Publications

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This report provides recommendations to improve the assessment method of the Federal Radiological Monitoring and Assessment Center (FRMAC) for the ingestion of crops contaminated with radionuclides. The current FRMAC method of calculating investigation levels (ILs) and crop derived response levels (DRLs) is detailed. Recommended modifications to these calculations are presented based on the following aspects: handling radionuclide mixtures, no immediate equilibrium, washing of contaminated crops, and updated dietary intake rates.

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Picuris Pueblo is a small tribal community in Northern New Mexico consisting of about 306 members and 86 homes. Picuris Pueblo has made advances with renewable energy implementation, including the installation of a 1 megawatt photovoltaic (PV) array. This array has provided the tribe with economic and other benefits that contribute toward the tribe's goal of tribal sovereignty. The tribe is seeking to implement more PV generation as well as battery energy storage systems. Picuris Pueblo is considering different implementation methods, including the formation of a microgrid system. This report studies the potential implementation of a PV and battery storage microgrid system and the associated benefits and challenges. The benefits of a microgrid system include cost savings, increased resiliency, and increased tribal sovereignty and align with the tribe's goals of becoming energy independent and lowering the cost of electricity.

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Scribe3D© is an application designed to allow users to develop risk threat scenarios on a 3D image of a facility/location of the users choosing. Once the facility/terrain is loaded, entities such as personnel, vehicles (ground and air), and structures/objects can be added. Then the user can make the entities move around the facility/terrain. Responder and Adversary forces can be outfitted with weapons and move from place to place on foot or in vehicles. In Scribe3D©, once the entities are identified, they can be moved to visualize realistic scenario situations by using a suite of tools to enhance decision making and scenario development. This manual can guide you through setting up and editing all aspects of Scribe3D© and guide you to the creation of a Scenario Exercise.

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Unmanned aircraft systems (UAS/drones) are rapidly evolving and are considered an emerging threat by nuclear facilities throughout the world. Due to the wide range of UAS capabilities, members of the workforce and security/response force personnel need to be prepared for a variety of drone incursion situations. Tabletop exercises are helpful, but actual live exercises are often needed to evaluate the quick chain of events that might ensue during a real drone fly-in and the essential kinds of information that will help identify the type of drone and pilot. Even with drone detection equipment, the type of UAS used for incursion drills can have a major impact on detection altitude and finding the UAS in the sky. Using a variety of UAS, the U.S. National Nuclear Security Administration (NNSA) Office of International Nuclear Security (INS) would like to offer partners the capability of adding actual UAS into workforce and response exercises to improve overall UAS awareness as well as the procedures that capture critical steps in dealing with intruding drones.

This report represents completion of milestone deliverable M2SF-23SN010309082 Annual Status Update for OWL due on November 30, 2022. It provides the status of fiscal year 2022 (FY2022) updates for the Online Waste Library (OWL).

Commercial vendors, trying to tap into the physical protection of critical infrastructure, are offering nuclear facilities the opportunity to borrow detection counter-unmanned aircraft systems (CUAS) equipment to survey the airspace over and around the facility. However, using one vendor or method of detection (e.g., radio frequency [RF], radar, acoustic, visual) will not necessarily provide a complete airspace profile since no single method can detect all UAS threats. Using several detection technologies, the unmanned aircraft systems (UAS) Team, who supports the U.S. National Nuclear Security Administration (NNSA) Office of International Nuclear Security (INS), would like to offer partners a comprehensive airspace profile of the types and frequency of UAS that fly within and around critical infrastructure. Improved UAS awareness will aid in the risk assessment process.

We present Q Framework: a verification framework used at Sandia National Laboratories. Q is a collection of tools used to verify safety and correctness properties of high-consequence embedded systems and captures the structure and compositionality of system specifications written with state machines in order to prove system-level properties about their implementations. Q consists of two main workflows: 1) compilation of temporal properties and state machine models (such as those made with Stateflow) into SMV models and 2) generation of ACSL specifications for the C code implementation of the state machine models. These together prove a refinement relation between the state machine model and its C code implementation, with proofs of properties checked by NuSMV (for SMV models) and Frama-C (for ACSL specifications).

Metal-assisted chemical etching (MACE) is a flexible technique for texturing the surface of semiconductors. In this work, we study the spatial variation of the etch profile, the effect of angular orientation relative to the crystallographic planes, and the effect of doping type. We employ gold in direct contact with germanium as the metal catalyst, and dilute hydrogen peroxide solution as the chemical etchant. With this catalyst-etchant combination, we observe inverse-MACE, where the area directly under gold is not etched, but the neighboring, exposed germanium experiences enhanced etching. This enhancement in etching decays exponentially with the lateral distance from the gold structure. An empirical formula for the gold-enhanced etching depth as a function of lateral distance from the edge of the gold film is extracted from the experimentally measured etch profiles. The lateral range of enhanced etching is approximately 10–20 µm and is independent of etchant concentration. At length scales beyond a few microns, the etching enhancement is independent of the orientation with respect to the germanium crystallographic planes. The etch rate as a function of etchant concentration follows a power law with exponent smaller than 1. The observed etch rates and profiles are independent of whether the germanium substrate is n-type, p-type, or nearly intrinsic.

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As machine learning (ML) models are deployed into an ever-diversifying set of application spaces, ranging from self-driving cars to cybersecurity to climate modeling, the need to carefully evaluate model credibility becomes increasingly important. Uncertainty quantification (UQ) provides important information about the ability of a learned model to make sound predictions, often with respect to individual test cases. However, most UQ methods for ML are themselves data-driven and therefore susceptible to the same knowledge gaps as the models themselves. Specifically, UQ helps to identify points near decision boundaries where the models fit the data poorly, yet predictions can score as certain for points that are under-represented by the training data and thus out-of-distribution (OOD). One method for evaluating the quality of both ML models and their associated uncertainty estimates is out-of-distribution detection (OODD). We combine OODD with UQ to provide insights into the reliability of the individual predictions made by an ML model.

The dynamics of the gold–silicon eutectic reaction in limited dimensions were studied using in situ transmission electron microscopy and scanning transmission electron microscopy heating experiments. The phase transformation, viewed in both plan-view and cross-section of the film, occurs through a complex combination of dislocation and grain boundary motion and diffusion of silicon along gold grain boundaries, which results in a dramatic change in the microstructure of the film. The conversion observed in cross-section shows that the eutectic mixture forms at the Au–Si interface and proceeds into the Au film at a discontinuous growth rate. This complex process can lead to a variety of microstructures depending on sample geometry, heating temperature, and the ratio of gold to silicon which was found to have the largest impact on the eutectic microstructure. The eutectic morphology varied from dendrites to hollow rectangular structures to Au–Si eutectic agglomerates with increasing silicon to gold ratio. Graphical abstract: [Figure not available: see fulltext.]

This is the user manual for EMPIRE, a simulation code for electromagnetics and plasma physics.

Recently, the study of topological structures in photonics has garnered significant interest, as these systems can realize robust, nonreciprocal chiral edge states and cavity-like confined states that have applications in both linear and nonlinear devices. However, current band theoretic approaches to understanding topology in photonic systems yield fundamental limitations on the classes of structures that can be studied. Here, we develop a theoretical framework for assessing a photonic structure’s topology directly from its effective Hamiltonian and position operators, as expressed in real space, and without the need to calculate the system’s Bloch eigenstates or band structure. Using this framework, we show that nontrivial topology, and associated boundary-localized chiral resonances, can manifest in photonic crystals with broken time-reversal symmetry that lack a complete band gap, a result that may have implications for new topological laser designs. Finally, we use our operator-based framework to develop a novel class of invariants for topology stemming from a system’s crystalline symmetries, which allows for the prediction of robust localized states for creating waveguides and cavities.

Dr. Fitzgerald, a postdoc at Sandia National Laboratories, works in a materials of mechanics group characterizing material properties of ductile materials. Her presentation focuses specifically on increasing throughput of coefficient of thermal expansion (CTE) measurements with the use of optical strain measurements, called digital image correlation (DIC). Currently, the coefficient of thermal expansion is found through a time intensive process called dilatometry. There are multiple types of dilatometers. One type, a double push rod mechanical dilatometer, uses and LVDT to measure the expansion of a specimen in one direction. It uses a reference material with known properties to determine the CTE of the specimen in question. Testing about 500 samples using the double push rod mechanical dilatometer would take about 2 years if testing Monday through Friday, because the reference material needs to be at a constant temperature and heating must done slowly to ensure no thermal gradients across the rod. A second type, scissors type dilatometer, pinches a sample using a “scissor-like” appendage that also uses a LVDT to measure thermal expansion as the sample is heated. Finally, laser dilatometry, was created to provide a non-contact means to measure thermal expansion. This process greatly reduces the time required to setup a measurement but is still only able to measure one sample at a time. The time required to test 500 samples gets reduced to 3.5 weeks. Additionally, to measure expansion in different directions, multiple lasers must be used. Dr. Fitzgerald solved this conundrum by using an optical measurement technique called digital image correlation to create strain maps in multiple orientations as well as measuring multiple samples at once. Using this technique, Dr. Fitzgerald can test 500 samples, conservatively, in 2 days.

We have demonstrated focused ion implantation for fabrication of single atom devices and nanofabrication. This is a viable solution for prototyping - fast and easy! There is on-going work in diamond, SiN, SiC, hBN, GaN, AlGan, etc. A new liquid metal alloy ion source development is on-going. There is a pathway towards deterministic defect centers in wide bandgap materials using FIB implantation.

On July 11, 2022, Sandia National Laboratories in California (SNL/CA) submitted a Response to Regional Water Quality Control Board Comments on Soil Sampling Results for Closure of a Portion of SWMU #16 in response to the February 16,2022 San Francisco Bay Regional Water Quality Control Board’s (SFRWQCB) letter requesting supporting information for the recommended closure of 7,700 linear feet of abandoned sewer lines. On August 18, 2022, SFRWQCB further requested a Sampling and Analysis Plan (SAP) for additional “step-out” sampling to delineate the potential presence of benzidine near borehole BH-056, which is located near the former sewer line. SNL/CA is in the process of contracting Weiss Associates (Weiss) to perform and oversee the boring, sampling, analysis, and report development to determine the potential presence and extent of benzidine. This document outlines the work that is anticipated, including the development of the SAP, to complete the investigation and submit a final report to the SFRWQCB. The work proposed by Weiss provides an estimated schedule for completing the investigation and developing the addendum Part II SAP for the project. In addition, Weiss provided a preliminary estimate of the sample locations (see Attachment A) which serve as addendum Part I of the SAP requested by the SFRWQCB. The contractor will submit the addendum Part II SAP, to satisfy the SFRWQCB requirement, before proceeding with any work.

This report describes research and development (R&D) activities conducted during Fiscal Year 2022 (FY22) specifically related to the Engineered Barrier System (EBS) R&D Work Package in the Spent Fuel Waste Science and Technology (SFWST) Campaign supported by the United States (U.S.) Department of Energy (DOE). The R&D activities focus on understanding EBS component evolution and interactions within the EBS, as well as interactions between the host media and the EBS. The R&D team represented in this report consists of individuals from Sandia National Laboratories, Lawrence Berkeley National Laboratory (LBNL), Los Alamos National Laboratory (LANL), and Vanderbilt University. EBS R&D work also leverages international collaborations to ensure that the DOE program is active and abreast of the latest advances in nuclear waste disposal.

High aspect ratio metal nanostructures are commonly found in a broad range of applications such as electronic compute structures and sensing. The self-heating and elevated temperatures in these structures, however, pose a significant bottleneck to both the reliability and clock frequencies of modern electronic devices. Any notable progress in energy efficiency and speed requires fundamental and tunable thermal transport mechanisms in nanostructured metals. In this work, time-domain thermoreflectance is used to expose cross-plane quasi-ballistic transport in epitaxially grown metallic Ir(001) interposed between Al and MgO(001). Thermal conductivities ranges from roughly 65 (96 in-plane) to 119 (122 in-plane) W m−1 K−1 for 25.5–133.0 nm films, respectively. Further, low defects afforded by epitaxial growth are suspected to allow the observation of electron–phonon coupling effects in sub-20 nm metals with traditionally electron-mediated thermal transport. Via combined electro-thermal measurements and phenomenological modeling, the transition is revealed between three modes of cross-plane heat conduction across different thicknesses and an interplay among them: electron dominant, phonon dominant, and electron–phonon energy conversion dominant. The results substantiate unexplored modes of heat transport in nanostructured metals, the insights of which can be used to develop electro-thermal solutions for a host of modern microelectronic devices and sensing structures.

The purpose of this sampling event was to determine if the observation point (inside the MFCP) could be relocated from 74 feet away to 21 feet from ground zero and to determine how much attenuation is provided by the MFCP. The MFCP provides noise attenuation to ensure Members of the Workforce (MOW) exposure to impact noise is below the Occupational Exposure Limit (OEL) of 140 dBC. The MFCP will be used for future tests under similar configurations. Please note that during each test shot, MOW was located inside MFCP that was 74 feet from ground zero and donned hearing protection (e.g., ear plugs with a minimum noise reduction rating of 23).

This report represents the 1st shot (in a series of 8) conducted on September 15, 2022. One 10 lb C4 charge (along with ~200g of Potassium Bromide (KBr)) was detonated inside 9920 North Pad Boom Box. Noise sampling was performed at several points on Site 9920 to characterize the noise mitigation provided by the block structure. This data will help inform safe locations for Members of the Workforce (MOWs) to be located during future testing with similar net explosive weights. During the test, all MOW/site visitors were bunkered inside Building 9926/Mobile Firing Control Point (MFCP) to prevent personnel exposure to any hazards associated with the testing

Elastomeric rubbers serve a vital role as sealing materials in the hydrogen storage and transport infrastructure. With applications including O-rings and hose-liners, these components are exposed to pressurized hydrogen at a range of temperatures, cycling rates, and pressure extremes. Cyclic (de)pressurization is known to degrade these materials through the process of cavitation. This readily visible failure mode occurs as a fracture or rupture of the material and is due to the oversaturated gas localizing to form gas bubbles. Computational modeling in the Hydrogen Materials Compatibility Program (H-Mat), co-led by Sandia National Laboratories and Pacific Northwest National Laboratory, employs multi-scale simulation efforts to build a predictive understanding of hydrogen-induced damage in materials. Modeling efforts within the project aim to provide insight into how to formulate materials that are less sensitive to high-pressure hydrogen-induced failure. In this document, we summarize results from atomistic molecular dynamics simulations, which make predictive assessments of the effects of compositional variations in the commonly used elastomer, ethylene propylene diene monomer (EPDM).

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Grid operating security studies are typically employed to establish operating boundaries, ensuring secure and stable operation for a range of operation under NERC guidelines. However, if these boundaries are severely violated, existing system security margins will be largely unknown, as would be a secure incremental dispatch path to higher security margins while continuing to serve load. As an alternative to the use of complex optimizations over dynamic conditions, this work employs the use of machine learning to identify a sequence of secure state transitions which place the grid in a higher degree of operating security with greater static and dynamic stability margins. Several reinforcement learning solution methods were developed using deep learning neural networks, including Deep Q-learning, Mu-Zero, and the continuous algorithms Proximal Reinforcement Learning, and Advantage Actor Critic Learning. The work is demonstrated on a power grid with three control dimensions but can be scaled in size and dimensionality, which is the subject of ongoing research.

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A collection of x-ray computed tomography scans of candy.

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Electric Vehicles (EV) present a unique challenge to electric power system (EPS) operations because of the potential magnitude and timing of load increases due to EV charging. Time-of-Use (TOU) electricity pricing is an established way to reduce peak system loads. It is effective at shifting the timing of some customer-activated residential loads – such as dishwashers, washing machines, or HVAC systems – to off-peak periods. EV charging, though, can be larger than typical residential loads (up to 19.2 kW) and may have on-board controls that automatically begin charging according to a pre-set schedule, such as when off-peak periods begin. To understand and quantify the potential impact of EV charging's response to TOU pricing, this paper simulates 10 distribution feeders with predicted 2030 EV adoption levels. The simulation results show that distribution EPS experience an increase in peak demand as high as 20% when a majority of the charging begins immediately after on-peak times end, as might occur if EV charging is automatically scheduled. However, if charging start times are randomized within the off-peak period, EV charging is spread out and the simulations showed a decrease in the peak load to be 5% lower than results from simulations that did not implement TOU rates.

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The HyRAM+ software toolkit provides a basis for conducting quantitative risk assessment and consequence modeling for hydrogen, natural gas, and autogas systems. HyRAM+ is designed to facilitate the use of state-of-the-art models to conduct robust, repeatable assessments of safety, hazards, and risk. HyRAM+ integrates deterministic and probabilistic models for quantifying leak sizes and rates, predicting physical effects, characterizing hazards (thermal effects from jet fires, overpressure effects from delayed ignition), and assessing impacts on people. HyRAM+ is developed at Sandia National Laboratories to support the development and revision of national and international codes and standards, and to provide developed models in a publicly-accessible toolkit usable by all stakeholders. This document provides a description of the methodology and models contained in HyRAM+ version 5.0. The most significant change for HyRAM+ version 5.0 from HyRAM+ version 4.1 is the ability to model blends of different fuels. HyRAM+ was previously only suitable for use with hydrogen, methane, or propane, with users having the ability to use methane as a proxy for natural gas and propane as a proxy for autogas/liquefied petroleum gas. In version 5.0, real natural gas or autogas compositions can be modeled as the fuel, or even blends of natural gas with hydrogen. These blends can be used in the standalone physics models, but not yet in the quantitative risk assessment mode of HyRAM+.

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This work presents the development of a multistaged stabilized continuation for the three-dimensional unpowered hypersonic trajectory planning problem using indirect optimal control methods. The stabilized continuation method is noniterative and guaranteed to terminate within a finite number of floating point operations, thereby making it well suited for onboard autonomous implementations. We present a multistage formulation of the stabilized continuation scheme that involves starting with a “loose” integration tolerance during the first stage and ramping up toward a “strict” integration tolerance through subsequent stages. An important benefit of this approach is that even when the solution to the underlying optimal control problem is numerically unstable, such as with the hypersonic vehicle footprint generation problem, the stabilized continuation algorithm is shown to be successful in finding a solution while providing some additional insights into the underlying cause of the numerical instability.

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Photovoltaic (PV) performance is affected by reversible and irreversible losses. These can typically be mitigated through responsive and proactive operations and maintenance (O&M) activities. However, to generate profit, the cost of O&M must be lower than the value of the recovered electricity. This value depends both on the amount of recovered energy and on the electricity prices, which can vary significantly over time in spot markets. The present work investigates the impact of the electricity price variability on the PV profitability and on the related O&M activities in Italy, Portugal, and Spain. It is found that the PV revenues varied by 1.6 × to 1.8 × within the investigated countries in the last 5 years. Moreover, forecasts predict higher average prices in the current decade compared to the previous one. These will increase the future PV revenues by up to 60% by 2030 compared to their 2015–2020 mean values. These higher revenues will make more funds available for better maintenance and for higher quality components, potentially leading to even higher energy yield and profits. Linearly growing or constant price assumptions cannot fully reproduce these expected price trends. Furthermore, significant price fluctuations can lead to unexpected scenarios and alter the predictions.

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Self-determination has been an on-going effort for Native American people and gained much traction with the passing of The Energy Policy Act of 2005, which included the Indian Tribal Energy Development and Self-Determination Act. Congress passed this act to assist Native American tribes and Alaska Native villages with planning, development, and assistance to achieve their energy goals. The Ute Mountain Ute Tribe (UMUT) has relied on oil and natural gas for economic support the last 70 years. Burning fossil fuels, along with oil and gas development, decreases the quality of air and leads to increased greenhouse gas emissions. Subsequently, the burning of fossil fuels to produce energy is now more costly than many renewable energy sources, including solar photovoltaic (PV) systems. Environmental stewardship, along with the need to maintain revenue generation, has led UMUT’s efforts to achieve energy self-determinism employing PV and exploring other technology. In the past, the tribe completed a 1 megawatt PV project near Towaoc, Colorado, which serves as a case study on the tribe’s energy goals: a future where renewables will dominate their energy landscape. This paper explores UMUT’s past and on-going efforts toward energy independence and how it relates to the broader landscape of Native American energy sovereignty.

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The recent discovery of bright, room-temperature, single photon emitters in GaN leads to an appealing alternative to diamond best single photon emitters given the widespread use and technological maturity of III-nitrides for optoelectronics (e.g. blue LEDs, lasers) and high-speed, high-power electronics. This discovery opens the door to on-chip and on-demand single photon sources integrated with detectors and electronics. Currently, little is known about the underlying defect structure nor is there a sense of how such an emitter might be controllably created. A detailed understanding of the origin of the SPEs in GaN and a path to deterministically introduce them is required. In this project, we develop new experimental capabilities to then investigate single photon emission from GaN nanowires and both GAN and AlN wafers. We ion implant our wafers with the ion implanted with our focused ion beam nanoimplantation capabilities at Sandia, to go beyond typical broad beam implantation and create single photon emitting defects with nanometer precision. We've created light emitting sources using Li⁺ and He⁺, but single photon emission has yet to be demonstrated. In parallel, we calculate the energy levels of defects and transition metal substitutions in GaN to gain a better understanding of the sources of single photon emission in GaN and AlN. The combined experimental and theoretical capabilities developed throughout this project will enable further investigation into the origins of single photon emission from defects in GaN, AlN, and other wide bandgap semiconductors.

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The wide variety of inverter control settings for solar photovoltaics (PV) causes the accurate knowledge of these settings to be difficult to obtain in practice. This paper addresses the problem of determining inverter reactive power control settings from net load advanced metering infrastructure (AMI) data. The estimation is first cast as fitting parameterized control curves. We argue for an intuitive and practical approach to preprocess the AMI data, which exposes the setting to be extracted. We then develop a more general approach with a data-driven reactive power disaggregation algorithm, reframing the problem as a maximum likelihood estimation for the native load reactive power. These methods form the first approach for reconstructing reactive power control settings of solar PV inverters from net load data. The constrained curve fitting algorithm is tested on 701 loads with behind-the-meter (BTM) PV systems with identical control settings. The settings are accurately reconstructed with mean absolute percentage errors between 0.425% and 2.870%. The disaggregation-based approach is then tested on 451 loads with variable BTM PV control settings. Different configurations of this algorithm reconstruct the PV inverter reactive power timeseries with root mean squared errors between 0.173 and 0.198 kVAR.

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Complex challenges across Sandia National Laboratories' (SNL) mission areas underscore the need for systems level thinking, resulting in a better understanding of the organizational work systems and environments in which our hardware and software will be used. SNL researchers have successfully used Activity Theory (AT) as a framework to clarify work systems, informing product design, delivery, acceptance, and use. To increase familiarity with AT, a working group assembled to select key resources on the topic and generate an annotated bibliography. The resources in this bibliography are arranged in six categories: 1) An introduction to AT; 2) Advanced readings in AT; 3) AT and human computer interaction (HCI); 4) Methodological resources for practitioners; 5) Case studies; and 6) Related frameworks that have been used to study work systems. This annotated bibliography is expected to improve the reader's understanding of AT and enable more efficient and effective application of it.

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Microgrids require reliable communication systems for equipment control, power delivery optimization, and operational visibility. To maintain secure communications, Microgrid Operational Technology (OT) networks must be defensible and cyber-resilient. The communication network must be carefully architected with appropriate cyber-hardening technologies to provide security defenders the data, analytics, and response capabilities to quickly mitigate malicious and accidental cyberattacks. In this work, we outline several best practices and technologies that can support microgrid operations (e.g., intrusion detection and monitoring systems, response tools, etc.). Then we apply these recommendations to the New Jersey TRANSITGRID use case to demonstrate how they would be deployed in practice.

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A collection of x-ray computed tomography scans of candy.

Members of the Workforce (MOW) who are exposed to noise levels above 140 dBC, regardless of hearing protection worn, are required to be enrolled into the SNL Hearing Conservation Program which includes audiometric testing, online training (HCP100) and wearing hearing protection. Based on the area impact noise sample results, the attenuation provided by the MFCP was protective for mitigating noise to levels below the ACGIH TLV of 140 dBC. The results also validated the scaled distance equation in an open-air environment as the results at K635 (864 feet) were below 140 dBC.

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The goal of the project was to protect US critical infrastructure and improve energy security through technical analysis of the risk landscape presented by the anticipated massive deployment of interoperable EV chargers.

This document presents the facility-recommended characterization of the neutron, prompt gamma ray, and delayed gamma ray radiation fields in the University of Texas at Austin Nuclear Engineering Teaching Laboratory (NETL) TRIGA reactor for the beam port 1/5 free-field environment at the 128-inch location adjacent to the core centerline. The designation for this environment is NETL-FF-BP1/5-128-cca. The neutron, prompt gamma ray, and delayed gamma ray energy spectra, uncertainties, and covariance matrices are presented as well as radial and axial neutron and gamma ray fluence profiles within the experiment area of the cavity. Recommended constants are given to facilitate the conversion of various dosimetry readings into radiation metrics desired by experimenters. Representative pulse operations are presented with conversion examples.

This manual describes the installation and use of the Xyce™ XDM Netlist Translator. XDM simplifies the translation of netlists generated by commercial circuit simulator tools into Xyce-compatible netlists. XDM currently supports translation from PSpice, HSPICE, and Spectre netlists into Xyce™ netlists.

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Underground explosions can produce infrasound in the atmosphere, and the wavefield characteristics are often governed by the ground surface motions. Finite-difference methods are popular for infrasound simulation as their generality and robustness allow for complex atmospheric structures and surface topography. A simple point-source approximation is often used because infrasound wavelengths tend to be large relative to the source dimensions. However, this assumption may not be able to capture the complexity of explosion-induced ground motions if the surface area is not compact, and appropriate source models must be incorporated into the finite-difference simulations for accurate infrasound prediction. In this study, we develop a point source representation of the complex ground motions for infrasound sources. Instead of a single point source, we use a series of point sources distributed over the source area. These distributed point sources can be equivalent to air volume changes produced by the ground motions in the atmosphere. We apply the distributed point-source method to a series of buried chemical explosions conducted during the Source Physics Experiment Phase I. Epicentral ground-motion measurements during the experiments provide a way to calculate accurate distributed point sources. We validate and evaluate the accuracy of distributed point source approach for infrasound simulations by direct comparison with acoustic observations in the field experiment.

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Geologic Disposal Safety Assessment Framework is a state-of-the-art simulation software toolkit for probabilistic post-closure performance assessment of systems for deep geologic disposal of nuclear waste developed by the United States Department of Energy. This paper presents a generic reference case and shows how it is being used to develop and demonstrate performance assessment methods within the Geologic Disposal Safety Assessment Framework that mitigate some of the challenges posed by high uncertainty and limited computational resources. Variance-based global sensitivity analysis is applied to assess the effects of spatial heterogeneity using graph-based summary measures for scalar and time-varying quantities of interest. Behavior of the system with respect to spatial heterogeneity is further investigated using ratios of water fluxes. This analysis shows that spatial heterogeneity is a dominant uncertainty in predictions of repository performance which can be identified in global sensitivity analysis using proxy variables derived from graph descriptions of discrete fracture networks. New quantities of interest defined using water fluxes proved useful for better understanding overall system behavior.

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Photovoltaic (PV) performance is affected by reversible and irreversible losses. These can typically be mitigated through responsive and proactive operations and maintenance (O&M) activities. However, to generate profit, the cost of O&M must be lower than the value of the recovered electricity. This value depends both on the amount of recovered energy and on the electricity prices, which can vary significantly over time in spot markets. The present work investigates the impact of the electricity price variability on the PV profitability and on the related O&M activities in Italy, Portugal, and Spain. It is found that the PV revenues varied by 1.6 × to 1.8 × within the investigated countries in the last 5 years. Moreover, forecasts predict higher average prices in the current decade compared to the previous one. These will increase the future PV revenues by up to 60% by 2030 compared to their 2015–2020 mean values. These higher revenues will make more funds available for better maintenance and for higher quality components, potentially leading to even higher energy yield and profits. Linearly growing or constant price assumptions cannot fully reproduce these expected price trends. Furthermore, significant price fluctuations can lead to unexpected scenarios and alter the predictions.

One detonation test was monitored for impulse noise at Thunder Range on November 6, 2020. The TNT equivalency for this shot was 100 lbs. Ground zero for this test was located at an open area of Range 7. The Armag, where MOW were remotely located, was just south of the east end of the TR shock tube The purpose of this sampling event was to characterize the noise attenuation provided by the Armag which will be used as the primary firing location in a future test series. To determine attenuation provided by the Armag, one sound level monitor was placed inside and a second monitor was placed outside the hardened structure at the same distance from ground zero. The Armag was located 1300 feet from ground zero. Essential personnel performing these tests were remotely located inside the Armag and wore hearing protection with a minimum NRR of 23. Members of the Workforce (MOW) who are exposed to noise levels above 140 dBC, regardless of hearing protection worn, are required to be enrolled into the SNL Hearing Conservation Program which includes audiometric testing, online training (HCP100) and wearing hearing protection.

This document is a reference guide to the Xyce™ Parallel Electronic Simulator, and is a companion document to the Xyce™ Users' Guide. The focus of this document is (to the extent possible) exhaustively list device parameters, solver options, parser options, and other usage details of Xyce™. This document is not intended to be a tutorial. Users who are new to circuit simulation are better served by the Xyce™ Users' Guide.

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We present a proof-of-concept demonstration of a narrow linewidth $^{87}$Rb magneto-optical trap (MOT) operating on the narrow linewidth $5S_{1/2}$ → $6P_{3/2}$ transition at 420 nm. We stabilized the absolute frequency of the 420 nm laser to an atomic transition in $^{87}$Rb and demonstrate a MOT using 420 nm light driving the $5S_{1/2}$, $F = 2$ → $6P_{3/2}, F' = 3$ transition. We then use tome-of-flight measurements to characterize the 420 nm MOT temperature, observing a minimum temperature of about $T^{(420)}_{horizontal}$ = 150μK and $T^{(420)}_{vertical}$ = 250μK before the opportunity to perform significant characterization and optimization. Although this temperature is significantly higher then the expected 420 nm Doppler cooling limit ($T_D^{(420)}$ ≈ 34 μK), these are already approaching the Doppler limit of a standard 780 nm MOT ($T_D^{(780)}$ ≈ 146 μK). We believe that with further optimization the Doppler cooling limit of ≈ 34 μK can be achieved. This initial result answers our key research question and demonstrates the viability of applying narrow linewidth laser cooling as a robust technique for future fieldable quantum sensors.

The Sandia National Laboratories site sustainability plan and its associated DOE Sustainability Dashboard data entries encompass Sandia National Laboratories contributions toward meeting the DOE sustainability goals. This site sustainability plan fulfills the contractual requirement for National Technology & Engineering Solutions of Sandia, LLC, the management and operating contractor for Sandia National Laboratories, to deliver an annual sustainability plan to the DOE National Nuclear Security Administration Sandia Field Office.

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Niobium doped lead-tin-zirconate-titanate ceramics near the PZT 95/5 orthorhombic AFE – rhombohedral FE morphotropic phase boundary Pb1-0.5y(Zr0.865-xTixSn0.135)1-yNbyO3 were prepared according to a 22+1 factorial design with x = 0.05, 0.07 and y = 0.0155, 0.0195. The ceramics were prepared by a traditional solid-state synthesis route and sintered to near full density at 1250°C for 6 h. All compositions were ∼98% dense with no detectable secondary phases by X-ray diffraction. The ceramics exhibited equiaxed grains with intergranular porosity, and grain size was ∼5 µm, decreasing with niobium substitution. Compositions exhibited remnant polarization values of ∼32 µC/cm2, increasing with Ti substitution. Depolarization by the hydrostatic pressure induced FE-AFE phase transition was drastically affected by variation of the Ti and Nb substitution, increasing at a rate of 113 MPa /1% Ti and 21 MPa/1% Nb. Total depolarization output was insensitive to the change in Ti and Nb substitution, ∼32.8 µC/cm2 for the PSZT ceramics. The R3c-R3m and R3m-Pm3m phase transition temperatures on heating ranged from 90 to 105°C and 183 to 191°C, respectively. Ti substitution stabilized the R3c and R3m phases to higher temperatures, while Nb substitution stabilized the Pm3m phase to lower temperatures. Thermal hysteresis of the phase transitions was also observed in the ceramics, with transition temperature on cooling being as much as 10°C lower.

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A collection of x-ray computed tomography scans of mineral specimens from private collections.

Cyber security has been difficult to quantify from the perspective of defenders. The effort to develop a cyber-attack with some ability, function, or consequence has not been rigorously investigated in Operational Technologies. This specification defines a testing structure that allows conformal and repeatable cyber testing on equipment. The purpose of the ETE is to provide data necessary to analyze and reconstruct cyber-attack timelines, effects, and observables for training and development of Cyber Security Operation Centers. Standardizing the manner in which cyber security on equipment is investigated will allow a greater understanding of the progression of cyber attacks and potential mitigation and detection strategies in a scientifically rigorous fashion.

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In this paper, we design efficient quadrature rules for finite element (FE) discretizations of nonlocal diffusion problems with compactly supported kernel functions. Two of the main challenges in nonlocal modeling and simulations are the prohibitive computational cost and the nontrivial implementation of discretization schemes, especially in three-dimensional settings. In this work, we circumvent both challenges by introducing a parametrized mollifying function that improves the regularity of the integrand, utilizing an adaptive integration technique, and exploiting parallelization. We first show that the “mollified” solution converges to the exact one as the mollifying parameter vanishes, then we illustrate the consistency and accuracy of the proposed method on several two- and three-dimensional test cases. Furthermore, we demonstrate the good scaling properties of the parallel implementation of the adaptive algorithm and we compare the proposed method with recently developed techniques for efficient FE assembly.

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This manual describes the use of the Xyce™ Parallel Electronic Simulator. Xyce™ has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: (1) Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). This includes support for most popular parallel and serial computers. (2) A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows one to develop new types of analysis without requiring the implementation of analysis-specific device models. (3) Device models that are specifically tailored to meet Sandia's needs, including some radiation-aware devices (for Sandia users only). (4) Object-oriented code design and implementation using modern coding practices. Xyce™ is a parallel code in the most general sense of the phrase—a message passing parallel implementation—which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel eficiency is achieved as the number of processors grows.

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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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