Publications

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MELCOR is an integrated thermal hydraulics, accident progression, and source term code for reactor safety analysis that has been developed at Sandia National Laboratories for the United States Nuclear Regulatory Commission (NRC) since the early 1980s. Though MELCOR originated as a light water reactor (LWR) code, development and modernization efforts have expanded its application scope to includ e non-LWR reactor concepts. Current MELCOR development efforts include providing the NRC with the analytical capabilities to support regulatory readiness for licensing non-LWR techno logies under Strategy 2 of the NRC?s near- term Implementation Action Plans. Beginning with the Next Generation Nuclear Project (NGNP), MELCOR has undergone a range of enha ncements to provide analytical capabilities for modeling the spectrum of advanced non-LWR concepts. This report describes the generic plant model developed to demonstrate MELCOR capabilities to perform heat pipe reactor (HPR) safety evaluations. The generic plant mode l is based on a publicly-available Los Alamos National Laboratory (LANL) Megapower design as modified in the Idaho National Laboratory (INL) Design A description. For plant aspects (e.g., reactor building size and leak rate) that are not described in the LANL and INL references , the analysts made assumptions needed to construct a MELCOR full-plant model. The HP R uses high assay, low-enrichment uranium (HALEU) fuel with steel cladding that uses heat pipes to transfer heat to a secondary Brayton air cycle. The core region is surrounded by a stainless-steel shroud, alumina reflector, core barrel and boron carbide neutron shield. The reactor is secured inside a below-grade cavity, with the operating floor located above the cavity. Example calculations are performed to show the plant response and MELCOR capabilities to characterize a range of accident conditions. The accidents selected for evaluation consider a range of degraded and failed modes of operation for key safety functions providing re activity control, the primary and secondary system heat removal, and the effectiveness of th e confinement natural circulation flow into the reactor cavity (i.e., a flow blockage).

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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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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.

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The supply chain attack pathway is being increasingly used by adversaries to bypass security controls and gain unauthorized access to sensitive networks and equipment (e.g., Critical Digital Assets). Cyber-attacks targeting supply chain generally aim to compromise the environments, products, or services of vendors and suppliers to inject, add, or substitute authentic software and hardware with malicious elements. These malicious elements are deemed to be authentic as they arise from the vendor or supplier (i.e., the supply chain). This research aims at providing a survey of technologies that have the potential to reduce exposure of sensitive networks and equipment to these attacks, thereby improving tamper resistance. The recent advances in the performance and capabilities of these technologies in recent years has increased their potential applications to reduce or mitigate exposure of the supply chain attack pathway. The focus being on providing an analysis of the benefits and disadvantages of smart cards, secure tokens, and elements to provide root of trust. This analysis provides evidence that these roots of trust can increase the technical capability of equipment and networks to authenticate changes to software and configuration thereby increasing resilience to some supply chain attacks, such as those related to logistics and ICT channels, but not development environment attacks.

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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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This report documents details of the microstructure and mechanical properties of -tin (Sn), that is used in the Tri-lab (Los Alamos National Laboratory (LANL), Lawrence Livermore National Laboratory (LLNL), Sandia National Laboratories (SNL)) collaboration project on Multi-phase Tin Strength. We report microstructural features detailing the crystallographic texture and grain morphology of as-received -tin from electron back scatter diffraction (EBSD). Temperature and strain rate dependent mechanical behavior was investigated by multiple compression tests at temperatures of 200K to 400K and strain rates of 0.0001 /s to 100 /s. Tri-lab tin showed significant temperature and strain rate dependent strength with no significant plastic anisotropy. A sample to sample material variation was observed from duplicate compression tests and texture measurements. Compression data was used to calibrate model parameters for temperature and rate dependent strength models, Johnson-Cook (JC), Zerilli-Armstrong (ZA) and Preston-Tonks-Wallace (PTW) strength models.

During the summer and fall of 2021, several functional area drills were held that focused on exercising Consequence Management’s (CM) ability to extract and use data from RadResponder for the purpose of answering intermediate-phase questions presented as technical inject requests for information (RFI) in Sandia National Laboratories (SNL) Consequence Management Operational System (COSMOS) software. The scenario chosen was that of Northern Lights 2016 (NL16) which was a large-scale nuclear power plant (NPP) release exercise in the state of Minnesota. The NL16 data was extracted from the Radiological Assessment and Monitoring System (RAMS) event where it was created and was reformatted for implanting to a new RadResponder event. Next, the beta-version of a laboratory sample data simulator was used to generate more sample data that was injected to the event. Five “mini-drills” were devised with each prompt defined by a data-based need. For each drill, a team of assessment and NARAC scientists worked the problem using the drill prompt and the available data in RadResponder. The teams held a kickoff meeting, had several days to work the problem, and then reported their results as well as observations in a hotwash. Several areas for improvement in both the software and process were identified during the course of these drills. This report will document the process of addressing each RFI and the discovered gaps in both software capability and methodology so that they can be considered for future development and investment by the CM and NIRT programs.

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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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Two classes of hydrogen gas are observed in pressurized EPDM. The H₂ gas with slower diffusional dynamics localizes away from crosslinks.

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This report is part of a series of six white papers, prepared jointly by the Proliferation Resistance and Physical Protection Working Group (PRPPWG) and the six System Steering Committees (SSCs) and provisional System Steering Committees (pSSCs). This publication is an update to a similar series published in 2011 presenting the status of Proliferation Resistance & Physical Protection (PR&PP) characteristics for each of the six systems selected by the Generation IV International Forum (GIF) for further research and development, namely: the Sodium-cooled fast Reactor (SFR), the Very high temperature reactor (VHTR), the gas-cooled fast reactor (GFR), the Molten salt reactor (MSR) and the Supercritical water–cooled reactor (SCWR). This white paper represents the status of Proliferation Resistance and Physical Protection (PR&PP) characteristics for the Very-High-Temperature Reactor (VHTR) reference designs selected by the Generation IV International Forum (GIF) VHTR System Steering Committee (SSC). The intent is to generate preliminary information about the PR&PP features of the VHTR reactor technology and to provide insights for optimizing their PR&PP performance for the benefit of VHTR system designers. It updates the VHTR analysis published in the 2011 report “Proliferation Resistance and Physical Protection of the Six Generation IV Nuclear Energy Systems”, prepared Jointly by the Proliferation Resistance and Physical Protection Working Group (PRPPWG) and the System Steering Committees and provisional System Steering Committees of the Generation IV International Forum, taking into account the evolution of both the systems, the GIF R&D activities, and an increased understanding of the PR&PP features. The white paper, prepared jointly by the GIF PRPPWG and the GIF VHTR SSC, follows the high-level paradigm of the GIF PR&PP Evaluation Methodology to investigate the key points of PR&PP features extracted from the reference designs of VHTRs under consideration in various countries. A major update from the 2011 report is an explicit distinction between prismatic block-type VHTRs and pebble-bed VHTRs. The white paper also provides an overview of the TRISO fuel and fuel cycle. For PR, the document analyses and discusses the proliferation resistance aspects in terms of robustness against State-based threats associated with diversion of materials, misuse of facilities, breakout scenarios, and production in clandestine facilities. Similarly, for PP, the document discusses the robustness against theft of material and sabotage by non-State actors. The document follows a common template adopted by all the white papers in the updated series.

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The BayoTech hydrogen generation system has been evaluated in terms of safety considerations at the NM Gas site. The consequence of a leak in different components in the system was evaluated in terms of plume dispersion and overpressure. Additionally, the likelihood of a leak scenario for different hydrogen components was identified. The worst-case plume dispersion cases, full-bore leaks, resulted in relatively large plumes. However, these cases were noted to be far less likely than the partial break cases that were evaluated. The partial break cases resulted in nearly negligible plume lengths. Similarly, the overpressure analysis of the full-bore break scenarios resulted in much larger overpressures than the partial break cases (which resulted in negligible overpressure at the lot line). There were several cases evaluated in the analysis that represented leak scenarios from both hydrogen and natural gas sources. Generally, the natural gas leak scenarios resulted in a smaller horizontal impact than that of hydrogen leaks. The worst-case consequence from a hydrogen leak resulted from the compressors, storage pods, or dispensing system. To consider the safety features that may isolate the leak, the consequence was evaluated at different times after the leak event to show the reduction of pressure. After 2 seconds, the plume dispersion from this event is contained within the perimeter of the site. The worst-case consequences show that the plume may disperse to adjacent facilities and to the street. When considering both likelihood and consequence, the risk may be considered low because the maximum frequency of a full-bore leak from any component within the hydrogen compound is 8.2 E-5/yr. This means that a full-bore leak is expected to occur less than once every 10,000 years. The risk can be further reduced by implementing mitigative countermeasures, such as CMU walls along the sides of the equipment compound. This would reduce the overall consequence of the worst-case dispersion scenarios (horizontal impact of plume). In terms of siting and safety analysis, the NFPA 2 code was used to provide a high-level evaluation of the current site plan. The most limiting equipment in terms of set-back distance are the compressors/storage units because of the high-pressure hydrogen. The site layout was evaluated for an acceptable location for the compression/storage unit based on NFPA 2 set-back distances. It is important to note that the NFPA 2 set-back distances consider both likelihood and consequence. This is important because the worst-case results evaluated herein also represent the least likely leak scenario. Other site-specific considerations were evaluated, including the parking shade structure with photovoltaic cells and refueling vehicles. These issues were dispositioned and determined to not present a safety risk.

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

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This report details a method to estimate the energy content of various types of seismic body waves. The method is based on the strain energy of an elastic wavefield and Hooke’s Law. We present a detailed derivation of a set of equations that explicitly partition the seismic strain energy into two parts: one for compressional (P) waves and one for shear (S) waves. We posit that the ratio of these two quantities can be used to determine the relative contribution of seismic P and S waves, possibly as a method to discriminate between earthquakes and buried explosions. We demonstrate the efficacy of our method by using it to compute the strain energy of synthetic seismograms with differing source characteristics. Specifically, we find that explosion-generated seismograms contain a preponderance of P wave strain energy when compared to earthquake-generated synthetic seismograms. Conversely, earthquake-generated synthetic seismograms contain a much greater degree of S wave strain energy when compared to explosion-generated seismograms.

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This report details how to successfully use the Fairfield Nodal ZLand seismic instruments to collect data, including preparation steps prior to deploying the instruments, how to record data during a field campaign, and how to retrieve recorded data from the instruments after their deployment. This guide will walk through each step for the novice user, as well as provide a checklist of critical steps for the advanced user to ensure successful, efficient field campaigns and seismic data collection. Currently, use of the seismic nodal instruments is highly limited due to the detailed nature and prior knowledge required to successfully set up, use, and retrieve data from these instruments. With this guide, all interested users will have the knowledge required to perform a seismic deployment and collect data with the Fairfield Nodal instruments.

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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.

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.

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.

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.

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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.

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.

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 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.

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.

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.

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.

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.

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.

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.

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.

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.