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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Loop series expansions for tensor networks

Belief propagation (BP) can be a useful tool to approximately contract a tensor network, provided that the contributions from any closed loops in the network are sufficiently weak. In this article, we describe how a loop series expansion can be applied to systematically improve the accuracy of a BP approximation to a tensor network contraction, in principle converging arbitrarily close to the exact result. More generally, our result provides a framework for expanding a tensor network as a sum of component networks in a hierarchy of increasing complexity. We benchmark this proposal for the contraction of infinite projected entangled pair states, either representing the ground state of an Affleck-Kennedy-Lieb-Tasaki (AKLT) model or with randomly defined tensors, where it is shown to improve in accuracy over standard BP by several orders of magnitude while incurring only a minor increase in computational cost. These results indicate that the proposed series expansions could be a useful tool to accurately evaluate tensor networks in cases that otherwise exceed the limits of established contraction routines.

Evenbly, Glen [AWS Center for Quantum Computing, P↗
DOE OSTI2026

Ultrasonic Resonance Techniques for Materials Research

Mechanical resonances are directly related to the physical behavior of a system at the bulk and microscopic levels. In materials science, resonant ultrasound spectroscopy (RUS) has long been a preferred nondestructive method to study mechanical resonances of solids and precisely measure quantitative material properties, namely elasticity. In recent years, advances in computational power and hardware have enabled RUS to be relevant for an increasing range of applications, such as advanced manufacturing. An extension of this technique, nonlinear RUS (NRUS), has been demonstrated to provide unmatched sensitivity to early-stage damage. NRUS was originally developed to probe geologic materials but has become a vital tool in nondestructive evaluation and materials research, offering a powerful means of quantifying and characterizing microstructural nonlinearity in a broad range of materials. This review summarizes recent developments and growth opportunities in RUS and NRUS techniques, modeling, and applications across a wide range of material systems including metals, composites, geomaterials, and explosives.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Development of the Contamination Distribution Centered Toxics Mobility Vulnerability Index in the Beaumont–Port Arthur Region of Texas

This study advances the Toxics Mobility Inventory (TMI) and the Toxics Mobility Vulnerability Index (TMVI) to develop a new tool to assess the movement of hazardous substances and their implications for vulnerable communities. It emphasizes the need to include contamination distribution variables in such indices to address disproportionate impacts and more accurately reflect vulnerability. The study uses the TMI framework and TMVI methodology in the Beaumont–Port Arthur region of Texas, also integrating contamination distribution considerations into the analysis to develop a new framework and process. The new Contamination Distribution Centered Toxics Mobility Vulnerability Index (CDC-TMVI) consolidates climate change and topography variables into a broader built environment vulnerability category while introducing a contamination sources category. Using ArcGIS Pro and ToxPi tools, the study evaluates 27 geospatial variables across four categories: built environment vulnerability, social vulnerability, health outcomes, and contamination sources. The results indicate significant contributions from contamination and social vulnerability variables, highlighting areas with higher risks of flooding and air pollution. This article advocates for future research and policy efforts to enhance the integration of contamination sources and their spatial distributions into toxics mobility assessments to better protect vulnerable populations. Furthermore, the unique methodology and findings serve as a basis for developing targeted measures and strategic planning to improve environmental health.

contamination↗
DOE OSTI2025

Microwave-Assisted Activation of Mo/HZSM5 in Methane Dehydroaromatization

Natural gas flaring is a significant challenge for oil and gas producers. One viable option to mitigate flaring is the conversion of natural gas into valuable chemicals. Applying microwave energy to heterogenous catalyst materials offers advantages in terms of higher rates and product selectivities in comparison to traditional thermal systems which can be designed for on-demand chemical production in modular reactor systems. Methane dehydroaromatization (MDHA) produces transportable, liquid aromatic products directly from natural gas, which is ideal for remote production but is hindered by low thermodynamic yields and rapid deactivation. The stability and performance of the Mo/ZSM5 catalyst is often determined by the state and nature of Mo in the catalyst, which in turn is dictated by the temperature and gaseous environment during catalyst activation. In this study, the Mo/HZSM5 catalyst was activated under three different heating modes (thermal, microwave E-field, and microwave H-field) and four different gas environments (CO, He, CH4+H2, and H2). All the activated catalysts were characterized using different tools and performance evaluated in MDHA.

methane dehydroaromatization↗
DOE OSTI2025

Building Datasets and Training Methods for ML Based Magnet Quench Detection

Detecting quenches in superconducting (SC) magnets during training is a challenging process that involves capturing physical events that occur at different frequencies and appear as various signal features. These events may be correlated across instrumentation type, thermal cycle, and ramp. These events together build a more complete picture of continuous processes occurring in the magnet, and may allow us to flag potential precursors for quench detection. We present our work on building an automatic machine learning (ML) based quench detection system. We build upon our existing work on unsupervised auto-encoders for acoustic sensors and quench antenna (QA) by first establishing a supervised ML training pipeline. We show the results of an event tagging, analysis, and simulation framework on our QA and acoustic data which are used concurrently to build a training dataset for a supervised implementation. We then show how this supervised training can be used as a prior in a semi-supervised framework and compare this to the unsupervised neural network auto-encoder performance.This allows us to have a more concrete understanding of the performance of our algorithms relative to physical events occurring in the magnet, and also provides a baseline software tool to generically evaluate our quench prediction autoencoders under completely unsupervised, supervised, and semi-supervised training conditions.

Khan, Maira [Fermilab]↗
DOE OSTI2025

Assessment of Heavy-Duty Fueling Methods and Components-Modeling and Analysis

The goal of the Assessment of Heavy-Duty Fueling Methods and Components project was to comprehensively assess heavy-duty (HD) fuel cell electric vehicle fueling protocols and their effects on techno-economic assessments (TEA) and total cost of ownership (TCO). The project leveraged and built upon ongoing international HD fueling protocols and fueling component development activities to deliver component performance assessments, modeling tools and methods evaluations, TEA of industry-selected protocol structures, and experimental validations of the strategies at the station scale. The effects of the protocols on the fueling times, station costs, and TCO were explored. Fueling time, which was influenced by temperature and protocol selection, had a large impact on the station cost due to component sizing and satisfying hourly demand. As the fleet size increased, the station cost was shown to exponentially decrease by achieving economies of scale. Technology year and fuel economy were the largest contributors to the TCO; however, the choice of fueling protocol had a minor impact on the TCO.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

OptiBench: An Optimization Benchmark Tool for Renewable Energy Problems

We propose a benchmark framework and visualization tool, OptiBench, for analyzing the performance of state-of-the-art optimization solvers across a variety of optimization problems in renewable energy research. Our framework is designed from the ground up in the Julia programming language and enables analysis at scale on high performance computing (HPC) systems. Our visualization tool allows effortless evaluation of optimization solver performance, robustness, and accuracy through intuitive plots, e.g., performance profiles, heat maps, and distribution plots. We have tested three benchmark suites relevant to the modeling of renewable energy systems, viz., CUTEst, PGLib-OPF, and WaterTAP water treatment optimization problems. We illustrate benchmarking of CUTEst using OptiBench on the National Laboratory of the Rockies's (NLR) HPC Kestrel. Our findings indicate that MA57 HSL linear solver demonstrated the best overall performance for an experimental IPOPT implementation. Our work is ongoing and we intend to add support for more optimization solvers and benchmark test suites in the future.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Assessment of Heavy-Duty Fueling Methods and Components

Chevron, NLR, ANL, and NextEnergy partnered in the development of a comprehensive assessment of heavy-duty (HD) fuel cell electric vehicle fueling protocols. The project leveraged and built upon existing international heavy-duty (HD) fueling protocols and fueling component development activities to deliver component performance assessments, modeling tools and methods evaluations, techno-economic assessments of industry-selected protocol structures and experimental validations of the strategies performed at NLR's HD hydrogen fueling station.

08 HYDROGEN↗
DOE OSTI2025

A double copy from twisted (co)homology at genus g

We study a family of generalized hypergeometric integrals defined on punctured Riemann surfaces of genus g. These integrals are closely related to g-loop string amplitudes in chiral splitting, where one leaves the loop-momenta, moduli and all but one puncture un-integrated. We study the twisted homology groups associated to these integrals, and determine their intersection numbers. We make use of these homology intersection numbers to write a double-copy formula for the "complex" version of these integrals -- their closed-string analogues. To verify our findings, we develop numerical tools for the evaluation of the integrals in this work. This includes the recently introduced Enriquez kernels -- integration kernels for higher-genus polylogarithms.

Pokraka, Andrejz [Brown University; Amsterdam Univ↗
DOE OSTI2025

Wire Arc Additive Manufacturing of Multi-material Parts Using H-13 Tool Steel

H-13 tools steel’s relative hardness, resistance to thermal fatigue, and high tolerance of thermal shock, make it very desirable for use in forging, pressing, casting, and extrusion processes[1]. H-13 is however typically quite expensive when compared to many other steel compositions. It is therefore desirable to encase a lower cost steel composition with H-13. This configuration allows for the benefits of H-13 tooling to be realized, at a considerably reduced cost. To demonstrate the viability of this concept, a casting tool was fabricated using a Wire Arc Additive Manufacturing (WAAM) process. Initial materials testing was conducted on a multi-material wall which consisted of one section of H-13 tool steel, and one section of 410NiNmo. These tests included scanning electron microscopy, energy dispersive X-ray spectroscopy, and hardness testing. This testing generated favorable results and subsequently a casting tool was fabricated for evaluation. Utilization of a Multi-Material WAAM process to fabricate large tooling in this manner could yield significant improvements in material cost, manufacturing agility, and supply chain complexity.

Lambert, Nathan [ORNL] (ORCID:0009000324134206)↗
DOE OSTI2025

Internship Presentation: Integrating Safety and Cybersecurity: Security-by-Design with SOWT Analysis for Reactor Testing

This study covers leveraging reactor testing facilities that are primarily designed with a focus on safety to enhance cybersecurity testing. By incorporating reactor security-by-design with reactor safety-by-design principles and adopting defense-in-depth strategies that emphasize both safety and security, the research evaluates applicable cyber tools, models, and solutions. This includes simulating specific cyber-attack scenarios using reactor simulators and performing SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis to improve the cybersecurity of reactor systems.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2025

Microreactor Optimization Using Simulation And Economics (mouse)

Microreactor Optimization Using Simulation and Economics (MOUSE) is a tool that integrates both nuclear microreactor design and reactor economics to provide comprehensive evaluations and optimizations. This tool enables stakeholders to explore the interplay between technical and economic variables, guiding them towards effective and competitive microreactor solutions. For the reactor core simulations, MOUSE leverages the OpenMC Monte Carlo Particle Transport Code to perform detailed core simulations for various microreactor designs. The included OpenMC models are 2D core designs of a Liquid Metal Thermal Microreactor (LMTR), a Gas-Cooled TRISO-Fueled Microreactor (GCMR), and a Heat Pipe Microreactor. Beyond core design, MOUSE includes simplified calculations for: - Calculating the masses of heat exchangers within the system. - Mechanical power of pumps. - Estimating the area occupied by various buildings within the nuclear plant. For the economic analysis, MOUSE provides detailed bottom-up cost estimates, encompassing a wide range of costs including preconstruction costs, direct costs, indirect costs, training costs, financial costs, operation & maintenance (O&M) costs, and fuel costs. These cost estimations are developed using data from the MARVEL project and additional literature sources, enabling the calculation of total capital costs and levelized cost of energy for both first-of-a-kind and nth-of-a-kind microreactors. MOUSE also enables analysis of the cost drivers and competitiveness in the electricity market. MOUSE allows users to modify a wide array of technical and economic parameters to evaluate different scenarios and their impacts. Examples of these parameters include: Fuels, coolants, or reflector materials Enrichment levels Control drum materials and geometry Fuel pin geometry and materials Moderator pin geometry and materials Reactor core and reflector dimensions Packing factor for the TRISO particles Nuclear reactor power and reactor burnup Number of sensors Shielding thickness Reactor vessel and guard vessel dimensions Operational staff requirements Number of emergency shutdowns Levelization period Interest rate Construction duration Since MOUSE is powered by the WATTS toolkit, it supports optimization studies, parametric analyses, and uncertainty calculations/propagation. The optimization techniques enable users to identify optimal design and economic configurations. The parametric analysis tools allow users to explore the sensitivity of various parameters, while uncertainty propagation helps quantify the impact of uncertainties on overall performance and cost. User Interface and Workflow: Currently, MOUSE is a command-line-based tool. Users can input various reactor design or economic parameters, modify the designs, run simulations, and visualize results through comprehensive data visualization and reporting capabilities. The typical workflow involves setting up the reactor model, defining economic parameters, running simulations, and analyzing the results to make informed decisions. By combining advanced design calculations with detailed economic modeling, MOUSE provides a robust framework for optimizing nuclear microreactor technologies, enhancing their competitiveness, and guiding stakeholders towards innovative and cost-effective solutions.

Hanna, Botros [Idaho National Laboratory (INL), Id↗
DOE OSTI2025

Floating Wind Array Ontology and Modeling Framework

While there are many tools for designing and modeling a single floating turbine, array level design and modeling has much more to consider. Designing floating wind arrays requires a coupled approach considering many variables, from bathymetry to installation and maintenance to failure and risk analysis. With all of these considerations, an array-level modeling tool is needed to quickly evaluate array designs. The Floating Array Model (FAModel) tool developed at the National Renewable Energy Laboratory was created to fill this gap in low-fidelity array modeling. FAModel is a python framework created to streamline holistic low-fidelity floating wind modeling for array-level analysis. FAModel integrates site data and models with a variety of open-source modeling tools developed by NREL, including FLORIS, RAFT, MoorPy, and anchor capacity models. The integration of these tools allows users to quickly and holistically design an array by considering forces, area analysis, visualization, annual energy production, failure modeling, and component costs.

17 WIND ENERGY↗
DOE OSTI2026

CO2 Handling & Electrolyzer Efficiency Scaling Evaluator

CHEESE is an interactive dashboard tool for estimating the performance and material requirements of carbon dioxide electrolysis systems. It helps users evaluate how electrode area, current density, product selectivity, gas flow, cell voltage, and the number of cells in a stack affect system operation. The dashboard provides simple and advanced modes so it can be used for both quick estimates and more detailed engineering analysis. Users can estimate product output, carbon dioxide use, electrical power, electrode area, gas and liquid flow rates, energy efficiency, material cost per test, and the effect of scaling from a single cell to a multi cell stack. It also includes tools for examining carbon balance, equipment durability, component replacement, and changes in performance over time. This is intended to help both academia and industry researchers who are either getting into CO2 electrolysis on lab-scale or are trying to establish a larger footprint. CHEESE presents results through tables, charts, and simplified cell and stack diagrams. It is intended to support research planning, experimental design, comparison of operating conditions, and early stage scale up studies.

Prajapati, Aditya [Lawrence Livermore National Lab↗
DOE OSTI2024

WFOT: A Wave Function Overlap Tool between Single- and Multi-Reference Electronic Structure Methods for Spectroscopy Simulation

We report the development of a novel diagnostic tool, named wave function overlap tool (WFOT), designed to evaluate the overlap between wave functions computed at single-reference [i.e., time-dependent density functional theory or configuration interaction singles (CIS)] and multireference (i.e., CASSCF/CASPT2) electronic structure levels of theory. It relies on truncating the single- and multireference WFs to CIS-like expansions spanning the same configurational space and maximizing the molecular orbital overlap by means of a unitary transformation. To demonstrate the functionality of the tool, we calculate the transient spectrum of acetylacetone by evaluating excited state absorption signals with multireference quality on top of single-reference on-the-fly dynamics simulations. Semiautomatic spectra generation is facilitated by interfacing the tool with the COBRAMM package, which also allows one to use WFOT with several quantum chemistry codes such as Gaussian, NWChem, and OpenMolcas. Finally, other exciting possibilities for the utilization of the code beyond the simulation of transient absorption spectroscopy are eventually discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Applying Automated Detectors for Regional Infrasound Signals to Global Networks: A Case Study Using the 2022 Hunga Tonga Volcanic Eruption

The January 15, 2022 Tonga Hunga volcanic eruption was the largest event to be recorded across the International Monitoring System infrasound network. Signals from the eruption were identified at all 53 operational stations by International Data Centre analysts. This report contains descriptors for signal detection bulletins produced by infrasound researchers at Sandia National Laboratories and Los Alamos National Laboratory. Manual detection bulletins were produced by laboratory staff. Automated detection bulletins were produced using automated infrasound processing tools developed at both laboratories. Initial results are provided to evaluate the utility of extending tools developed for regional infrasound event analysis to global-scale events.

58 GEOSCIENCES↗
DOE OSTI2025

Analyzing the Impact of Future Weather Data on Energy Consumption in Weatherization Assistant

This study supports the mission of the U.S. Department of Energy’s Weatherization Assistance Program (WAP), which aims to increase the energy efficiency of dwellings and reduce their total residential expenditures. Specifically, we examine how projected future climate conditions may affect residential building energy performance by integrating future weather data into the National Energy Audit Tool (NEAT). Since WAP evaluates the cost-effectiveness of retrofit measures over lifespans of up to 30 years, accounting for evolving climate conditions is increasingly important. To reflect future household energy demands, this study replaces historically based Typical Meteorological Year (TMY3) weather inputs with Future Typical Meteorological Year (fTMY) datasets derived from global climate model (GCM) projections. A simulation-based framework was established to enable NEAT analysis under future weather conditions. This workflow involves converting EPW-format weather files into JSON inputs compatible with NEAT and generating degree-hour metrics needed for load calculations. The fTMY dataset used in this study was developed by Oak Ridge National Laboratory through downscaling of six GCMs under different emission scenarios and covers the period from 2020 to 2100. In contrast, the TMY3 dataset is based on historical weather data from 1961 to 1990. Simulations were conducted for benchmark single-family prototype buildings across ASHRAE climate zones 1–7, which cover all regions of the U.S. except the subarctic Zone 8 in northern Alaska, evaluating both heating and cooling loads under TMY3 and fTMY conditions. Four foundation types were tested, while heating systems were standardized, as NEAT does not differentiate thermal energy load by HVAC system type in its load calculations. Results show that fTMY weather input consistently yield lower heating loads and higher cooling loads across most locations, aligning with expected climate warming trends. Notably, colder regions such as zones 6A, 6B, and 7 experience marked reductions in heating load, while warmer and transitional zones, such as 2A (Lufkin, TX) and 3C (San Francisco, CA), have substantial increases in cooling loads. Although this study does not directly assess the performance of retrofit measures under future climate conditions, it provides a critical foundation for doing so. By quantifying shifts in baseline (i.e., pre-retrofit case) energy loads between historical and future weather files, the study highlights the importance of integrating climate-responsive data into audit tools. These findings will inform future efforts to evaluate the long-term effectiveness and cost-effectiveness of weatherization measures under changing climate conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

NGEE Arctic Authorship Guidelines

Authorship Guidelines were developed to help facilitate trust among team members as we span multiple institutions, scientific disciplines, and career stages. NGEE Arctic was built on a foundation of open science, data sharing, and collaboration. In Phase 4 of the project, it was particularly important to keep this foundation in mind as we develop new collaborations across the Arctic. Included in this package is one *.pdf. The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research. Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

Iversen, Colleen [ORNL] (ORCID:0000000182933450)↗