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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 OSTI2024

Towards Resilient Near Real-Time Analysis Workflows in Fusion Energy Science

Nuclear fusion holds the promise of an endless source of energy. Several research experiments across the world and joint modeling and simulation efforts between the nuclear physics and high performance computing communities are actively preparing the operation of the International Thermonuclear Experimental Reactor (ITER). Both experimental reactors and their simulated counterparts generate data that must be analyzed quickly and in a resilient way to support decision making for the configuration of subsequent runs or prevent a catastrophic failure. However, the cost if the traditional techniques used to improve the resilience of analysis workflows, i.e., replicating datasets and computational tasks, becomes prohibitive with explosion of the volume of data produced by modern instruments and simulations. Therefore, we advocate in this paper for an alternate approach based on data reduction and data streaming. The rationale is that by allowing for a reasonable, controlled, and guaranteed loss of accuracy it becomes possible to transfer smaller amounts of data, shorten the execution time of analysis workflows, and lower the cost of replication to increase resilience. We develop our research and development roadmap towards resilient near real-time analysis workflows in fusion energy science and present early results showing that data streaming and data reduction is a promising way to speed up the execution and improve the resilience of analysis workflows.

Suter, Fred↗
DOE OSTI2023

Application of NEAMS Multiphysics Framework for Species Tracking in Molten Salt Reactors

This report from Idaho National Laboratory (INL) summarizes the key modeling and simulation activities conducted under the Department of Energy (DOE) Molten Salt Reactor (MSR) Campaign during the Fiscal Year 2023 (FY23). The focus of the work was to leverage state-of-the-art modeling capabilities from the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) codes to enable novel multiphysics and multiscale modeling and simulation of MSRs. Through collaboration with NEAMS code developers, advanced multiphysics analysis capabilities for MSR systems were demonstrated by coupling depletion, thermal-hydraulics, and thermochemistry into an innovative framework for chemical species transport in MSRs. As a result, the framework can track nuclides throughout their lifetimes in the core, from production (depletion) to advection throughout the salt volume (thermal-hydraulics) and off-gassing or precipitation outside of the salt (thermochemistry). This work supports the near-term deployment of MSRs by integrating the synergistic efforts between the DOE’s MSR Campaign and NEAMS program. The resulting framework will help better connect system design modelers with experimentalists to better understand and predict complex physical behaviors in MSRs. Researchers and MSR developers alike can now leverage these new modeling and simulation capabilities to perform novel analyses with applications including: • MSR dynamics during normal operational transients and accident scenarios • Off-gas system design and performance for fuel cycle and depletion analysis • Corrosion and active chemistry control for reactor component health and lifetime determination • Source term, decay heat and activity determination in accident scenarios • Special nuclear material accountancy and chemical forensic analysis for safeguards • Digital twin development of experiments and experimental reactor demonstrations • Measurement requirements for instrumentation and control design • Uncertainty and sensitivity analysis of missing data to inform future experimental data collection.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Resilient Cooperative Voltage Control for Distribution Network with High Penetration Distributed Energy Resources

Here, this paper considers the problem of designing a resilient distributed voltage control algorithm for distribution systems with high penetration of distributed energy resources in the presence of an unknown cyber-attack. The purpose of the attack is to force the system to violate the operating voltage limit by intercepting its communication channels and inserting exogenous signals to perturb and/or modify the information being exchanged. We first review the cooperative voltage control proposed in our previous work and provide a new stability analysis for it. Next, we present a resilient cooperative voltage control algorithm by introducing a virtual system interconnected with the original system such that the voltage can be maintained within the operational limit under unknown attacks. The resiliency of the proposed algorithm is demonstrated via simulations on the IEEE 8500-node system when subjected to an attack which consists of corrupting the data being exchanged in the communication network between two generation units.

cooperative control↗
DOE OSTI2024

Prediction of The TREAT Facility Power and Temperature of Sirius-2c Nuclear Propulsion Fuel Experiment

This paper presents simulation results of the Sirius-2c full power experiment that was performed at the TREAT facility to support experiment modeling and transient analysis of the NASA-sponsored Sirius series of experiments for nuclear thermal propulsion applications. We presents a novel approach to predict the control rod motion and power of the reactor and the temperature of the specimen during transient experiments using the Griffin and Bison packages of the Multiphysics Object Oriented Simulation Environment (MOOSE). First, the model predicts the transient rod motion that results in the desired reactor power shape. Then, the temperature of the specimen is predicted based on the power deposited in the specimen. The prediction results are in good agreement with the measured reactor power and control rod position and over-predicted the specimen temperature which is mainly related to specimen surface emissivities. The reactor reaches a peak power of 80 MW and a specimen temperature of 2500 K and considering the right specimen emissivities the predicted temperature is in an excellent agreement with the measured values. This model can be utilized in helping and supporting the design and optimization a new experiments that are going to be irradiated in the TREAT facility.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Interacting galaxies in the IllustrisTNG simulations - I: Triggered star formation in a cosmological context

ABSTRACT We use the IllustrisTNG cosmological hydrodynamical simulations to investigate how the specific star formation rates (sSFRs) of massive galaxies (M* > 1010 M⊙) depend on the distance to their closest companions. We estimate sSFR enhancements by comparing with control samples that are matched in redshift, stellar mass, local density, and isolation, and we restrict our analysis to pairs with stellar mass ratios of 0.1 to 10. At small separations (∼15 kpc), the mean sSFR is enhanced by a factor of 2.0 ± 0.1 in the flagship (110.7 Mpc)3 simulation (TNG100-1). Statistically significant enhancements extend out to 3D separations of 280 kpc in the (302.6 Mpc)3 simulation (TNG300-1). We find similar trends in the EAGLE and Illustris simulations, although their sSFR enhancements are lower than those in TNG100-1 by about a factor of two. Enhancements in IllustrisTNG galaxies are seen throughout the redshift range explored (0 ≤ $z$ < 1), with the strength of the enhancements decreasing with increasing redshift for galaxies with close companions. In order to more closely compare with observational results, we separately consider 2D projected distances between galaxies in IllustrisTNG. We detect significant sSFR enhancements out to projected separations of 260 kpc in TNG300-1, with projection effects diluting the size of the enhancements by about 20 per cent below 50 kpc. We find similar sSFR enhancements in TNG100-1 and Sloan Digital Sky Survey galaxies, with enhancements extending out to projected separations of about 150 kpc for star-forming galaxies at $z$ < 0.2. Finally, by summing over all separations, we estimate that the presence of closest companions boosts the average sSFR of massive galaxies in TNG100-1 by 14.5 per cent.

Patton, David R.↗
DOE OSTI2022

Resilient cooling through geothermal district energy system

Decarbonization and resilience to heat waves have recently become high priorities for building and district energy systems. Geothermal coupled district heating and cooling systems that operate a water loop near ground temperature gain increasing adoption to support decarbonization. In these systems, vapor-compression machines, distributed in the energy transfer stations, lift the temperature up or down to the needs of the particular building. In principle, these systems can provide low-power, free cooling from the geothermal bore field during heat waves when electricity is often scarce. However, the performance of such a resilience operation mode and its implication on the energy system configuration and the sizing of the bore field and HVAC equipment is not yet understood. Consequently, we are assessing their resilience, power use and design implications under a scenario of a heat wave on five working days during which chillers are switched off to reduce electrical consumption. Our analysis is based on high-fidelity, coupled dynamic models of district energy, building-side HVAC and actual control logic, with whole building energy simulation used to assess thermal conditions in a 2004 vintage multi-zone office building in Chicago, IL. The results show that relying only on waterside economizer cooling, the indoor thermal conditions can be maintained in a tolerable range for the majority of the building zones with half the electrical energy compared to standard chiller operation. Thermal comfort in the hottest zones can be further improved by oversizing the cooling coil. However, the waterside economizer has significant implications on the system configuration and sizing: The geothermal bore field needs to be sized about 30% larger than the upper limit of the range observed for conventional geothermal systems. Nevertheless, if a central chiller plant is added, the bore field can be downsized to the typical design range. The latter configuration still allows compressor-less cooling during the heat wave with peak power reduced by 60% compared to the standard design and chiller operation.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Transient fuel performance analysis for the preliminary fuel concept of general atomics fast modular reactor

This study investigates the transient fuel performance of General Atomics Fast Modular Reactor (GA-FMR) during accident scenarios, focusing on the behavior of its innovative fuel system that combines high-assay low enriched uranium dioxide (HALEUO2) fuel with SiGA® ceramic matrix composite silicon carbide cladding. The preliminary fuel design’s response was analyzed during reactivity-initiated accidents (RIA) and loss of coolant accidents (LOCA) using BISON fuel performance analysis code, which included both the diffusion enhanced and BISON-FASTGRASS coupled UO 2 models. The RIA analysis demonstrated that effective reactivity control reduced fuel temperature, though with transient fission gas release resulting in additional tensile stress state on the cladding. LOCA simulations revealed differing predictions between the two models: the BISON UO 2 model showed more transient fission gas release but minimal pellet expansion, while the BISON-FASTGRASS UO 2 model predicted less pronounced fission gas release but more fuel swelling and thermal expansion, potentially leading to pellet-cladding mechanical interaction. Here, these findings highlight critical areas for fuel design optimization and identify knowledge gaps requiring further experimental and computational investigation to advance GA-FMR fuel development.

Lee, Soon K. [Argonne National Laboratory (ANL), A↗
DOE OSTI2020

Molecular mechanisms underlying the extreme mechanical anisotropy of the flaviviral exoribonuclease-resistant RNAs (xrRNAs)

Mechanical anisotropy is an essential property for many biomolecules to assume their structures, functions and applications, however, the mechanisms for their direction-dependent mechanical responses remain elusive. Herein, by using a single-molecule nanopore sensing technique, we explore the mechanisms of directional mechanical stability of the xrRNA1 RNA from ZIKA virus (ZIKV), which forms a complex ring-like architecture. We reveal extreme mechanical anisotropy in ZIKV xrRNA1 which highly depends on Mg 2+ and the key tertiary interactions. The absence of Mg 2+ and disruption of the key tertiary interactions strongly affect the structural integrity and attenuate mechanical anisotropy. The significance of ring structures in RNA mechanical anisotropy is further supported by steered molecular dynamics simulations in combination with force distribution analysis. We anticipate the ring structures can be used as key elements to build RNA-based nanostructures with controllable mechanical anisotropy for biomaterial and biomedical applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A two-dimensional type I superionic conductor

Superionic conductors (SICs) possess liquid-like ionic diffusivity in the solid state, finding wide applicability from electrolytes in energy storage to materials for thermoelectric energy conversion. Type I SICs (e.g., AgI, Ag 2 Se, etc.) are defined by a first-order transition to the superionic state and have so far been found exclusively in three-dimensional crystal structures. Here, we reveal a two-dimensional type I SIC, α-KAg 3 Se 2 by scattering techniques and complementary simulations. Quasi-elastic neutron scattering and ab initio molecular dynamics simulations confirm that the superionic Ag + ions are confined to sub-nanometre sheets, with the simulated local structure validated by experimental X-ray powder pair-distribution-function analysis. Finally, we demonstrate that the phase transition temperature can be controlled by chemical substitution of the alkali metal ions that comprise the immobile charge-balancing layers. Our work thus extends the known classes of SICs and will facilitate the design of new materials with tailored ionic conductivities and phase transitions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Ensemble Federated Machine Learning‐Based Cybersecurity Situational Awareness in Microgrid Network

Cyber-physical microgrids are vulnerable to stealthy cybersecurity threats that disguise their actions through the exploitation of system knowledge. Such actions can severely impacts microgrids deployed in defense bases, slowing the response time of military forces during national emergencies. Several machine-learning algorithms have been proposed to detect intrusions in the grid networks; however, these traditional machine-learning algorithms lack data privacy and are subject to several adversarial machine-learning threats. This paper proposes a novel federated machine learning (FML)-based three-model framework to detect and identify stealthy data-integrity attacks while ensuring data privacy in microgrid networks. The proposed architecture uses a variational mode decomposition technique to extract derived features from incoming measurement and control datasets. The extraction of these derived features allows FML models to learn minute variations in data patterns that allow them to perform significantly better than the models trained with generic datasets consisting of raw features. Our experimental results show the efficient performance of the proposed methodology against different types of data integrity attacks while considering primary and secondary controllers in microgrids. Further, the applied FML-integrated random forest ensemble algorithm outperforms the existing generic FML algorithms during noisy and noise-free datasets with prediction latencies of only 91–134 µs per sample within the 0.1 s sampling interval and requires communication bandwidth of around ∼8.25 KB/s at the control center and ∼2.7 KB/s per edge client for communication.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Investigation of Abnormal Level Control Oscillations in a BWR Feedwater System

In the long-term operation of nuclear power plants, the aging of systems, structures, and components can lead to maintenance issues that must be dealt with to maintain cost-effective plant operations. One common issue affecting the currently operated boiling water reactors is the onset of unexpected level oscillations in feedwater heaters. This phenomenon can cause excessive cycling of drain valves and lead to premature failures. In this work, we develop a dynamic model of a set of feedwater heaters to determine the root cause of oscillations observed in an operating plant. Simulation results of various transient scenarios were used to investigate the effects of the controller parameters, boundary conditions, and possible valve and instrument issues. The analysis led to the conclusion that the most likely causes of the observed self-sustained oscillations in the system are the nonlinear behaviors of the drain valve and the level transmitter induced by degraded equipment condition. In conclusion, a partial plug of the pressure line used for level sensing in the system can account for a significant deadtime in the level transmitter, a nonlinear effect shown to induce self-sustained oscillatory behaviors.

Boiling water reactors↗
DOE OSTI2020

Stable compression of a spherical tokamak plasma

In this study, an analysis of toroidal plasma compression by a collapsing flux conserver reveals linearly stable scenarios of operation to high compression ratios. The resistive and ideal MHD stability is calculated in full toroidal geometry using the asymptotic matching method in realistic conditions. A time dependent MHD simulation of the compression is conducted to confirm the conservation principles used to calculate the equilibrium states for the analysis. The near edge current profile, controlled by toroidal field ramping during compression, is shown to be critical to stability due to coupling between poloidal components of the least stable mode. Two cases with slight differences in edge current are examined, one with a stable corridor to high compression and one without.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

The impact of aerosol mixing state on immersion freezing: insights from classical nucleation theory and particle-resolved simulations

Immersion freezing, initiated by ice-nucleating particles (INPs) in supercooled aqueous droplets, plays an important role in the formation of ice crystals within clouds. The efficiency of immersion freezing depends strongly on INP composition and, crucially, on the mixing state – how chemical species are distributed across the particle population. Here, we quantify the impact of aerosol mixing state on immersion freezing using a combined theoretical and particle-resolved modeling approach. We derive analytical expressions for the frozen fraction of internally and externally mixed INP populations based on classical nucleation theory, showing that the frozen fraction is sensitive to whether ice-active species are present in all particles or only in a subset of the population. We introduce a multi-species immersion freezing scheme into the particle-resolved model PartMC, using the water activity-based immersion freezing model (ABIFM) to compute freezing probabilities for mixed-composition particles. To improve computational efficiency, we implement a Binned Tau-Leaping algorithm and demonstrate an order-of-magnitude speedup with minimal accuracy loss. Simulations reproduce the analytical trends in limiting cases and extend the analysis to more general aerosol populations, where mixing state continues to exert a substantial control on frozen fraction. Sensitivity analyses across particle size, species type, and cooling condition reveal that the mixing state effect is most pronounced when small amounts of highly efficient INPs are mixed with less efficient materials. These findings underscore the need to represent aerosol mixing state explicitly in models of heterogeneous ice nucleation to reduce uncertainty in cloud-phase partitioning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Engineering Scale Drying of Aluminum-Clad Spent Nuclear Fuel: Experiment Report

Engineering-scale tests were performed to evaluate the relative effectiveness of forced gas and vacuum-drying processes on aluminum-clad spent nuclear fuel (ASNF) in preparation for extended dry storage. Drying models were developed to improve confidence in the likely range of conditions at the start of dry storage and to understand the factors most significant to each process. Testing was performed at the Holtec International Forced Helium Dehydration training facility in Camden, New Jersey, by students from the University of South Carolina in collaboration with Idaho National Laboratory. A full-size Type 1a basket, with a full-diameter vessel configuration (based on the Department of Energy standardized canister design), was used in combination with a 10 assembly surrogate ASNF arrangement to provide a proxy for geometry. A resistance heater incorporated in one assembly simulated the influence of 100 W decay heat. This instrumented chamber allowed testing of the removal of bulk water, physisorbed water, and chemisorbed water over a range of operating parameters with either drying process. Thick oxide films were grown on aluminum test plates to mimic the ASNF surface chemistry. These one-use test plates were housed within select assemblies during drying. Post-test analysis of these plates gave a measure of the moisture removed during each test, which was compared to a control. Instrumentation provided detailed thermal, humidity, and gas or pressure data relevant to each test. Model simulations generally compared favorably to instrument data for the tests. While both processes were able to remove bulk water, removal of chemisorbed water was shown to depend heavily on local temperature. To the disadvantage of vacuum drying, operations approaching or exceeding 220°C achieved consistently more dehydroxylation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Signature Analysis Utilizing a Dynamic Molten Salt Reactor Model for MC&A

Moving from traditional fixed fuel nuclear reactor systems to a mobile, dynamic fuel system that has dissolved special nuclear material in a molten salt is a paradigm shift in several respects. One major consideration is how to develop effective nuclear material controls and accounting for these novel reactor systems. The Molten Salt Reactor Experiment is one example of a critical molten salt system and provided a significant reference library based on the documented effort. But it was low thermal power that was not intended to reflect a commercial scale electricity production design. Therefore, to facilitate and assist vendors with domestic licensing considerations, research is underway to identify methods that could be used for domestic safeguards approaches for these novel reactor systems. This research presents the results of a signature analysis of data generated from three simulated scenarios using the molten salt demonstration reactor model defined in the Transient Simulation Framework of Reconfigurable Modules. Each scenario provides 1 hour isotope inventories over a 180 day period. The scenarios investigated provide test cases to examine if direct gamma-ray spectroscopy of the fuel can be used to identify changes comparing a base case (no reactivity control and fixed fission contribution) to an insertion of reactivity (10 pcm no change in fission composition) and a change in fission composition. The analysis demonstrates that monitoring the total count rate in a highly collimated high-resolution photon energy spectrum is sensitive to perturbations imposed into the reactor model. The total photon count rate changes ≈2% for the fission composition change and ≈4.5% for the reactivity insertion compared to the base case. However, both scenarios show an increase in the total photon count rate. The total photon count rate can be used to identify changes due to power (number of fissions) but not due to a change in the material undergoing fission. To distinguish between the two cases of increased power, the photon spectrum would require an intensive analysis technique. A photon peak count rate ratio analysis could be used to identify changes in the fissile material fission generation in the core through identification of a static peak that shows little variation to the source of fission and a highly varying peak. The photon peak strength will ultimately be determined by the isotope’s fission yield. A preliminary analysis investigating the coupling of the isotope’s fission yield and its concentration in the fuel salt derived from the modeling has been performed. A ratio analysis of the photon peak count rates of 140 La to 99 Mo demonstrated that the reactivity insertion creates a distinct difference in the ratio compared to the fission composition change scenario.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Comparative analysis of thermal management systems in electric vehicles at extreme weather conditions: Case study on Nissan Leaf 2019 Plus, Chevrolet Bolt 2020 and Tesla Model 3 2020

With the surge in electric vehicle (EV) adoption and the need for extended driving ranges, optimizing energy efficiency, particularly through thermal management, is critical, especially in extreme weather. Managing the substantial energy needed for cabin climate control and battery temperature regulation can increase energy demands by over 50 %, severely limiting range. This study conducts a comparative analysis of thermal management systems (TMS) in three popular EV vehicles, 2020 Chevrolet Bolt, 2019 Nissan Leaf Plus, and 2020 Tesla Model 3, evaluating their distinct TMS configurations and performance under varied weather conditions. Using both numerical simulations and experimental data collected on a controlled test bench at Argonne National Laboratory, we assess how TMS architecture and operational modes influence energy consumption and range. A comprehensive TMS model was developed, integrating cabin and battery thermal sub-models in the Autonomie software platform, to simulate temperature fluctuations and range impacts. Cabin climate was modeled using a mono-zonal approach, while battery cell temperature distribution was estimated through a 2D nodal structure. Each vehicle's distinct TMS setup was evaluated: the Chevrolet Bolt and Tesla Model 3 use a dual evaporator vapor compression cycle with a PTC heater for the cabin and a coolant loop for battery thermal management; the Nissan Leaf Plus employs a heat pump with a PTC heater for the cabin and air-cooling for the battery. Tests conducted at ambient temperatures of 35°C, 22°C, -7°C, and -18°C reveal significant differences in energy use and range reduction across both configurations and conditions. At 35°C, the Tesla Model 3, Chevrolet Bolt, and Nissan Leaf Plus have a range reduction of 8%, 9%, and 13%, respectively, due to air conditioning. In winter, heating technology is paramount; at -7°C, the Nissan Leaf's heat pump configuration achieves a lower range reduction (19.3%) compared to the Tesla and Chevrolet Bolt PTC heaters, which reduce range by 28.3% and 31%, respectively. Further, this study provides valuable insights for automotive engineers, EV technology researchers, and thermal management system designers aiming to enhance electric vehicle performance by understanding how different weather conditions and TMS architectures impact energy consumption and driving range.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.

42 ENGINEERING↗