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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Stakeholder-guided holistic, Adaptive Framework for enhancing community Energy Resilience (SAFER) (Final Technical Report)

The Stakeholder-guided holistic, Adaptive Framework for enhancing community Energy Resilience (SAFER) project advances resilience science and engineering by addressing challenges in rural Kansas communities where aging infrastructure, extreme weather, and socioeconomic disparities heighten vulnerability to energy disruptions. Traditional approaches often focus on technical performance while overlooking community concerns and priorities. SAFER responds by integrating community perspectives with advanced analytical frameworks to create a holistic model for measuring and improving resilience. Project objectives included developing novel resilience metrics, advancing modeling frameworks that capture interdependencies across infrastructures, and embedding community-centric indicators directly into planning processes for distributed energy resources. The key technical innovations included the creation of self-organizing map (SOM)-based indices for objective resilience quantification, hetero-functional graph theory (HFGT) models linking power, water, transportation, and community assets, and graph neural network (GNN) tools for identifying critical nodes in complex systems. Community-centric energy planning was demonstrated through optimal siting and sizing of (photovoltaic) PV and battery storage, ensuring resilience enhancements also addressed energy burden and energy insecurity. SAFER engaged community partners in Dodge City and Ford County through surveys, focus groups, and workshops, generating more than 600 responses that established baseline measures of energy burden, financial insecurity, and willingness-to-pay to avoid outages. This data, organized in terms of a community capitals framework, informed the development of weighted reliability indices that better reflect community costs than traditional utility metrics. SAFER’s GNN-based critical node identification framework identified expert-labelled critical nodes with over 99% accuracy, while also uncovering additional functionalities essential for proactive resilience planning. The project’s models demonstrated that optimal PV and storage deployment could improve resilience indices by over 11 percent, with dispatch strategies further enhancing outcomes, confirming both the technical effectiveness and economic feasibility of these approaches. Through its combined emphasis on rigorous modeling, community-focused planning, and community engagement, SAFER advances the state of resilience research while delivering direct benefits to rural communities. The project provides tools, guidelines, and resilience heatmaps that help utilities, local governments, and residents better anticipate disruptions, prioritize investments, and strengthen the capacity to withstand and recover from energy-related hazards. Furthermore, the developed HFG and GNN frameworks are designed for transferability, allowing them to be adapted for resilience planning in other communities with minimal retraining. This inductive learning capability provides a scalable pathway to extend the SAFER project’s impact. Thus, creating a foundation for a nationally applicable model of infrastructure resilience. Additionally, the HFG can also be extended to include other FEMA community lifelines.

14 SOLAR ENERGY↗
NASA NTRS2014

Modeling Materials: Design for Planetary Entry, Electric Aircraft, and Beyond

NASA missions push the limits of what is possible. The development of high-performance materials must keep pace with the agency's demanding, cutting-edge applications. Researchers at NASA's Ames Research Center are performing multiscale computational modeling to accelerate development times and further the design of next-generation aerospace materials. Multiscale modeling combines several computationally intensive techniques ranging from the atomic level to the macroscale, passing output from one level as input to the next level. These methods are applicable to a wide variety of materials systems. For example: (a) Ultra-high-temperature ceramics for hypersonic aircraft-we utilized the full range of multiscale modeling to characterize thermal protection materials for faster, safer air- and spacecraft, (b) Planetary entry heat shields for space vehicles-we computed thermal and mechanical properties of ablative composites by combining several methods, from atomistic simulations to macroscale computations, (c) Advanced batteries for electric aircraft-we performed large-scale molecular dynamics simulations of advanced electrolytes for ultra-high-energy capacity batteries to enable long-distance electric aircraft service; and (d) Shape-memory alloys for high-efficiency aircraft-we used high-fidelity electronic structure calculations to determine phase diagrams in shape-memory transformations. Advances in high-performance computing have been critical to the development of multiscale materials modeling. We used nearly one million processor hours on NASA's Pleiades supercomputer to characterize electrolytes with a fidelity that would be otherwise impossible. For this and other projects, Pleiades enables us to push the physics and accuracy of our calculations to new levels.

Supercomputing↗
DOE OSTI2023

Radioxenon Detection for Monitoring Subsurface Nuclear Explosion

The Comprehensive Nuclear-Test-Ban Treaty (CTBT) bans the testing of nuclear weapons anywhere on the earth (atmospheric, surface, underwater and subsurface). Identification of nuclear explosions in the atmosphere, surface, and underwater is relatively straightforward considering a wide range of signatures resulting from such an event. However, for a subsurface explosion, most of the signatures traditionally associated with a nuclear explosion are not readily available. Therefore, the international community has increasingly relied on the atmospheric measurement of noble gases to identify subsurface nuclear weapon explosions. This chapter initially covers the basic principles of subsurface nuclear explosion identification and the importance of detecting radioxenon. This is followed by reviewing some of the early radioxenon detection systems that were developed by research groups around the world in the late 1990s and early 2000s. The detection media employed, results from laboratory and field testing, and some challenges/drawbacks for these systems are detailed. The next section of the chapter is dedicated to innovative detector concepts that have emerged in the past ten to fifteen years using novel detection material, algorithms, and signal readout techniques. The advances achieved in terms of energy resolution, coincidence detection efficiencies, system performance, and the minimum detectable concentration are covered. The final section goes over some of the potential improvements that can be incorporated in the design to enhance detector sensitivity and new detection material that can be explored in the field of radioxenon detection.

Gadey, Harish Reddy↗
DOE OSTI2022

Highly efficient interface stabilization for ambient-temperature quasi-solid-state sodium metal batteries

Solid-state sodium (Na) batteries (SSSBs) using sulfide-based solid electrolytes (SSEs) hold tremendous promise due to their high theoretical specific capacity, enhanced safety and abundant resources. However, detrimental interfacial issues between SSEs and Na metal present a major challenge to the advancement of sulfide-based SSSBs. To address interfacial issues, we demonstrate an efficient approach by incorporating an ionic liquid electrolyte ((PYR/Na)TFSI) as interlayer to stabilize the Na metal/SSE interface. The presence of the (PYR/Na)TFSI interlayer enables the formation of a stable solid electrolyte interphase (SEI) to prevent the harmful reactions and inhibit Na dendrites. Combination of ab initio molecular dynamics simulations and X-ray photoelectron spectroscopy revealed that this stable SEI is largely composed of reduced products of TFSI -, such as NaF and CF 3 . As a result, the symmetric cells exhibited stable Na plating/striping cycling for 300 h at 0.1 mA cm -2 . In addition, FeS2||Na quasi-solid-state batteries delivered an impressive specific capacity of over 300 mAh g -1 under the current density of 20 mA g -1 at room temperature. Under a higher current density (100 mA g -1 ), such batteries performed with long-term cycling stability and maintained a specific capacity of around 103 mAh g -1 after 330 cycles. This work demonstrates the novel perspective of using an ionic liquid interlayer to address interfacial issues, contributing to the advancement of high-performance SSSBs for the next-generation energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2025

RELAP5-3D Capabilities for High-Temperature Gas-Cooled Reactor Analysis

RELAP5-3D is the premier systems thermal-hydraulic code in the world. The code has been used significantly for high-temperature gas-cooled reactor (HTGR) analyses over the last 10 years, but there has not been a comprehensive summary of RELAP5-3D capabilities and methods for HTGR modeling. In this paper, we provide a guide for how novice users can build models for prismatic HTGRs. This guide includes best practices for developing heat structures and setting up radiation and conduction heat transfer. We also provide a summary of relevant validation studies. These studies are divided into three categories: separate effects tests, integral effects tests, and nuclear reactor studies. We present a comprehensive review of RELAP5-3D HTGR applications for reactor modeling over the last 10 years. These applications include work for the Modular High-Temperature Gas-Cooled Reactor benchmark, design activities for a prismatic HTGR as part of the U.S. Department of Energy’s Advanced Demonstration and Test Reactor Options Study, and studies performed to design gas-cooled microreactors. Following the comprehensive literature review, we present a gap analysis highlighting capabilities of RELAP5-3D that are available and missing for a complete analysis of HTGR thermal hydraulics. We also discuss the limitations of existing code capabilities and potential improvements that could improve analyses. Current research efforts have yet to fully validate RELAP5-3D for a prismatic HTGR analysis; however, some of this is attributable to confounding factors in the available experimental data as opposed to code capabilities. In conclusion, this paper presents the most comprehensive review to date on RELAP5-3D capabilities, limitations, and applications for HTGR analysis.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Photoionization of tungsten ions: experiment and theory for ${{\rm{W}}}^{4+}$

Experimental and theoretical results are reported for single-photon single ionization of the tungsten ion ${{\rm{W}}}^{4+}$. Absolute cross sections have been measured employing the photon-ion merged-beams setup at the Advanced Light Source in Berkeley. Detailed photon-energy scans were performed at 200 meV bandwidth in the 40–105 eV range. Theoretical results have been obtained from a Dirac-Coulomb R-matrix approach employing basis sets of 730 levels for the photoionization of ${{\rm{W}}}^{4+}$. Calculations were carried out for the $4{f}^{14}5{s}^{2}5{p}^{6}5{d}^{2}{}^{3}{{\rm{F}}}_{J}$, J = 2, ground level and the associated fine-structure levels with J = 3 and 4 for the ${{\rm{W}}}^{4+}$ ions. In addition, cross sections have been calculated for the metastable levels $4{f}^{14}5{s}^{2}5{p}^{6}5{d}^{2}{}^{3}{{\rm{P}}}_{0,1,2},{}_{}{}^{1}{\rm{D}}_{2}^{},{}_{}{}^{1}{\rm{G}}_{4}^{},{}_{}{}^{1}{\rm{S}}_{0}^{}$. In conclusion, a very satisfying agreement of theory and experiment is found for the photoionization cross section of ${{\rm{W}}}^{4+}$ which is remarkable given the complexity of the electronic structure of tungsten ions in low charge states.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

University Research in Support of TREAT Modeling and Simulation, FY 2017

INL is currently evolving a modeling and simulation (M&S) capability that will enable im- proved core operation as well as design and analysis of TREAT experiments. This M&S capability primarily uses MAMMOTH, a reactor physics application being developed under the Multi-physics Object Oriented Simulation Environment (MOOSE) framework. MAMMOTH allows the coupling of a number of other MOOSE-based applications. This work is being supplemented by related research projects at a number of universities. INL is funding TREAT-related research at North Carolina State University, University of New Mexico, Oregon State University, and MIT under internally funded projects within the INL/Battelle National University Consortium Program. Under the DOE Nuclear Energy Advanced Modeling and Simulation program (NEAMS), other research is being performed at MIT, University of Florida, and Texas A&M University. In addition, Dr. Barry Ganapol of University of Arizona was funded for summer work at the INL. This report is a compilation of conference papers that were submitted as part of this research by the NEAMS University partners and from the visiting professor.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

In-Situ Ion Irradiation to Add Irradiation Assisted Grain Growth to the Marmot Tool

In the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the MARMOT mesoscale fuel performance tool is used to inform the development of mechanistic materials models for the BISON fuel performance tool. The grain size of the fuel has a large impact on its performance, directly impacting heat conduction, fission gas release, creep, and fracture. Thus, atomistic and mesoscale MARMOT simulations have been used to investigate grain boundary migration and grain growth in UO 2 . However, the current grain growth models in MARMOT does not consider the effect of irradiation on causing grain growth. This research project experimentally studied and implemented irradiation effects on grain growth of UO 2 into MARMOT.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Validation of NEAMS Tools Using MSRE Data

This report documents the benchmarks developed and performed for the tools and codes developed under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program utilizing the MSRE experiment data. There are three focus areas explored in this work: fuel evolution, CFD, and system transient analyses. Fuel depletion is important for MSR reactor physics and fuel cycle analysis. Fuel depletion capability is currently being developed in the Griffin reactor physics code. To support this, a benchmark problem is developed using the MSRE data and an existing depletion code with flowing fuel analysis functionality (ADDER) to validate this new capability in Griffin. The ADDER calculation is compared with the TRITON-MSR results as well as the MSRE experimental data. This benchmark can be directly used to verify and validate the Griffin fuel depletion capability in future years. For CFD simulation, the MSRE CAD model is obtained from the Copenhagen Atomics and a mesh is generated for the MSRE inlet plenum. The Nek5000 code will be employed to find the flow distribution in the MSRE inlet plenum based on the mesh generated. For system analysis, a simple benchmark problem for three types of MSR system transients is developed. The SAM and SPECTRA codes are used to solve the simple problem, and the results from the two codes agree well. The SAM code is also employed to obtain the frequency response of the MSRE system at the 5 and 8 MWt power levels. The results agree well with the experiment measurements. These verification and validation efforts gives SAM users more confidence in MSR system transient simulations using SAM. Lastly, the SAM-Griffin Multiphysics coupling work is initiated. A simple one-way coupling of evaluating the precursor drift effect on the MSRE k-eff is demonstrated. This preliminary coupling work serves as the basis for future more complex Multiphysics simulation and modelling.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Process Anomaly Detection for Sparsely Labeled Events in Nuclear Power Plants

An essential aspect of online monitoring, subtle anomaly detection increases the detection lead time for equipment failure and enables a nuclear power plant (NPP) to mitigate unexpected partial or full outages, resulting in significant cost saving to the plant. Once an anomaly is detected by plant staff, its cause and severity are investigated. Because the vast majority of anomalies require some level of investigation, including some that require time-consuming examination, before they are passed over to the engineering organization for further analysis, plants are often equipped with tools to assist the staff in performing anomaly detection. Those tools operate as a black box and are often based on statistical methods that establish sensor correlations using preconfigured mathematical models and flag correlation deviations as anomalies. Due to the number of anomalies detected at a given NPP on a daily basis, a significant number of flagged anomalies usually await examination for days or weeks. A primary cause of this backlog is that the methods used by the tools generate many false positives. Though this is usually attributed to oversensitive model settings due to very narrow normal operation bands, it can also be associated with the model development being inadequate for the process being monitored, or with missing model inputs that could have explained misclassified positives. The performance of anomaly detection tools impacts their plant acceptance and utilization, especially when the effort to address false positives generated by the tool depletes the value or cost saved by using that tool. Thus, means to advance anomaly detection performance have been investigated by the Department of Energy’s Light Water Reactor Sustainability program. Previous and ongoing efforts have targeted unsupervised machine-learning (ML) methods, which do not require the labeling of any data fed into the ML model. By contrast, in supervised anomaly detection methods, every data point is labeled as either a normal or abnormal process condition, and the model is trained to replicate the classification process. Supervised methods usually outperform unsupervised methods, due to the added value in differentiating normal from anomalous states of the monitored process. An NPP’s corrective action program requires it to track and document, via a dedicated report, the resolution of any issues that occur within the plant. Once created, each report is reviewed by a plant screening committee, and several classifications and decisions are made. Recently, a collaborating NPP developed an artificial intelligence and ML-based classifier to categorize a condition report (CR) into classes that can serve to label the data as normal or anomalous. Applying CRs as labels represents a semi-supervised use case. Semi-supervised ML assumes that labels exist for some data points (i.e., labeled anomalies, in this case) but not for the rest. In this effort, semi-supervised ML methods were used to fuse data from CRs with anomaly detection methods in order to test the hypothesis that partially labeled anomalies would improve the accuracy of the anomaly detection methods. Specifically, two methods were used. The first is the deep Semi-supervised Anomaly Detection (deep SAD) method, which can handle labels ranging from fully unsupervised to fully supervised cases. The second is a newly designed ML method developed specifically for this effort and referred to as the high-order feature (HOF)-based method. To evaluate these two methods in controlled environments, synthetic data generators were developed and used. The first datasets used a spring-mass-damper (SMD) system simulator commonly found in mechanical engineering references. This was used to create two use cases: a one- and a three-mass system. Anomalies were introduced by changing the spring and damper coefficients while the system was actuated by random forces. The second datasets used the commercial Dymola-Modelica software to build a simplified nuclear reactor model. Anomalies were added in the form of corrupted sensor readings and/or control commands. The deep SAD method was tested using the SMD system, while the HOF method was tested using both datasets. Application of the deep SAD semi-supervised ML method demonstrated that labels can generate increased confidence in detecting true anomalies. This helped increase the number of true positives and decrease the number of false negatives—something that would aid in addressing the backlog of possible anomalies. Application of the HOF method demonstrated that labels can aid in down selecting from a candidate set of features to a more optimal subset in order to better differentiate between normal and anomalous conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1977

Future trends in electrical energy generation economics in the United States

Developments related to the economics of coal-fired systems in the U.S. are mainly considered. The historical background of the U.S. electric generation industry is examined and the U.S. electrical generation characteristics in the year 1975 are considered. It is pointed out that coal-fired power plants are presently the largest source of electrical energy generation in the U.S. Questions concerning the availability and quality of coal are investigated. Currently there are plans for converting some 50 large oil and gas-fired generating plants to coal, and it is expected that coal will be the fuel used in almost all fossil-fired base load additions to generating capacity. Aspects of advanced energy conversion from coal are discussed, taking into account the performance and economic potential of the energy conversion systems.

Schmitt, R. W.↗
NASA NTRS1991

Analysis, design, and experimental results for lightweight space heat receiver canisters, phase 1

Critical technology experiments have been performed on thermal energy storage modules in support of the Brayton Advanced Heat Receiver program. The modules are wedge-shaped canisters designed to minimize the mechanical stresses that occur during the phase change of the lithium fluoride phase change material. Nickel foam inserts were used in some of the canisters to provide thermal conductivity enhancement and to distribute the void volume. Two canisters, one with a nickel foam insert, and one without, were thermally cycled in various orientations in a fluidized bed furnace. The only measurable impact of the nickel foam was seen when the back and short sides of the canister were insulated to simulate operation in the advanced receiver design. In tests with insulation, the furnace to back side delta T was larger in the canister with the nickel foam insert, probably due to the radiant absorptivity of the nickel. However, the differences in the temperature profiles of the two canisters were small, and in many cases the profiles matched fairly well. Computed Tomography (CT) was successfully used to nondestructively demarcate void locations in the canisters. Finally, canister dimensional stability, which was measured throughout the thermal cycling test program with an inspection fixture was satisfactory with a maximum change of 0.635 mm (0.025 in.).

Schneider, Michael G.↗
NASA NTRS1991

Critical technology experiment results for lightweight space heat receiver

Critical technology experiments have been performed on thermal energy storage modules in support of the NASA Advanced Solar Dynamic Brayton Heat Receiver Program. The modules, wedge-shaped canisters containing lithium fluoride (LiF), were designed to minimize the mechanical stresses that occur during the phase change of the LiF. Nickel foam inserts were placed in two of the test canisters to provide thermal conductivity enhancement and to distribute the void volume throughout the canister. A procedure was developed for reducing the nickel oxides on the nickel foam to enhance the wicking ability of the foam. The canisters were filled with LiF and closure-welded at the NASA Lewis Research Center. Two canisters, one with a nickel foam insert, the other without an insert, were thermally cycled in various orientations in a fluidized bed furnace. Computer-aided tomography was successfully used to nondestructively determine void locations in the canisters. Finally, canister dimensional stability was measured after thermal cycling with an inspection fixture.

Schneider, Michael G.↗
NASA NTRS1999

Paving a Highway to Space

This paper presents the Paving a Highway to Space at the 49th JANNAF (Joint Army-Navy-NASA-Air force) Propulsion Meeting. The topics include: 1) Earth-To-Orbit; 2) Orbit and Beyond; 3) Duct Propulsion; 4) Electric Propulsion; 5) Beamed Energy Propulsion; 6) Externally-Effected Force; 7) Nuclear Propulsion; 8) The Road to Higher Power Densities and Performance; 9) Propulsion Technology Map; 10) Launch Applications; 11) Space Applications; and 12) Advanced High-Energy Concepts. This paper is presented in viewgraph form.

Schafer, C. F.↗
DOE OSTI2016

Heated Bundle Test in AREVA Inc's Fuel Cooling Test Facility

As part the Department of Energy (DOE) initiative for advanced nuclear fuel development, AREVA Inc is performing a series of flow and thermal mixing tests on a simulated, internally heated bundle of wire-wrapped fuel pins of the type commonly used in liquid-metal fast-breeder reactors at its Fuel Cooling Test Facility (FCTF) in Richland, Washington. The FCTF is part of the Product Development Test Facility (PDTF), which is a dedicated facility for advanced thermal-hydraulic testing of nuclear fuel assemblies. Initially developed to perform post Loss Of Coolant Accident (LOCA) testing, i.e., spray and reflood tests, this test facility has been adapted to accommodate the unique requirements of the heated bundle tests described here. The purpose of this test is to investigate and measure thermal distribution and pressure drop behavior for two configurations (non-deformed and deformed duct) of heated 61-pin, hexagonally packed fast reactor test assembly in a fully turbulent regime for generating Computational Fluid Dynamics (CFD) validation grade data. This test is performed in conjunction with high fidelity flow field measurement experiments and high fidelity CFD to provide a comprehensive understanding of the flow inside such a design. The present paper focuses on the heated bundle test performed at AREVA Inc. First, the test loop is described and then an overview of the test activities is presented. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

2026 Site Development Plan

The 2026 edition of the Site Development Plan focuses on 30 years of infrastructure plans as they strengthen the core Science, Technology, and Engineering (ST&E) pillars of Lawrence Livermore National Laboratory (LLNL): High-Energy-Density (HED) Science, Advanced Materials and Manufacturing (AMM), and High Performance Computing (HPC).

Tran, Lucas [Lawrence Livermore National Laborator↗
DOE OSTI2026

DUNE – Simulation Validation of Fermilab Detector Reconstruction

DUNE (Deep Underground Neutrino Experiment) is Fermilab’s flagship international experiment designed to study neutrinos by sending an intense beam from Illinois to detectors located 1,300 kilometers away at the Sanford Underground Research Facility (SURF) in South Dakota. To prepare for such a large-scale experiment, physicists develop detailed simulations to produce mock data sets which are analyzed by the CAFAna framework. During my internship, I developed software using the CAFAna framework to analyze simulated detector data and generated plots to make data trends easier to interpret and identify patterns. My analysis has uncovered inconsistencies in reconstructed neutrino tracks, duplicated reconstructed tracks causing sporadic spikes in the data, and unnatural differences in energy levels between interaction types. These analyses help verify that the improvements to detector simulations do not introduce unintended resolution errors and ensure proper reconstruction performance, supporting DUNE’s goal of making precise neutrino measurements and advancing the Department of Energy’s mission of fundamental scientific discovery.

Vershaw, Andre [Unlisted, US, IL; Fermilab] (ORCID↗