Publications

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The fabrication of long-lived electrical contacts to thermoelectric Bi₂Te₃-based modules is a challenging problem due to chemical incompatibilities and rapid diffusion rates. Previously, technical guidance from SAND report 2015-7203 selected electroplated Au as the preferred method for fabrication of long-lived contacts because of concerns that the grain structure of sputtered/physical vapor deposited (PVD) Au contacts can evolve during aging. We have re-evaluated PVD Au contacts and show that they are appropriate for long-life service. We measure grain size and morphology at different aging times under accelerated temperature gradient conditions, and we show that the PVD Au contacts are stable and remain relatively unchanged. The PVD Au fabricated here is not subject to the deterioration observed in the previous report.

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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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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.