Publications

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Precise wording is important in every field of study, including operational procedures. Confusion in the wording “organic” and “inorganic” may have contributed to substitution of an organic kitty litter for an inorganic adsorbent used to prepare nuclear waste for disposal at an underground salt repository. Adsorbents prevent liquids like nitric acid from causing corrosion within the waste drums. However, combination of organic material with nitric acid can cause heat- and gas-generating reactions resulting in thermal runaway, rapid pressurization, and drum rupture. In 2014, waste Drum 68660 containing nitric acid-soaked organic kitty litter exploded and released transuranic waste into the repository. The cause of the accident was never identified. Here we show that the root cause of Drum 68660 igniting was restriction of the drum vent resulting in accelerated nitric acid chemistry, thermal runaway, and radiation dispersal.

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Metal hydride hydrogen compression utilizes a reversible heat-driven interaction of a hydride-forming metal alloy with hydrogen gas. This paper reports on the development of a laboratory scale two-stage Metal Hydride Compressor (MHC) system with a feed pressure of 150 bar delivering high purity H2 gas at outlet pressures up to 875 bar. Stage 1 and stage 2 AB₂ metal hydrides are identified based on experimental characterization of the pressure-composition-temperature (PCT) behavior of candidate materials. The selected metal hydrides are each combined with expanded natural graphite, increasing the thermal conductivity of the composites by an order of magnitude. These composites are integrated in two compressor beds with internal heat exchangers that alternate between hydrogenation and dehydrogenation cycles by thermally cycling between 20 °C and 150 °C. The prototype compressor achieved compression of hydrogen from 150 bar to 700 bar with an average flow rate of 33.6 g/hr.

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While the use of machine learning (ML) classifiers is widespread, their output is often not part of any follow-on decision-making process. To illustrate, consider the scenario where we have developed and trained an ML classifier to find malicious URL links. In this scenario, network administrators must decide whether to allow a computer user to visit a particular website, or to instead block access because the site is deemed malicious. It would be very beneficial if decisions such as these could be made automatically using a trained ML classifier. Unfortunately, due to a variety of reasons discussed herein, the output from these classifiers can be uncertain, rendering downstream decisions difficult. Herein, we provide a framework for: (1) quantifying and propagating uncertainty in ML classifiers; (2) formally linking ML outputs with the decision-making process; and (3) making optimal decisions for classification under uncertainty with single or multiple objectives.

Members of the Nuclear Criticality Safety (NCS) Program at Sandia National Laboratories (SNL) have updated the suite of benchmark problems developed to validate MCNP6 Version 2.0 for use in NCS applications. The updated NCS benchmark suite adds approximately 600 new benchmarks and includes peer review of all input files by two different NCS engineers (or one NCS engineer and one candidate NCS engineer). As with the originally released benchmark suite, the updated suite covers a broad range of fissile material types, material forms, moderators, reflectors, and neutron energy spectra. The benchmark suite provides a basis to establish a bias and bias uncertainty for use in NCS analyses at SNL.

Battery storage systems are increasingly being installed at photovoltaic (PV) sites to address supply-demand balancing needs. Although there is some understanding of costs associated with PV operations and maintenance (O&M), costs associated with emerging technologies such as PV plus storage lack details about the specific systems and/or activities that contribute to the cost values. This study aims to address this gap by exploring the specific factors and drivers contributing to utility-scale PV plus storage systems (UPVS) O&M activities costs, including how technology selection, data collection, and related and ongoing challenges. Specifically, we used semi-structured interviews and questionnaires to collect information and insights from utility-scale owners and operators. Data was collected from 14 semi-structured interviews and questionnaires representing 51.1 MW with 64.1 MWh of installed battery storage capacity within the United States (U.S.). Differences in degradation rate, expected life cycle, and capital costs are observed across different storage technologies. Most O&M activities at UPVS related to correcting under-performance. Fires and venting issues are leading safety concerns, and owner operators have installed additional systems to mitigate these issues. There are ongoing O&M challenges due the lack of storage-specific performance metrics as well as poor vendor reliability and parts availability. Insights from this work will improve our understanding of O&M consideration at PV plus storage sites.

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This document contains the design and operation principles for the wind turbine emulator (WTE) located in the Distributed Energy Technologies Laboratory (DETL) at Sandia National Laboratories (Sandia). The wind turbine emulator is a power hardware -in-the-loop (PHIL) representation of the research wind turbines located in Lubbock, Texas at the Sandia Scaled Wind Farm Technology (SWiFT) facility. This document describes installation and commissioning steps, and it provides references to component manuals and specifications.

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On October 1, 2022, sound level measurements were taken at various locations throughout Kirtland Air Force Base (KAFB) and Southeastern Albuquerque. The purpose was to support sound propagation modeling predictions and sound regulations for public exposure during the detonation of an approximately 300-pound energetic experiment. Ground Zero was located on Range 7 of Sandia Thunder Range (06647). A total of 8 measurement locations were identified (e.g., 5 on KAFB and 3 in the Southeastern Albuquerque neighborhoods).

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This report examines the localization of high frequency electromagnetic fields in general three-dimensional cavities along periodic paths between opposing sides of the cavity. The focus is on the case where the mirrors at the ends of the orbit are concave and have two different radii of curvature. The cases where these orbits lead to unstable localized modes are known as scars. The ellipsoidal coordinate system is utilized in the construction of the scarred modes. The field at the interior foci is examined as well as trigonometric projections along the periodic scarred ray path.

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Accurate representation of environmental controllers of soil organic carbon (SOC) stocks in Earth System Model (ESM) land models could reduce uncertainties in future carbon–climate feedback projections. Using empirical relationships between environmental factors and SOC stocks to evaluate land models can help modelers understand prediction biases beyond what can be achieved with the observed SOC stocks alone. In this study, we used 31 observed environmental factors, field SOC observations (n = 6,213) from the continental United States, and two machine learning approaches (random forest [RF] and generalized additive modeling [GAM]) to (a) select important environmental predictors of SOC stocks, (b) derive empirical relationships between environmental factors and SOC stocks, and (c) use the derived relationships to predict SOC stocks and compare the prediction accuracy of simpler model developed with the machine learning predictions. Out of the 31 environmental factors we investigated, 12 were identified as important predictors of SOC stocks by the RF approach. In contrast, the GAM approach identified six (of those 12) environmental factors as important controllers of SOC stocks: potential evapotranspiration, normalized difference vegetation index, soil drainage condition, precipitation, elevation, and net primary productivity. The GAM approach showed minimal SOC predictive importance of the remaining six environmental factors identified by the RF approach. Our derived empirical relations produced comparable prediction accuracy to the GAM and RF approach using only a subset of environmental factors. The empirical relationships we derived using the GAM approach can serve as important benchmarks to evaluate environmental control representations of SOC stocks in ESMs, which could reduce uncertainty in predicting future carbon–climate feedbacks.

Viscoelastic rebound of the solid Earth upon the removal of ice loads has the potential to inhibit marine ice sheet instability, thereby forestalling ice-sheet retreat and global mean sea-level rise. The timescale over which the solid Earth - ice sheet system responds to changes in ice thickness and bedrock topography places a strong control on the spatiotemporal influence of this negative feedback mechanism. In this study, we assess the impact of solid-earth rheological structure on model projections of the retreat of Thwaites Glacier, West Antarctica, and the concomitant sea-level rise by coupling the dynamic ice sheet model MALI to a regional glacial isostatic adjustment (GIA) model. We test the sensitivity of model projections of ice-sheet retreat and associated sea-level rise across a range of four different solid-earth rheologies, forced by standard ISMIP6 ocean and atmospheric datasets for the RCP8.5 climate scenario. These model parameters are applied to 500-year, coupled ice-sheet - GIA simulations. For the mantle viscosity best supported by observations, the negative GIA feedback leads to a reduction in mass loss that remains above 20% after about a hundred years. Mass-loss reduction peaks at 50% around 2300, which is when a control simulation without GIA experiences its maximum rate of retreat. For a weaker solid-earth rheology that is unlikely but compatible with observational uncertainty, mass loss reduction remains above 50% after 2150. At 2100, mass loss reduction is 10% for the best-fit rheology and 25% for the weakest rheology. At the same time, we estimate that water expulsion from the rebounding solid Earth beneath the ocean near Thwaites Glacier may increase sea-level rise by up to 20% at five centuries. Additionally, the reduction in ice-sheet retreat caused by GIA is substantially reduced under stronger climate forcings, suggesting that the stabilizing feedback of GIA will also be an indirect function of emissions scenario. We hypothesize that feedbacks between the solid Earth - ice sheet system are controlled by a competition between the spatial extent and timescale of bedrock uplift relative to the rate of grounded ice retreat away from the region of most rapid unloading. Although uncertainty in solid-earth rheology leads to large uncertainty in future sea-level rise contribution from Thwaites Glacier, under all plausible parameters the GIA effects are too large to be ignored for future projections of Thwaites Glacier of more than a century.

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