Publications

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Disposal of large, heat-generating waste packages containing the equivalent of 21 pressurized water reactor (PWR) assemblies or more is among the disposal concepts under investigation for a future repository for spent nuclear fuel (SNF) in the United States. Without a long (>200 years) surface storage period, disposal of 21-PWR or larger waste packages (especially if they contain high-burnup fuel) would result in in-drift and near-field temperatures considerably higher than considered in previous generic reference cases that assume either 4-PWR or 12-PWR waste packages (Jové Colón et al. 2014; Mariner et al. 2015; 2017). Sevougian et al. (2019c) identified high-temperature process understanding as a key research and development (R&D) area for the Spent Fuel and Waste Science and Technology (SFWST) Campaign. A two-day workshop in February 2020 brought together campaign scientists with expertise in geology, geochemistry, geomechanics, engineered barriers, waste forms, and corrosion processes to begin integrated development of a high-temperature reference case for disposal of SNF in a mined repository in a shale host rock. Building on the progress made in the workshop, the study team further explored the concepts and processes needed to form the basis for a high-temperature shale repository reference case. The results are described in this report and summarized..

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Arm processors have been explored in HPC for several years, however there has not yet been a demonstration of viability for supporting large-scale production workloads. In this paper, we offer a retrospective on the process of bringing up Astra, the first Petascale supercomputer based on 64-bit Arm processors, and validating its ability to run production HPC applications. Through this process several immature technology gaps were addressed, including software stack enablement, Linux bugs at scale, thermal management issues, power management capabilities, and advanced container support. From this experience, several lessons learned are formulated that contributed to the successful deployment of Astra. These insights can be helpful to accelerate deploying and maturing other first-seen HPC technologies. With Astra now supporting many users running a diverse set of production applications at multi-thousand node scales, we believe this constitutes strong supporting evidence that Arm is a viable technology for even the largest-scale supercomputer deployments.

There is an emerging consciousness in India of the importance of nuclear security and safety. Motivated by a combination of rapid growth in its civil nuclear sector, heightened scrutiny of recent nuclear accidents around the world, and the deteriorating regional security environment, India has pushed to adopt measures to strengthen and enhance its nuclear security and safety governance structures. India recognizes that the various recent global nuclear security initiatives are in its own best interest and has been an enthusiastic participant in the Nuclear Security Summit process. Today, India demonstrates a greater willingness to showcase its nuclear security arrangements before the public and has undertaken many institutional, legal, and operational reforms to maintain international regime compliance. This study takes a comprehensive look at India's approach to nuclear security and critically examines the physical security measures the country has put in place. Particular focus is placed on the evolution and strengths, as well as weaknesses, of the country's nuclear security institutions, instruments, practices, and culture. Given that the strengthening of India's nuclear security governance is an ongoing endeavor, the paper also puts forward a number of policy recommendations.

Germanium–antimony–telluride has emerged as a nonvolatile phase change memory material due to the large resistivity contrast between amorphous and crystalline states, rapid crystallization, and cyclic endurance. Improving thermal phase stability, however, has necessitated further alloying with optional addition of a quaternary species (e.g., C). In this work, the thermal transport implications of this additional species are investigated using frequency-domain thermoreflectance in combination with structural characterization derived from x-ray diffraction and Raman spectroscopy. Specifically, the room temperature thermal conductivity and heat capacity of (Ge₂Sb₂Te₅)_1–xC_x are reported as a function of carbon concentration (x ≤ 0:12) and anneal temperature (T ≤ 350 °C) with results assessed in reference to the measured phase, structure, and electronic resistivity. Phase stability imparted by the carbon comes with comparatively low thermal penalty as materials exhibiting similar levels of crystallinity have comparable thermal conductivity despite the addition of carbon. The additional thermal stability provided by the carbon does, however, necessitate higher anneal temperatures to achieve similar levels of structural order.

We present experimental results from the first systematic study of performance scaling with drive parameters for a magnetoinertial fusion concept. In magnetized liner inertial fusion experiments, the burn-averaged ion temperature doubles to 3.1 keV and the primary deuterium-deuterium neutron yield increases by more than an order of magnitude to 1.1×1013 (2 kJ deuterium-tritium equivalent) through a simultaneous increase in the applied magnetic field (from 10.4 to 15.9 T), laser preheat energy (from 0.46 to 1.2 kJ), and current coupling (from 16 to 20 MA). Individual parametric scans of the initial magnetic field and laser preheat energy show the expected trends, demonstrating the importance of magnetic insulation and the impact of the Nernst effect for this concept. A drive-current scan shows that present experiments operate close to the point where implosion stability is a limiting factor in performance, demonstrating the need to raise fuel pressure as drive current is increased. Simulations that capture these experimental trends indicate that another order of magnitude increase in yield on the Z facility is possible with additional increases of input parameters.

Maritime trade accounts for approximately 80 percent of international commerce. The high volume of vessels traversing domestic and international ports makes port areas prime targets for terrorism as well as illegal trafficking of drugs and arms (conventional or nuclear). Port security is therefore a worldwide concern affecting global economies, freedom of movement, and national security. However, extensive port monitoring is inherently complex and time consuming — making it truly viable only via an automated framework that can detect potential illicit activity and alert authorities in a timely manner. The development of image processing algorithms for this purpose requires access to large, labeled datasets that cover the breadth of targets of interest as well as the environments that they are observed within. Curated and labeled datasets of this nature are of enormous value to Sandia's Defense Nuclear Nonproliferation and National Security Program portfolios, as well as to Sandia's machine learning/automatic target recognition (ML/ATR) algorithm development and R&D communities. The goal of this project is to create a commercial satellite imagery dataset of labeled maritime vessels in port areas to support the development of ML/ATR algorithms for port security nonproliferation purposes. This dataset — Port Security Nonproliferation Vessel Overhead Imagery Dataset (PSN VOID) — has the potential to support a variety of other ancillary missions, such as maritime domain awareness, domestic and international security, drug interdiction, and weapons trafficking.

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Temperature checks for fever are extensively used for preliminary COVID screenings but are ineffective during the incubation stage of infection when a person is asymptotic. Researchers at the European Centre for Disease Prevention and Control concluded that approximately 75% of passengers infected with COVID-19 and traveling from affected Chinese cities would not be detected by early screening. Core body temperature is normally kept within a narrow range and has the smallest relative standard deviation of all vital signs. Heat in the body is prioritized around internal organs at the expense of the periphery by controlling blood flow. In fact, blood flow to the skin may vary by a factor of 100 depending on thermal conditions. This adaptation causes rapid temperature fluctuations in different skin regions from changes in cardiac output, metabolism, and likely cytokine diffusion during inflammation that would not be seen in average core body temperature. Current IR and thermal scanners used for temperature checks are not necessarily reflective of core body temperatures and require cautious interpretation as they frequently result in false positive and false negative diagnosis. Hand held thermometers measure average skin temperatures and can get readings that differ from core body temperature by as much as 7°. Rather than focusing on a core body temperature threshold assessment we believe that variability of temperature patterns using a novel wearable transdermal microneedle sensor will be more sensitive to infections in the incubation stage and propose to develop a wearable transdermal temperature sensor using established Sandia microneedle technology for pre symptomatic COVID screening that can additionally be used to monitor disease progression at later stages.

The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Spent Fuel & Waste Disposition (SFWD) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and highlevel nuclear waste (HLW). A high priority for SFWST disposal R&D is to develop a disposal system modeling and analysis capability for evaluating disposal system performance for nuclear waste in geologic media. This report describes fiscal year (FY) 2020 advances of the Geologic Disposal Safety Assessment (GDSA) Framework and PFLOTRAN development groups of the SFWST Campaign. The common mission of these groups is to develop a geologic disposal system modeling capability for nuclear waste that can be used to probabilistically assess the performance of disposal options and generic sites. The capability is a framework called GDSA Framework that employs high-performance computing (HPC) capable codes PFLOTRAN and Dakota.

Sandia Materials Science Investment Area contributed to the SARS-CoV-2 virus and COVID-19 disease which represent the most significant pandemic threat in over 100 years. We completed a series of 7, short duration projects to provide innovative materials science research and development in analytical techniques to aid the neutralization of COVID-19 on multiple surfaces, approaches to rapidly decontaminate personal protective equipment, and pareto assessment of construction materials for manufacturing personal protective equipment. The developed capabilities and processes through this research can help US medical personnel, government installations and assets, first responders, state and local governments, and multiple federal agencies address the COVID-19 Pandemic.

This report documents a new approach to designing disease control policies that allocate scarce testing, contact tracing, and vaccination resources to better control community transmission of COVID19 or similar diseases. The Adaptive Recovery Model (ARM) combines a deterministic compartmental disease model with a stochastic network disease propagation model to enable us to simulate COVID-19 community spread through the lens of two complementary modeling motifs. ARM contact networks are derived from cell-phone location data that have been anonymized and interpreted as individual arrivals to specic public locations. Modeling disease spread over these networks allows us to identify locations within communities conducive to rapid disease spread. ARM applies this model- and data-derived abstractions of community transmission to evaluate the effectiveness of disease control measures including targeted social distancing, contact tracing, testing and vaccination. The architecture of ARM provides a unique capacity to help decision makers understand how best to deploy scarce testing, tracing and vaccination resources to minimize disease-spread potential in a community. This document details the novel mathematical formulations underlying ARM, presents a dynamical stability analysis of the deterministic model components, a sensitivity analysis of control parameters and network structure, and summarizes a process for deriving contact networks from cell-phone location data. An example use case steps through applying ARM to evaluate three targeted social distancing policies using Bernalillo County, New Mexico as an exemplar test locale. This step-by-step analysis demonstrates how ARM can be used to measure the relative performance of competing public health policies. Initial scenario tests of ARM shows that ARMs design focus on resource utilization rather than simple incidence prediction can provide decision makers with additional quantitative guidance for managing ongoing public health emergencies and planning future responses.

In Germany, rock salt formations are a possible host rock taken into account for the safe disposal of heat-emitting radioactive waste. With respect to crushed salt will be used in the repository for backfilling of open cavitied (using dry material). With time, the crushed salt will be compacted by the convergence of the host rock and reaches porosities comparable with the rock salts. The compaction behaviour of crushed salt has been investigated within the last 40 years, however, its behaviour at low porosities and the resulting low permeabilities becomes relevant with the introduction of the approach of the containment providing rock zone. In the current state, the database and process understanding have some important gaps in knowledge referring the material behaviour, existing laboratory and numerical models, especially for the porosity range. The objective of this project was the development of methods and strategies for the reduction of deficits in the prediction of crushed salt compaction leading to an improvement of the prognosis quality. It includes the development of experimental methods for determining crushed salt properties in the range of low porosities, the enhancement of process understanding and the investigation and development of existing numerical models.

This SAND Report provides an overview of AniMACCS, the animation software developed for the MELCOR Accident Consequence Code System (MACCS). It details what users need to know in order to successfully generate animations from MACCS results, to include information on the capabilities, requirements, testing, limitations, input settings, and problem reporting instructions for AniMACCS version 1.3. Supporting information is provided in the appendices, such as guidance on required input files using both WinMACCS and running MACCS from the command line. This page left blank

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Most current flight systems are dependent on GPS for navigation. Recently, however, navigation in GPS-denied environments has become an area of intensive research. Additional navigation sensor data can be obtained from visual observations (stars or terrain), inertial measurement units, radar, measurements of the local magnetic field, or perhaps even gravity. Absolute and relative positioning via magnetic field measurements have been shown to be viable in many applications including ground navigation, low altitude aircraft flight, and spaceflight. There is greater variability in the magnetic field over shorter distances when flying at low altitude and in ground applications, leading to more accurate positioning. However, ground-based magnetic navigation is often heavily influenced by man-made structures, especially in urban environments. This is not the case for airborne magnetic navigation since the influence of buildings, roads, etc. is negligible for typical aircraft altitudes. For absolute magnetic navigation, the positioning accuracy decreases as altitude increases for a given vehicle velocity, but the observed time variability in the field can be reclaimed by traveling faster through the field. Thus, navigation accuracy becomes a balance of speed and altitude since the higher altitude can be counterbalanced by higher velocity. To understand these effects quantitatively, we explored various techniques to aid a simulated inertial measurement unit with magnetic information. Using a technique known as two-dimensional magnetic map matching, we simulated the performance of airborne magnetic navigation at fixed speed while varying the altitude, flight direction, magnetometer data collection time, reference magnetic map bias error, and type of trajectory (over land or over ocean).

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