor of 0.5 mW/W2 and power conversion efficiencies of 0.015% at nominal pump intensities of 11 kW/cm2. These conversion efficiencies are higher than the record values reported to date in all-dielectric nonlinear metasurfaces but with 3 orders of magnitude lower pump power. Our results therefore open a new direction for designing efficient nonlinear all-dielectric metasurfaces for new classical and quantum light sources.

The protection systems (circuit breakers, relays, reclosers, and fuses) of the electric grid are the primary component responding to resilience events, ranging from common storms to extreme events. The protective equipment must detect and operate very quickly, generally <0.25 seconds, to remove faults in the system before the system goes unstable or additional equipment is damaged. The burden on protection systems is increasing as the complexity of the grid increases; renewable energy resources, particularly inverter-based resources (IBR) and increasing electrification all contribute to a more complex grid landscape for protection devices. In addition, there are increasing threats from natural disasters, aging infrastructure, and manmade attacks that can cause faults and disturbances in the electric grid. The challenge for the application of AI into power system protection is that events are rare and unpredictable. In order to improve the resiliency of the electric grid, AI has to be able to learn from very little data. During an extreme disaster, it may not be important that the perfect, most optimal action is taken, but AI must be guaranteed to always respond by moving the grid toward a more stable state during unseen events.

A combination of electrodeposition and thermal reduction methods have been utilized for the synthesis of ligand-free FeNiCo alloy nanoparticles through a high-entropy oxide intermediate. These phases are of great interest to the electrocatalysis community, especially when formed by a sustainable chemistry method. This is successfully achieved by first forming a complex five element amorphous FeNiCoCrMn high-entropy oxide (HEO) phase via electrodeposition from a nanodroplet emulsion solution of the metal salt reactants. The amorphous oxide phase is then thermally treated and reduced at 570-600 °C to form the crystalline FeNiCo alloy with a separate CrMnOx cophase. The FeNiCo alloy is fully characterized by scanning transmission electron microscopy and energy-dispersive X-ray spectroscopy elemental analysis and is identified as a face-centered cubic crystal with the lattice constant a = 3.52 Å. The unoptimized, ligand-free FeNiCo NPs activity toward the oxygen evolution reaction is evaluated in alkaline solution and found to have an ∼185 mV more cathodic onset potential than the Pt metal. Beyond being able to synthesize highly crystalline, ligand-free FeNiCo nanoparticles, the demonstrated and relatively simple two-step process is ideal for the synthesis of tailor-made nanoparticles where the desired composition is not easily achieved with classical solution-based chemistries.

There are several engineering applications in which the assumptions of homogenization and scale separation may be violated, in particular, for metallic structures constructed through additive manufacturing. Instead of resorting to direct numerical simulation of the macroscale system with an embedded fine scale, an alternative approach is to use an approximate macroscale constitutive model, but then estimate the model-form error using a posteriori error estimation techniques and subsequently adapt the macroscale model to reduce the error for a given boundary value problem and quantity of interest. Here, we investigate this approach to multiscale analysis in solids with unseparated scales using the example of an additively manufactured metallic structure consisting of a polycrystalline microstructure that is neither periodic nor statistically homogeneous. As a first step to the general nonlinear case, we focus here on linear elasticity in which each grain within the polycrystal is linear elastic but anisotropic.

Electrically detected magnetic resonance and near-zero-field magnetoresistance measurements were used to study atomic-scale traps generated during high-field gate stressing in Si/SiO2 MOSFETs. The defects observed are almost certainly important to time-dependent dielectric breakdown. The measurements were made with spin-dependent recombination current involving defects at and near the Si/SiO2 boundary. The interface traps observed are Pb0 and Pb1 centers, which are silicon dangling bond defects. The ratio of Pb0/Pb1 is dependent on the gate stressing polarity. Electrically detected magnetic resonance measurements also reveal generation of E′ oxide defects near the Si/SiO2 interface. Near-zero-field magnetoresistance measurements made throughout stressing reveal that the local hyperfine environment of the interface traps changes with stressing time; these changes are almost certainly due to the redistribution of hydrogen near the interface.

Graph partitioning has emerged as an area of interest due to its use in various applications in computational research. One way to partition a graph is to solve for the eigenvectors of the corresponding graph Laplacian matrix. This project focuses on the eigensolver LOBPCG and the evaluation of a new preconditioner: Randomized Cholesky Factorization (rchol). This proconditioner was tested for its speed and accuracy against other well-known preconditioners for the method. After experiments were run on several known test matrices, rchol appears to be a better preconditioner for structured matrices. This research was sponsored by National Nuclear Security Administration Minority Serving Institutions Internship Program (NNSA-MSIIP) and completed at host facility Sandia National Laboratories. As such, after discussion of the research project itself, this report contains a brief reflection on experience gained as a result of participating in the NNSA-MSIIP.

We present an overview of the magneto-inertial fusion (MIF) concept MagLIF (Magnetized Liner Inertial Fusion) pursued at Sandia National Laboratories and review some of the most prominent results since the initial experiments in 2013. In MagLIF, a centimeter-scale beryllium tube or "liner" is filled with a fusion fuel, axially pre-magnetized, laser pre-heated, and finally imploded using up to 20 MA from the Z machine. All of these elements are necessary to generate a thermonuclear plasma: laser preheating raises the initial temperature of the fuel, the electrical current implodes the liner and quasi-adiabatically compresses the fuel via the Lorentz force, and the axial magnetic field limits thermal conduction from the hot plasma to the cold liner walls during the implosion. MagLIF is the first MIF concept to demonstrate fusion relevant temperatures, significant fusion production (>10^13 primary DD neutron yield), and magnetic trapping of charged fusion particles. On a 60 MA next-generation pulsed-power machine, two-dimensional simulations suggest that MagLIF has the potential to generate multi-MJ yields with significant self-heating, a long-term goal of the US Stockpile Stewardship Program. At currents exceeding 65 MA, the high gains required for fusion energy could be achievable.

Experiments were designed and conducted to investigate the impact that geometric cavities have on the transfer of energy from an embedded explosion to the surface of the physical domain. The experimental domains were fabricated as 3-inch polymer cubes, with varying cavity geometries centered in the cubes. The energy transfer, represented as a shock wave, was generated by the detonation of an exploding bridgewire at the center of the cavity. The shock propagation was tracked by schlieren imaging through the optically accessible polymer. The magnitude of energy transferred to the surface was recorded by an array of pressure sensors. A minimum of five experimental runs were conducted for each cavity geometry and statistical results were developed and compared. Results demonstrated the decoupling effect that geometric cavities produce on the energy field at the surface.

Fractional equations have become the model of choice in several applications where heterogeneities at the microstructure result in anomalous diffusive behavior at the macroscale. Here, we introduce a new fractional operator characterized by a doubly-variable fractional order and possibly truncated interactions. Under certain conditions on the model parameters and on the regularity of the fractional order we show that the corresponding Poisson problem is well-posed. Additionally, we introduce a finite element discretization and describe an efficient implementation of the finite-element matrix assembly in the case of piecewise constant fractional order. Through several numerical tests, we illustrate the improved descriptive power of this new operator across media interfaces. Furthermore, we present one-dimensional and two-dimensional h-convergence results that show that the variable-order model has the same convergence behavior as the constant-order model.

Computational tools to study thermodynamic properties of magnetic materials have, until recently, been limited to phenomenological modeling or to small domain sizes limiting our mechanistic understanding of thermal transport in ferromagnets. Herein, we study the interplay of phonon and magnetic spin contributions to the thermal conductivity in a-iron utilizing non-equilibrium molecular dynamics simulations. It was observed that the magnetic spin contribution to the total thermal conductivity exceeds lattice transport for temperatures up to two-thirds of the Curie temperature after which only strongly coupled magnon-phonon modes become active heat carriers. Characterizations of the phonon and magnon spectra give a detailed insight into the coupling between these heat carriers, and the temperature sensitivity of these coupled systems. Comparisons to both experiments and ab initio data support our inferred electronic thermal conductivity, supporting the coupled molecular dynamics/spin dynamics framework as a viable method to extend the predictive capability for magnetic material properties.

Spectral line-shape models are an important part of understanding high-energy-density (HED) plasmas. Models are needed for calculating opacity of materials and can serve as diagnostics for astrophysical and laboratory plasmas. However, much of the literature on line shapes is directed toward specialists. This perspective makes it difficult for non-specialists to enter the field. We have two broad goals with this topical review. First, we aim to give information so that others in HED physics may better understand the current field. This first goal may help guide future experiments to test different aspects of the theory. Second, we provide an introduction for those who might be interested in line-shape theory, and enough materials to be able to navigate the field and the literature. We give a high-level overview of line broadening process, as well as dive into the formalism, available methods, and approximations.

With a wide variety of wave energy device archetypes currently under consideration, it is a major challenge to ensure that research findings and methods are broadly applicable. In particular, the design and testing of wave energy control systems, a process which includes experimental design, empirical modeling, control design, and performance evaluation, is of interest. This goal motivated the redesign and testing of a floating dual flap wave energy converter. As summarized in this paper, the steps taken in the design, testing, and analysis of the device mirrored those previously demonstrated on a three-degree of freedom point absorber device. The method proposed does not require locking WEC degrees of freedom to develop an excitation model, and presents a more attainable system identification procedure for at-sea deployments. The results show that the methods employed work well for this dual flap device, lending additional support for the broad applicability of the design and testing methods applied here. The aim of this paper is to demonstrate that these models are particularly useful for deducing areas of device design or controller implementation that can be reasonably improved to increase device power capture.

For the PACT center to both develop testing protocols and provide service to the metal halide perovskite (MHP) PV community, PACT will seek modules (mini and full-sized) for testing purposes. To ensure both safety and high-quality samples PACT publishes acceptance criteria to define the minimum characteristics of modules the center will accept for testing. These criteria help to ensure we are accepting technologies that are compatible with our technical facilities and testing equipment and can transition to large scale commercial manufacturing. This module design acceptance criteria document is for industry partners and is different from the acceptance criteria for research partners (academia, national laboratories) partners.

Radiographic diodes focus on an intense electron beam to a small spot size to minimize the source area of energetic photons for radiographic interrogation. The self-magnetic pinch (SMP) diode has been developed as such a source and operated as a load for the six-cavity radiographic integrated test stand (RITS-6) inductive voltage adder driver. While experiments support the generally accepted conclusion that a 1:1 aspect diode (cathode diameter equals anode-cathode gap) delivers optimum SMP performance, such experiments also show that reducing the cathode diameter, while reducing spot size, also results in reduced radiation dose, by as much as 50%, and degraded shot reproducibility. Analysis of the effective electron impingement angle on the anode converter with time made possible by a newly developed dose-rate array diagnostic indicates that fast-developing oscillations of the angle are correlated with early termination of the radiation pulse on many of the smaller-diameter SMP shots. This behavior as a function of relative cathode size persists through experiments with output voltages and currents up to 11.5 MV and 225 kA, respectively, and with spot sizes below approximately few millimeters. Since simulations to date have not predicted such oscillatory behavior, considerable discussion of the angle behavior of SMP shots is made to lend credence to the inference. There is clear anecdotal evidence that DC heating of the SMP diode region leads to stabilization of this oscillatory behavior. This is the first of two papers on the performance of the SMP diode on the RITS-6 accelerator.

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Neuromorphic computing, which aims to replicate the computational structure and architecture of the brain in synthetic hardware, has typically focused on artificial intelligence applications. What is less explored is whether such brain-inspired hardware can provide value beyond cognitive tasks. Here we show that the high degree of parallelism and configurability of spiking neuromorphic architectures makes them well suited to implement random walks via discrete-time Markov chains. These random walks are useful in Monte Carlo methods, which represent a fundamental computational tool for solving a wide range of numerical computing tasks. Using IBM’s TrueNorth and Intel’s Loihi neuromorphic computing platforms, we show that our neuromorphic computing algorithm for generating random walk approximations of diffusion offers advantages in energy-efficient computation compared with conventional approaches. We also show that our neuromorphic computing algorithm can be extended to more sophisticated jump-diffusion processes that are useful in a range of applications, including financial economics, particle physics and machine learning.

The progression of wind turbine technology has led to wind turbines being incredibly optimized machines often approaching their theoretical maximum production capabilities. When placed together in arrays to make wind farms, however, they are subject to wake interference that greatly reduces downstream turbines' power production, increases structural loading and maintenance, reduces their lifetimes, and ultimately increases the levelized cost of energy. Development of techniques to manage wakes and operate larger and larger arrays of turbines more efficiently is now a crucial field of research. Herein, four wake management techniques in various states of development are reviewed. These include axial induction control, wake steering, the latter two combined, and active wake control. Each of these is reviewed in terms of its control strategies and use for power maximization, load reduction, and ancillary services. By evaluating existing research, several directions for future research are suggested.

Cookoff experiments of powdered and pressed TATB-based plastic bonded explosives (PBXs) have been modeled using a pressure-dependent universal cookoff model (UCM) in combination with a micromechanics pressurization (MMP) model described in a companion paper. The MMP model is based on the accumulation of decomposition gases at nucleation sites that load the surrounding TATB crystals and binder. This is the first cookoff model to use an analytical mechanics solution for compressibility and thermal expansion to describe internal pressurization caused by both temperature and decomposition occurring within closed-pore explosives. This approach produces more accurate predictions of ignition time and pressurization within high-density explosives than simple equation-of-state models. The current paper gives details of the reaction chemistry, model parameters, predicted uncertainty, and validation using experiments from multiple laboratories with errors less than 6 %. The UCM/MMP model framework gives more accurate thermal ignition predictions for high density explosives that are initially impermeable to decomposition gases.

Dual-fuel (DF) engines, in which premixed natural gas and air in an open-type combustion chamber is ignited by diesel-fuel pilot sprays, have been more popular for marine use than pre-chamber spark ignition (PCSI) engines because of their superior durability. However, control of ignition and combustion in DF engines is more difficult than in PCSI engines. In this context, this study focuses on the ignition stability of n-heptane pilot-fuel jets injected into a compressed premixed charge of natural gas and air at low-load conditions. To aid understanding of the experimental data, chemical-kinetics simulations were carried out in a simplified engine-environment that provided insight into the chemical effects of methane (CH4) on pilot-fuel ignition. The simulations reveal that CH4 has an effect on both stages of n-heptane autoignition: the small, first-stage, cool-flame-type, low-temperature ignition (LTI) and the larger, second-stage, high-temperature ignition (HTI). As the ratio of pilot-fuel to CH4 entrained into the spray decreases, the initial oxidization of CH4 consumes the OH radicals produced by pilot-fuel decomposition during LTI, thereby inhibiting its progression to HTI. Using imaging diagnostics, the spatial and temporal progression of LTI and HTI in DF combustion are measured in a heavy-duty optical engine, and the imaging data are analyzed to understand the cause of severe fluctuations in ignition timing and combustion completeness at low-load conditions. Images of cool-flame and hydroxyl radical (OH*) chemiluminescence serve as indicators of LTI and HTI, respectively. The cycle-to-cycle and spatial variation in ignition extracted from the imaging data are used as key metrics of comparison. The imaging data indicate that the local concentration of the pilot-fuel and the richness of the surrounding natural-gas air mixture are important for LTI and HTI, but in different ways. In particular, higher injection pressures and shorter injection durations increase the mixing rate, leading to lower concentrations of pilot-fuel more quickly, which can inhibit HTI even as LTI remains relatively robust. Decreasing the injection pressure from 80 MPa to 40 MPa and increasing the injection duration from 500 µs to 760 µs maintained constant pilot-fuel mass, while promoting robust transition from LTI to HTI by effectively slowing the mixing rate. This allows enough residence time for the OH radicals, produced by the two-stage ignition chemistry of the pilot-fuel, to accelerate the transition from LTI to HTI before being consumed by CH4 oxidation. Thus from a practical perspective, for a premixed natural gas fuel–air equivalence-ratio, it is possible to improve the “stability” of the combustion process by solely manipulating the pilot-fuel injection parameters while maintaining constant mass of injected pilot-fuel. This allows for tailoring mixing trajectories to offset changes in fuel ignition chemistry, so as to promote a robust transition from LTI to HTI by changing the balance between the local concentration of the pilot-fuel and richness of the premixed natural gas and air. This could prove to be a valuable tool for combustion design to improve fuel efficiency or reduce noise or perhaps even reduce heat-transfer losses by locating early combustion away from in-cylinder walls.

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Economically successful microalgal mass cultivation is dependent on overcoming several barriers that contribute to the cost of production. The severity of these barriers is dependent on the market value of the final product. These barriers prevent the commercially viable production of algal biofuels but are also faced by any producers of any algal product. General barriers include the cost of water and limits on recycling, costs and recycling of nutrients, CO2 utilization, energy costs associated with harvesting and biomass loss due to biocontamination and pond crashes. In this paper, recent advances in overcoming these barriers are discussed.

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Grain boundaries have complex structural features that influence strength, ductility and fracture in metals and alloys. Grain boundary misorientation angle has been identified as a key parameter that controls their mechanical behavior, but the effect of misorientation angle has been challenging to isolate in polycrystalline materials. Here, we describe the use of bicrystal Au thin films made using a rapid melt growth process to study deformation at a single grain boundary. Tensile testing is performed on bicrystals with different misorientation angles using in situ TEM, as well as on a single crystalline sample. Plastic deformation is initiated through dislocation nucleation from free surfaces. Grain boundary sliding is not observed, and failure occurs away from the grain boundary through plastic collapse in all cases. The failure behavior in these nanoscale bicrystals does not appear to depend on the misorientation angle or grain boundary energy but instead has a more complex dependence on sample surface structure and dislocation activity.

Montmorillonite (MMT) clays are important industrial materials used as catalysts, chemical sorbents and fillers in polymer–clay nanocomposites. The layered structure of these clays has motivated research into further applications of these low-cost materials, including use as ion exchange media and solid-state ionic conductors. In these applications, the mechanical properties of MMT are key when considering long-term, reliable performance. Previous studies have focused on the mechanical properties of nanocomposites with MMT as the minority component or pure MMT thin films. In this work, the microstructure and mechanical properties of pure MMT and majority MMT/polyethylene composites pressed into dense pellets are examined. Characterization methods such as X-ray diffraction, atomic force microscopy and scanning electron microscopy together with nanoindentation reveal important structure–property relationships in the clay-based materials. Utilizing these techniques, we have discovered that MMT processing impacts the layered microstructure, chemical stability and, critically, the elastic modulus and hardness of bulk MMT samples. Particularly, the density of the pellets and the ordering of the clay platelets within them strongly influence the elastic modulus and hardness of the pellets. By increasing pressing force or by incorporating secondary components, the density, and therefore mechanical properties, can be increased. If the layered structure of the clay is destroyed by exfoliation, the mechanical properties will be compromised. Understanding these relationships will help guide new studies to engineer mechanically stable MMT-based materials for industrial applications. Graphical abstract: [Figure not available: see fulltext.].

Stainless steels are susceptible to localized forms of corrosion attack, such as pitting. The size and lifetime of a nucleated pit can vary, depending on a critical potential or current density criterion, which determines if the pit repassivates or continues growing. This work uses finite element method (FEM) modeling to compare the critical pit radii predicted by thermodynamic and kinetic repassivation criteria. Experimental electrochemical boundary conditions are used to capture the active pit kinetics. Geometric and environmental parameters, such as the pit shape and size (analogous to additively manufactured lack-of-fusion pores), solution concentration, and water layer thickness were considered to assess their impact on the pit repassivation criterion. The critical pit radius (the transition point from stable growth to repassivation) predicted for a hemispherical pit was larger when using the repassivation potential (Erp) criteria, as opposed to the current density criteria (pit stability product). Including both the pit stability product and Erp into its calculations, the analytical maximum pit model predicted a critical radius two times more conservative than the FEA approach, under the conditions studied herein. The complex pits representing lack-of-fusion pores were shown to have minimal impact on the critical radius in atmospheric conditions.

Fast detection and isolation of faults in a DC microgrid is of particular importance. Fast tripping protection (i) increases the lifetime of power electronics (PE) switches by avoiding high fault current magnitudes and (ii) enhances the controllability of PE converters. This paper proposes a traveling wave (TW) based scheme for fast tripping protection of DC microgrids. The proposed scheme utilizes a discrete wavelet transform (DWT) to calculate the high-frequency components of DC fault currents. Multiresolution analysis (MRA) using DWT is utilized to detect TW components for different frequency ranges. The Parseval energy of the MRA coefficients are then calculated to demonstrate a quantitative relationship between the fault current signal energy and coefficients’ energy. The calculated Parseval energy values are used to train a Support Vector Machine classifier to identify the fault type and a Gaussian Process regression engine to estimate the fault location on the DC cables. The proposed approach is verified by simulating two microgrid test systems in PSCAD/EMTDC.

Although unique expected energy models can be generated for a given photovoltaic (PV) site, a standardized model is also needed to facilitate performance comparisons across fleets. Current standardized expected energy models for PV work well with sparse data, but they have demonstrated significant over-estimations, which impacts accurate diagnoses of field operations and maintenance issues. This research addresses this issue by using machine learning to develop a data-driven expected energy model that can more accurately generate inferences for energy production of PV systems. Irradiance and system capacity information was used from 172 sites across the United States to train a series of models using Lasso linear regression. The trained models generally perform better than the commonly used expected energy model from international standard (IEC 61724-1), with the two highest performing models ranging in model complexity from a third-order polynomial with 10 parameters (R2adj= 0.994) to a simpler, second-order polynomial with 4 parameters (R2adj= 0.993), the latter of which is subject to further evaluation. Subsequently, the trained models provide a more robust basis for identifying potential energy anomalies for operations and maintenance activities as well as informing planning-related financial assessments. We conclude with directions for future research, such as using splines to improve model continuity and better capture systems with low (≤1000 kW DC) capacity.

Magnetized Liner Inertial Fusion (MagLIF) [Slutz et al., Phys. Plasmas 17, 056303 (2010)] experiments driven by the Z machine produce >1013 deuterium-deuterium fusion reactions [Gomez et al., Phys. Rev. Lett. 125, 155002 (2020)]. Simulations indicate high yields and gains (1000) with increased current and deuterium-tritium layers for burn propagation [Slutz et al., Phys. Plasmas 23, 022702 (2016)]. Such a coating also isolates the metal liner from the gaseous fuel, which should reduce mixing of liner material into the fuel. However, the vapor density at the triple point is only 0.3 kg/m3, which is not high enough for MagLIF operation. We present two solutions to this problem. First, a fuel wetted low-density plastic foam can be used to form a layer on the inside of the liner. The desired vapor density can be obtained by controlling the temperature. This does however introduce carbon into the layer which will enhance radiation losses. Simulations indicate that this wetted foam layer can significantly contribute to the fusion yield when the foam density is less than 35 kg/m3. Second, we show that a pure frozen fuel layer can first be formed on the inside of the liner and then low temperature gaseous fuel can be introduced just before the implosion without melting a significant amount of the ice layer. This approach is the most promising for MagLIF to produce high yield and gain.

The goal of this work is to build up the capability of quasi-particle simulation (QuiPS), a novel flow solver, such that it can adequately model the rarefied portion of an atmospheric reentry trajectory. Direct simulation Monte Carlo (DSMC) is the conventional solver for such conditions, but struggles to resolve transient flows, trace species, and high-level internal energy states due to stochastic noise. Quasi-particle simulation (QuiPS) is a novel Boltzmann solver that describes a system with a discretized, truncated velocity distribution function. The resulting fixed-velocity, variable weight quasi-particles enable smooth variation of macroscopic properties. The distribution function description enables the use of a variance-reduced collision model, greatly minimizing expense near equilibrium. This work presents the addition of a neutral air chemistry model to QuiPS and some demonstrative 0D simulations. The explicit representation of internal distributions in QuiPS reveals some of the flaws in existing physics models. Variance reduction, a key feature of QuiPS, can greatly reduce expense of multi-dimensional calculations, but is only cheaper when the gas composition is near chemical equilibrium.

The self-magnetic pinch (SMP) diode is a type of radiographic diode used to generate an intense electron beam for radiographic applications. At Sandia National Laboratories, SMP was the diode load for the six-cavity radiographic integrated test stand inductive voltage adder (IVA) driver operated in a magnetically insulated transmission line (MITL). The MITL contributes a flow current in addition to the current generated within the diode itself. Extensive experiments with a MITL of 40 ω load impedance [T. J. Renk et al., Phys. Plasmas 29, 023105 (2022)] indicate that the additional flow current leads to results similar to what might be expected from a conventional high-voltage interface driver, where flow current is not present. However, when the MITL flow impedance was increased to 80 ω, qualitatively different diode behavior was observed. This includes large retrapping waves suggestive of an initial coupling to low impedance as well as diode current decreasing with time even as the total current does not. A key observation is that the driver generates total current (flow + diode) consistent with the flow impedance of the MITL used. The case is made in this paper that the 80 ω MITL experiments detailed here can only be understood when the IVA-MITL-SMP diode is considered as a total system. The constraint of fixed total current plus the relatively high flow impedance limits the ability of the diode (whether SMP or other type) to act as an independent load. An unexpected new result is that in tracking the behavior of the electron strike angle on the converter as a function of time, we observed that the conventional cIVx "Radiographic"radiation scaling (where x ∼2.2) begins to break down for voltages above 8 MV, and cubic scaling is required to recover accurate angle tracking.

Material produced by current metal additive manufacturing processes is susceptible to variable performance due to imprecise control of internal porosity, surface roughness, and conformity to designed geometry. Using a double U-notched specimen, we investigate the interplay of nominal geometry and porosity in determining ductile failure characteristics during monotonic tensile loading. We simulate the effects of distributed porosity on plasticity and damage using a statistical model based on populations of pores visible in computed tomography scans and additional sub-threshold voids required to match experimental observations of deformation and failure. We interpret the simulation results from a physical viewpoint and provide a statistical model of the probability of failure near stress concentrations. We provide guidance for designs where material defects could cause unexpected failures depending on the relative importance of these defects with respect to features of the nominal geometry.

We characterized nine commercial aluminum (Al) powders using several methods to measure particle characteristics and thermal analysis, with the goal to understand how these parameters influence energy release. Although it is well-known that lot-to-lot variations in commercial nanoparticles are common, the Al powders were more heterogeneous than anticipated – both with regards to particle size distributions and impurities. Manufacturer specifications – often quoted in the literature without confirmation – were not always accurate for the specific sample lots we investigated. In several cases, different conclusions could be drawn from individual particle size techniques; a combination of multiple techniques provides a clearer picture of the powder properties. Thorough characterization of Al powders is required prior to interpretation of experimental results from a variety of applications. In particular, previous studies have shown contradictory results on the influence of Al on detonation performance, perhaps partially due to insufficient characterization of the Al powders themselves.

Triangle counting is a fundamental building block in graph algorithms. In this article, we propose a block-based triangle counting algorithm to reduce data movement during both sequential and parallel execution. Our block-based formulation makes the algorithm naturally suitable for heterogeneous architectures. The problem of partitioning the adjacency matrix of a graph is well-studied. Our task decomposition goes one step further: it partitions the set of triangles in the graph. By streaming these small tasks to compute resources, we can solve problems that do not fit on a device. We demonstrate the effectiveness of our approach by providing an implementation on a compute node with multiple sockets, cores and GPUs. The current state-of-the-art in triangle enumeration processes the Friendster graph in 2.1 seconds, not including data copy time between CPU and GPU. Using that metric, our approach is 20 percent faster. When copy times are included, our algorithm takes 3.2 seconds. This is 5.6 times faster than the fastest published CPU-only time.

Capacitance-voltage ( {C} - {V} ) characteristics and carrier transport properties of 2-D electron gases (2DEGs) in an undoped Si/SiGe heterostructure at {T}= {4} - {35} K are presented. Two capacitance plateaus due to density saturation of the 2DEG in the buried Si quantum well (QW) are observed and explained by a model of surface tunneling. The peak mobility at 4 K is 4.1 \times 10^{{5}} cm2/ \text{V}\cdot \text{s} and enhanced by a factor of 1.97 at an even lower carrier density compared to the saturated carrier density, which is attributed to the effect of remote carrier screening. At {T}\,\,=35 K, the mobility enhancement with a factor of 1.35 is still observed, which suggests the surface tunneling is still dominant.

This paper compares four different formulations of model predictive control that attempt to maximise electrical power generated by a wave energy converter (WEC). Control laws include (1) pure maximisation of mechanical power, (2) maximisation of mechanical power with a control penalty factor, (3) maximisation of electrical power using power conversion efficiency, and (4) maximisation of electrical power using the full electro-mechanical model of a system. For this study, a wave-to-wire model is developed for a floating spherical buoy connected to a permanent magnet synchronous generator. The performance of the controllers, including the mechanical and electrical power outputs, is compared in irregular wave conditions for the unconstrained and force-constrained scenarios. The results demonstrate that the controller designed to maximise mechanical power is not suitable for practical applications and may lead to negative electrical power output due to the non-ideal power take-off efficiency. Moreover, the replacement of the power take-off dynamics by the efficiency coefficient does not guarantee the maximum electrical power production.

Agencies that monitor for underground nuclear tests are interested in techniques that automatically characterize mining blasts to reduce the human analyst effort required to produce high-quality event bulletins. Waveform correlation is effective in finding similar waveforms from repeating seismic events, including mining blasts. We report the results of an experiment to detect and identify mining blasts for two regions, Wyoming (U.S.A.) and Scandinavia, using waveform templates recorded by multiple International Monitoring System stations of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO PrepCom) for up to 10 yr prior to the time of interest. We discuss approaches for template selection, threshold setting, and event detection that are specialized for characterizing mining blasts using a sparse, global network. We apply the approaches to one week of data for each of the two regions to evaluate the potential for establishing a set of standards for waveform correlation processing of mining blasts that can be generally applied to operational monitoring systems with a sparse network. We compare candidate events detected with our processing methods to the Reviewed Event Bulletin of the International Data Centre to assess potential reduction in analyst workload.

The direct injection spark ignition (DISI) engine has received considerable attention due to its potential to increase the power density of traditional spark ignition engines while significantly improving fuel economy through lean, unthrottled combustion. However, the market introduction of DISI engines operated in a lean combustion mode is inhibited by their unsatisfactory emissions, especially during cold start conditions that make proper mixture formation more challenging. Ethanol-blended gasoline, now a widely used fuel, makes the cold start of a DISI engine more difficult, leading to higher HC and soot emissions because of the high latent heat of vaporization of ethanol relative to gasoline. This work investigated the impact of coolant temperature on the characteristics of combustion and emissions in a stratified-charge DISI engine fueled with an E30 fuel (i.e. 30% ethanol in gasoline), while the coolant temperature was alternated between four levels (45, 60, 75, and 90 °C) to simulate different conditions throughout the warm-up process. The experiments showed that the coolant temperature affected the post-spark inflammation time, as well as the speed, intensity, and stability of the combustion process in the engine. When the coolant temperature rose, the engine produced more NOX and less CO, PM and HC. In addition, high-speed direct photography was used to obtain crank-angle resolved images of fuel sprays and flames in the cylinder. As the coolant temperature rose, the liquid spray lengths became shorter, reducing the possibility of wall wetting, and reduced irradiance from soot particles also indicated less non-premixed combustion. The in-cylinder imaging results are consistent with the observed combustion and emission characteristics and shed light on the underlying processes. Some potential solutions to the emissions challenges faced here could be either raising in-cylinder temperatures by using trapped residuals or modifying the injection schedule, for example by increasing the number of injections or to inject later in the cycle into a higher-density environment.

Electromagnetic (EM) methods are among the original techniques for subsurface characterization in exploration geophysics because of their particular sensitivity to the earth electrical conductivity, a physical property of rocks distinct yet complementary to density, magnetization, and strength. However, this unique ability also makes them sensitive to metallic artifacts - infrastructure such as pipes, cables, and other forms of cultural clutter - the EM footprint of which often far exceeds their diminutive stature when compared to that of bulk rock itself. In the hunt for buried treasure or unexploded ordnance, this is an advantage; in the long-term monitoring of mature oil fields after decades of production, it is quite troublesome indeed. Here we consider the latter through the lens of an evolving energy industry landscape in which the traditional methods of EM characterization for the exploration geophysicist are applied toward emergent problems in well-casing integrity, carbon capture and storage, and overall situational awareness in the oil field. We introduce case studies from these exemplars, showing how signals from metallic artifacts can dominate those from the target itself and impose significant burdens on the requisite simulation complexity. We also show how recent advances in numerical methods mitigate the computational explosivity of infrastructure modeling, providing feasible and real-time analysis tools for the desktop geophysicist. Lastly, we demonstrate through comparison of field data and simulation results that incorporation of infrastructure into the analysis of such geophysical data is, in a growing number of cases, a requisite but now manageable step.

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An improved electrical contact resistance (ECR) model for elastic rough electrode contact is proposed, incorporating the effects of asperity interactions and temperature rise by frictional and joule heating. The analytical simulation results show that the ECR decreases steeply at the beginning of the contact between Al and Cu. However, it becomes stabilized after reaching a specific contact force. It is also found that the longer elapsed sliding contact time, the higher ECR due to the increase in electrical resistivity of electrode materials by the frictional temperature rise at the interface. The effects of surface roughness parameters on ECR are studied through the 32 full-factorial design-of-experiment analysis. Based on the two representative roughness parameters, i.e., root-mean-square (rms) roughness and asperity radius, their individual and coupled effects on the saturated ECR are examined. The saturated ECR increases with the rms roughness for a rough machined surface condition, but it is hardly affected by the asperity radius. On the other hand, the saturated ECR increases with both the rms roughness and the asperity radius under a smooth thin film surface condition.

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We explore the character angle dependence of dislocation-solute interactions in a face-centered cubic random Fe0.70Ni0.11Cr0.19 alloy through molecular dynamics (MD) simulations of dislocation mobility. Using the MD mobility data, we determine the phonon and thermally activated solute drag parameters which govern mobility for each dislocation character angle. The resulting parameter set indicates that, surprisingly, the solute energy barrier does not depend on character angle. Instead, only the zero-temperature flow stress—which is dictated by the activation area for thermal activation—is dependent on character angle. By analyzing the line roughness from MD simulations and the geometry of a bowing dislocation line undergoing thermal activation, we conclude that the character angle dependence of the activation area in this alloy is governed by the dislocation line tension, rather than the dislocation-solute interaction itself. Our findings motivate further investigation into the line geometry of dislocations in solid solutions.

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System emulation and firmware re-hosting have become popular techniques to answer various security and performance related questions, such as determining whether a firmware contain security vulnerabilities or meet timing requirements when run on a specific hardware platform. While this motivation for emulation and binary analysis has previously been explored and reported, starting to either work or research in the field is difficult. To this end, we provide a comprehensive guide for the practitioner or system emulation researcher. We layout common challenges faced during firmware re-hosting, explaining successive steps and surveying common tools used to overcome these challenges. We provide classification techniques on five different axes, including emulator methods, system type, fidelity, emulator purpose, and control. These classifications and comparison criteria enable the practitioner to determine the appropriate tool for emulation. We use our classifications to categorize popular works in the field and present 28 common challenges faced when creating, emulating, and analyzing a system from obtaining firmwares to post emulation analysis.

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The Multi-Fidelity Toolkit (MFTK) is a simulation tool being developed at Sandia National Laboratories for aerodynamic predictions of compressible flows over a range of physics fidelities and computational speeds. These models include the Reynolds-Averaged-Navier-Stokes (RANS) equations, the Euler equations, and modified Newtonian aerodynamics (MNA) equations, and they can be invoked independently or coupled with hierarchical Kriging to interpolate between high-fidelity simulations using lower-fidelity data. However, as with any new simulation capability, verification and validation are necessary to gather credibility evidence. This work describes formal code- and solution-verification activities as well as model validation with uncertainty considerations. Code verification is performed on the MNA model by comparing with an analytical solution for flat-plate and inclined-plate geometries. Solution-verification activities include grid-refinement studies of HIFiRE-1 wind tunnel measurements, which are used for validation, for all model fidelities. A thorough treatment of the validation comparison with prediction error and validation uncertainty is also presented.

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