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At least 1,117 records · Page 62

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DOE OSTI2024

Toadstool Deep Learning Framework

SAND2025-11741O Toadstool is a deep learning framework and support library that provides PyTorch boiler plate training and testing loops. This enables the user to remember parts and customize a callback interface. Toadstool also provides useful callbacks and other methods for deep learning experimentation. The framework also implements publicly available temperature and calibration methods, model initialization methods, learning rate schedulers, and model evaluation methods. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Heidbrink, Scott↗

DOE OSTI2024

Wind Turbine Airfoil Design Tools

SAND2025-11738O Wind Turbine Airfoil Design Tools is a software tool that connects existing open-source airfoil analysis tools with optimization software to produce modern airfoil design for wind turbine applications. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Maniaci, David↗

DOE OSTI2024

SetEnvironment

SAND2025-11727O SetEnvironment software is a utility library module that uses ConfigParserEnhanced, also a library module, to read specifically formatted .ini files for setting the user's environment. It creates a consistent environment with an expected set of variables and module loads, which is important for testing. Environment variable operations include set, append, prepend, unset, remove, and others and uses the Python os.environ methods. The module operations are performed with a wrapper. Systems using the Lmod package can generate a module function, which can also perform module operations specified in the text file. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

McLendon III, William↗

DOE OSTI2024

Metric DBSCAN

SAND2025-11725O Metric DBSCAN is an implementation of the popular DBSCAN clustering algorithm that works in general metric spaces. DBSCAN is a clustering algorithm, a fundamental building block in machine learning. It takes a set of objects and, given some notion of distance, identifies coherent groups of objects. With Metric DBSCAN, users can provide an arbitrary function to compute distance. Nearly all existing implementations of DBSCAN restrict distance to one of a few formulations. Metric DBScan accomplishes this cleanly and efficiently. The Python source code is on Github. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Dalbey, Keith↗

DOE OSTI2024

Conditional multi-step attribution for climate forcings

SAND2025-11608O Conditional multi-step attribution for climate forcings and its associated dataset present a framework for attributing a climate impacts, such as stratospheric warming or surface cooling, to a specific magnitude of climate forcing, such as stratospheric aerosol injection. The objective is to improve on existing methods that struggle to attribute highly noisy climate signals. This has potential broader use in climate security applications to identify and understand geoengineering and climate tipping point effects. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Swiler, Laura↗

DOE OSTI2024

PVCollada schema

SAND2025-11606O xml schema for PV uses Collada 1.4 schema to provide tag names and structures to allow PV software to exchange Collada files with PV-specific data. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Crosby, Sean↗

DOE OSTI2024

GeoCricket

SAND2025-12229O Geospatial Critical Infrastructure and Census Data Stockpile Tool (GeoCricket) is a set of functions that collect critical infrastructure and census data for use in the Resilient Node Cluster Analysis Tool (ReNCAT) and Quantum Geographic Information System Social Burden Calculator. It can also act to inform other place-based work. The code queries public-facing Representational State Transfer (REST) servers to collect geospatial data related to a specific area. It then exports that data as standard geographic information system file types or as a .csv file. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Haines, John↗

DOE OSTI2024

Probabilistic Grid Reliability Analysis with Energy Storage Systems

SAND2025-12025O The Probabilistic Grid Reliability Analysis with Energy Storage Systems (ProGRESS) software tool is an open-source tool for assessing the resource adequacy of the evolving electric power grid integrated with energy storage systems (ESS). This tool uses a simulation engine to create diverse scenarios that test the limits of the modern power grid consisting of a high-volume ESS and variable energy resources (VER). Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Nguyen, Tu↗

DOE OSTI2024

CHMMPY: A python package for constrained Hidden Markov Models

SAND2025-11909O chmmpy software analyzes multivariate timeseries data to detect patterns. It uses a Hidden Markov Model (HMM) and application-specific constraints that reflect known relationships among hidden states to accomplish this. The chmmpy software provides a generic framework for expressing application-specific constraints and supporting constrained HMM inference using optimization solvers. chmmpy is available on GitHub. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Hart, William↗

DOE OSTI2024

REDLY

SAND2025-11838O REDLY provides a framework for designing, training, and validating physics-informed neural networks for power system applications. It trains surrogates for Alternating Current Power Flow prediction and general economic dispatch problems, such as Alternating Current Optimal Power Flow and Direct Current Power Flow. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Blakely, Logan↗

DOE OSTI2024

Tight Practical Bounds for Subgraph Densities in Ego-centric Networks

SAND2025-11782O Tight Practical Bounds for Subgraph Densities in Ego-centric Networks is a software tool for calculating the “subgraph spread ratio” for social network analysis. This value is useful in network analysis for determining the amount of exogenous and endogenous pressure on a graph. It can distinguish between networks coming from different sources, e.g. distinguishing a graph of Facebook data versus a graph of Wikipedia data. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Mattes, Connor↗

DOE OSTI2024

ARCADE (Advanced Reactor Cyber Analysis and Development Environment)

SAND2025-11780O ARCADE (Advanced Reactor Cyber Analysis and Development Environment) software performs cybersecurity experiments on Defensive Cyber Security Architectures (DCSA) for Distributed Control Systems (DCSs). The application is integrated into a cohesive environment that performs cyber risk analyses and reduces costs. ARCADE can investigate the entire cyber-attack surface of a DCS from the physics of control, down to the firmware of individual components with automated efficiency. ARCADE has five major functional components: the Data Broker system, the virtualization environment, the cyber-attack simulator, the cyber-physical analysis system, and the physics simulator. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Valme, Romuald↗

DOE OSTI2024

TorchDendrite

SAND2025-11595O The TorchDendrite library implements hardware-informed dendrites using PyTorch and SNNTorch as backends. It allows the integration of dendrite-inspired neurons into machine learning networks built with both SNNTorch and PyTorch. TorchDendrite will be available on Github. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Chance, Frances↗

DOE OSTI2024

LAPIS: Linear Algebra Performance for Intermediate Subprograms

SAND2025-11594O LAPIS (Linear Algebra Performance for Intermediate Subprograms) is a compiler infrastructure for linear algebra that targets both high productivity and performance portability. It is based on the open-source MLIR package from the LLVM project. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Kelley, Brian↗

DOE OSTI2023

Development and evaluation of a skeletal mechanism for EHN additized gasoline mixtures in large Eddy simulations of HCCI combustion

Advanced Low Temperature Combustion modes, such as the Sandia proposed Additive-Mixing Fuel Injection (AMFI), can unlock significant potential to boost fuel conversion efficiency and ultimately improve the energy conversion of internal combustion engines. This is a novel improved combustion process that is enabled by supplying small (<5%) variable amounts of autoignition improver to the fuel to enhance the engine operation and control. Common, diesel-fuel ignition-quality enhancing additive, 2-ethylexyl nitrate (EHN), is doped into gasoline to enable Sandia LTGC + AMFI combustion. This manuscript focuses on the development of a reduced sub-mechanism for EHN chemical kinetics at engine relevant conditions that is implemented into a skeletal mechanism for chemical kinetic studies of gasoline surrogate fuels. The mechanism validation utilized zero-dimensional numerical simulations and comparison to shock tube ignition-delay data of pure and EHN-doped n-heptane. Additional validation is presented with Homogeneous Charge Compression-Ignition (HCCI) engine data of pure and EHN-doped research-grade E10 gasoline. Then, the mechanism was deployed in a 3-D computational fluid dynamics (CFD) using Large Eddy Simulations (LES) to model the HCCI engine experiments of 0.4% vol EHN additized E10 gasoline at several equivalence ratios. Simulations showed a very good performance of the mechanism, and the model accurately reproduced (a) the ignition point, (b) combustion phasing, (c) combustion duration, and (d) the peak of the heat release rates of the engine experiments. The results show that EHN promotes Low-Temperature Heat Release, ultimately driving the gasoline to autoignite at thermodynamic conditions where the fuel would not otherwise ignite. Overall, this work demonstrates a viable reduced chemical-kinetic mechanism for EHN and shows that it can be combined with a skeletal gasoline mechanism for CFD-LES analysis of well-mixed LTGC that matches well with experimental results. The CFD-LES analysis also shows the spatial distribution of EHN-fuel interactions that control the autoignition throughout the combustion chamber.

Guleria, Gaurav↗

DOE OSTI2024

Modeling a Hypothetical Fusion Blanket Design Using MELCOR-TMAP

MELCOR (not an acronym) is a nuclear safety code developed by Sandia National Laboratories for the Nuclear Regulatory Commission. Idaho National Laboratory collaborates with Sandia to maintain and develop a version of MELCOR specifically for fusion device applications. Most recently, the tritium migration analysis program (TMAP) has been incorporated into MELCOR for fusion, in a version called MELCOR-TMAP. We show the results applying MELCOR-TMAP to model steady-state inventory and tritium retention in a liquid immersion blanket design for a hypothetical fusion device under steady-state operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Preliminary Design of Critical Experiments Involving Commercially Available B 4 C Neutron Absorber Plates with Low-Enriched UO 2 Fuel

The International Criticality Safety Benchmark Evaluation Project (ICSBEP) is an initiative to provide high-quality benchmark data in a standardized format for criticality safety analysts to use to validate calculational tools and nuclear data. In the last released 2022 version, the ICSBEP handbook contains over 5,000 critical experiment descriptions, results, and associated models. This paper describes the critical configurations proposed and calculations performed as part of the conceptual design phase of Integral Experiment Request (IER) 554 (IER-554). The goal of IER-554 is to add to the benchmark experiments available to the criticality safety community by designing critical experiments that can analyze how adding commercially available Boralcan plates to an assembly of low-enriched UO2 fuel rods affects the effective neutron multiplication factor (k eff ). Boralcan, a neutron absorber product developed by Rio Tinto, is made of B4C in an Al 1100 matrix and is commonly used for criticality suppression in fuel storage pools. In the current version of the ICSBEP handbook, only a few dated critical experiments involve B4C materials, and none involve Boralcan in a thin plate shape. The experiments designed as part of IER-554 are intended to be performed at the Sandia Pulsed Reactor Facility/Critical Experiments (SPRF/CX) apparatus at Sandia National Laboratories. SPRF/CX is a well-characterized assembly considered trustworthy by the benchmarking community because of the numerous high-quality evaluations with very low experimental uncertainties included in the ICSBEP handbook. Figure 1 illustrates the assembly for a particular configuration from LCT-078, one of the published benchmarks in the ICSBEP handbook. The experiments will be moderated and reflected by light water at ambient atmospheric pressure. Before the plates are inserted in the critical assembly, they will be characterized with x-ray computed tomography (XCT) to identify the sizes and distribution of the B 4 C powder particles inside the plates. The preliminary design calculations were performed with SCALE 6.3.0 using the KENO V.a sequence for the criticality calculations, the CE-TSUNAMI-3D sequence for the sensitivity and uncertainty studies, and the ENDF/B-VII.1 Continuous Energy cross section library. All the calculation results presented have 10 pcm statistical uncertainties. A set of critical experiments with Boralcan plates could increase the confidence of the criticality safety community in its modeling methods when using this type of neutron absorber material. Experiments would also help validate k eff calculations, and the industry could use these validations to change the B loading credit limits from the US Nuclear Regulatory Commission standard review plan for dry cask storage of spent nuclear fuel. This paper summarizes only part of the analysis documented in the preliminary design report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Recovery and Calibration of Legacy Underground Nuclear Test Seismic Data from the Leo Brady Seismic Network

The Leo Brady Seismic Network (LBSN, originally the Sandia Seismic Network) was established in 1960 by Sandia National Laboratories to monitor underground nuclear tests (UGTs) at the Nevada National Security Site (NNSS, formerly named the Nevada Test Site). The LBSN has been in various configurations throughout its existence, but it has generally been comprised of four to six stations at regional distances (~150–400 km) from the NNSS with approximately evenly spaced azimuthal coverage. Between 1962 and the end of nuclear testing in 1992, the LBSN—and a sister network operated by Lawrence Livermore National Laboratories—was the most comprehensive United States source of regional seismic data of UGTs. Approximately 75% of all UGTs performed by the United States occurred in the predigital era. At that time, LBSN data were transmitted as frequency-modulated (FM) audio over telephone lines to a central location and recorded as analog waveforms on high-fidelity magnetic audio tapes. These tapes have been in dry temperature-stable storage for decades and contain the sole record of this irreplaceable data; full waveforms of LBSN-recorded UGTs from this era were not routinely digitized or otherwise published. We have developed a process to recover and calibrate data from these tapes. First, we play back and digitize the tapes as audio. Next, we demodulate the FM “audio” into individual waveforms. We then estimate the various instrument constants through careful measurement of “weight-lift” tests performed prior to each UGT on each instrument. Finally, these coefficients allow us to scale and shape the derived instrument response of the seismographs and compute poles and zeros. Finally, the result of this process is a digital record of the recorded seismic ground motion in a modern data format, stored in a searchable database. To date, we have digitized tapes from 592 UGTs.

58 GEOSCIENCES↗