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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Upgrade of the CAESium-iodide scintillator ARray (CAESAR) electronics and data acquisition system for optimized performance at FRIB

Here, we report on the upgrade of the electronics and data acquisition (DAQ) of the high-efficiency CAESium-iodide scintillator ARray (CAESAR) at the Facility for Rare Isotope Beams (FRIB). With the on-going capability ramp-up of FRIB, CAESAR is expected to continue to be an in-demand -ray spectrometer owing to its high detection efficiency, compactness, and modularity, enabling easy integration with additional detection and DAQ systems. Within this context, the CAESAR electronics and DAQ were upgraded to remove obsolete modules, enhance the ease of integration with external instruments, and optimize the DAQ live time. We present the comprehensive results from offline (γ-ray sources) and online (in-beam experiment) commissioning, characterizing the performance of CAESAR’s new electronics and DAQ.

CsI(Na) scintillator array↗
DOE OSTI2024

Nuclear safety Enhanced: A Deep dive into current and future RAVEN applications

As the horizon of nuclear energy expands with the advent of small modular reactors, IV generation reactors, and fusion reactors, there is a growing perspective that the licensing process could benefit from a more comprehensive approach. Moving beyond traditional deterministic and PRA analysis might pave the way for a novel safety analysis paradigm propelled by the increasing computational power at our disposal. This paper explores different methodologies that can improve the outcomes of nuclear safety analysis. These range from uncertainty quantification techniques, aimed at enhancing the precision of safety margins, to deploying dynamic event trees by driving system code simulations, capturing the potential evolutions of severe accidents. These methodologies introduce innovative dimensions to safety analysis, considering the consequences of postulated events and the dynamics of accident sequences. However, they also bring forth challenges, especially in managing the complexity and sheer volume of potential scenarios. The paper touches upon some strategies to counter these challenges, emphasizing the importance of adaptability and continuous evolution in the face of emerging nuclear safety concerns. Additionally, the paper sheds light on the need for advanced tools to apply these methodologies. Among these tools is RAVEN, an open-source software designed for parametric and probabilistic analyses. Its core components, including distribution, sampler, and reduced order model, enable various applications, from risk assessment and mitigation to dynamic learning and plant control logic simulations.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A hybrid surrogate modeling framework for the Digital Twin of a Fluoride-salt-cooled High-temperature Reactor (FHR)

While nuclear energy is a non-greenhouse-gas emitting energy source, expensive operational costs due to the high-level of safety requirements decreases their competitiveness in the sustainable energy market. Advanced reactor concepts paired with Digital Twins aim to increase the commercialization gains of nuclear energy by reducing operational costs, increasing reactor reliability and enhancing power generation. To support Digital Twin tasks such as real-time autonomous control, proactive maintenance monitoring or optimizing power demand operations, a fast and accurate virtual representation of the Nuclear Power Plant (NPP) is required. The computational cost of high-fidelity, physics-based models are unsuitable for real-time analysis or scalability. Here, in this work, a hybrid surrogate modeling framework is developed fora Fluoride-salt-cooled High-temperature Reactor (FHR) that leverages physics-inspired models for key reactor components and uses data-driven methods for rapid system state space prediction. The Xenon reactivity feedback model is integrated to inform the surrogate model about the reactor core and the homologous pump theory model is the basis for representing pump degradation. Using a detailed, two dimensional thermal hydraulics model to generate data on the FHR, we train a network of Vectorized Autoregressive Moving-Average with eXogenous input (VARMAX) models to predict the remaining state values. The result is a surrogate model that provides a detailed reactor state representation of 41 system states and a pump degradation analysis. The framework is applied to Load Follows profiles, yielding high accuracy and a speedup that is more than 4000x faster compared to the higher- fidelity thermal hydraulics model, enabling real-time operational intelligence and applications in long horizon predictions. While the surrogate model framework is demonstrated for the particular case of FHR, the hybrid physical/data-driven modeling approach including the network of surrogates and the underlying modularity has the potential to be applied to other physical asset systems.

Digital Twins↗
DOE OSTI2025

Effects of break geometry and orientation on helium-air mixing in simulated reactor cavities of high temperature gas reactors

Here, this study experimentally examined the spatial and temporal variations in air and helium concentrations and temperature fields within simulated reactor cavities of a High Temperature Gas Reactor (HTGR) following helium discharge into an initially air-filled reactor cavity system. Detailed temperature maps were generated using a combination of fiber optics temperature sensor and multiple thermocouple probes within the simulated reactor cavities. The research scenario involved a hypothetical small pipe break in the Reactor Pressure Vessel, resulting in the release of high-temperature helium into the surrounding cavity. A scaled multi-compartment experimental facility, modeled after the General Atomics Modular High Temperature Gas Reactor (GA-MHTGR) design, was constructed for helium and air mixing experiments. Oxygen sensors and thermocouple probes were installed in all five cavities to measure the concentrations of oxygen (or helium) and the temperature distributions of the gas mixture. The experimental findings highlighted the significant impact of the injected helium jet velocity on the gas mixing process and demonstrated how the direction of the helium jet influences the air-helium temperature profiles within the cavities.

Air-ingress↗
DOE OSTI2025

A methodology for decay heat characterization in molten salt reactors

Accurate decay heat prediction in molten salt reactors (MSRs) faces dual challenges: complex operational uncertainties and the need for interpretable models compatible with engineering workflows. This work presents a hybrid machine learning and segmented polynomial methodology that addresses both requirements through three key innovations. First, a modular data architecture encodes MSR-specific operational parameters (power density: 1-100 W cm -3 , humidity: 0-0.1 wt %, air ingress: 0-0.1 mol %) with uncertainty-aware temporal discretization spanning 15 orders of magnitude. Second, region-optimized machine learning models achieve 92.3 % root mean square error (RMSE) reduction over conventional polynomials while maintaining physical interpretability through automated piecewise equation generation. Third, dual front-end interfaces accelerate safety analyses — a Jupyter environment enables researchers to explore 10,000+ parameter combinations via interactive widgets, while a Streamlit web application reduces design iteration cycles through production-grade visualization tools. Operational deployment demonstrates prediction times of only a couple hundred milliseconds for 10 4 years decay profiles, enabling real-time optimization of spent fuel container designs.

42 - ENGINEERING↗
DOE OSTI2026

SMR safety through HTTF modeling and benchmark efforts for code validation for gas-cooled reactor applications

Accurate modeling and simulation tools for thermal-hydraulics calculations are a key element needed to design and license new advanced reactors including Small Modular Reactors (SMR) and Microreactors. Uncertainties in modeling and simulation can have significant safety and economic implications. The High Temperature Test Facility (HTTF) at Oregon State University (OSU) is a scaled integral effects experiment designed to investigate transient behavior in high-temperature gas-cooled prismatic-block nuclear reactors. High-quality measurement data is available from the HTTF that is suitable for a thermal-hydraulics code validation benchmark for gas-cooled reactor simulations. Here, this paper summarizes individual HTTF modeling efforts to date for tool validation at Idaho National Laboratory (INL), Argonne National Laboratory (ANL), Oregon State University (OSU) and Canadian Nuclear Laboratories (CNL) using system thermal-hydraulics codes, Computational Fluid Dynamics (CFD) codes and system-CFD code couplings. Also, the paper introduces the ongoing OECD Nuclear Energy Agency (NEA) High Temperature Gas Reactor Thermal-Hydraulics (HTGR T/H) benchmark that allows for better comparisons of results between different international modeling teams. The benchmark provides well defined computational problems that include code-to-code comparisons and comparisons to measured data. These problems provide an avenue for quantifying accuracy and identifying sources of uncertainty in thermal-hydraulics calculations, including in measured thermophysical properties, as part of validation for gas-cooled reactor simulation tools.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2026

BISON analyses of TRISO fuel performance, its dependence on time-at-temperature, and possible implications for fuel design and qualification

The Advanced Gas Reactor Fuel Development and Qualification (AGR) program has established a substantial technical foundation to support private entry into the U.S. high-temperature gas-cooled reactor market. However, emerging tristructural isotropic (TRISO)-fueled reactor applications include small modular reactors and microreactors with longer fuel residence times, which may expose fuels to higher time-at-temperature (TAT) values than were explored by the AGR program. Increased TAT could affect diffusive and thermomechanical behaviors such as Pd penetration, fission gas release, creep, and fission product transport. In this work, we applied multiscale best-estimate BISON fuel performance modeling to assess these effects within a representative design space based on the AGR-5/6/7 experiment and analyzed trends in predicted particle and compact fuel performance metrics with possible implications for near-term fuel design and qualification. BISON unambiguously predicted that TRISO fuel performance is sensitive to TAT. Increasing TAT was not predicted to increase the magnitude of failure-inducing tangential stresses in particle coating layers. Predictions obtained using a mechanistic model for Pd penetration indicated that penetration depth does not depend strongly on TAT. While these observations suggest that AGR testing provides a conservative upper bound for the steady-state operation of TRISO particles at lower powers and higher residence times, BISON also predicted that the release of poorly retained Ag would increase with TAT. Because these analyses applied models to extrapolate beyond the available experimental data, the authors recommend performing targeted experiments to confirm these predictions. Nevertheless, these predictions may provide reactor developers with enough confidence to make near-term design decisions associated with the potential fuel performance trade-offs of increasing TAT.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Results of the AGR-5/6/7 UCO TRISO fuel irradiation test in the Advanced Test Reactor

AGR-5/6/7 was the last in a series of irradiation experiments sponsored by the U.S. Department of Energy in support of the development and qualification of TRISO coated particle fuel for use in a high-temperature gas-cooled reactor. This experiment was conducted to verify the performance of the reference-design TRISO-coated low-enriched UCO fuel for modular high-temperature gas-cooled reactor normal operating conditions and to explore fuel performance at temperatures substantially beyond those typical of normal operation. A total of 194 UCO fuel compacts in five capsules were irradiated in the Advanced Test Reactor for 360.9 effective full-power days, achieving final burnup ranging from 5.66% to 15.26% fissions per initial heavy metal atom and fast neutron fluence ranging from 1.62 × 10 25 to 5.55 × 10 25 n/m 2 (E > 0.18 MeV). Calculated time-averaged fuel temperatures ranged from 467 °C to 1432 °C, with a peak fuel temperature of 1536 °C. During the first five irradiation cycles (∼180 effective full-power days), 85m Kr fission gas release-rate-to-birth-rate ratios were 10 −7 –10 −6 , indicating no particle failures. Near the end of the sixth cycle, a substantial number of in-pile particle failures occurred in Capsule 1. The fission gas release from this capsule impacted the readings from the other four capsules and led to unreliable fission gas release measurements for all capsules during the last four cycles. A preliminary post-irradiation examination of Capsule 1 fuel and internal components revealed the in-pile particle failures resulted from operational issues with the capsule, not subpar performance of the fuel particles.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Simulations of neutron unbound physics for Geant4

The study of neutron unbound systems via the invariant mass technique is the primary focus of the MoNA Collaboration, which built and operates the Modular Neutron Array (MoNA) and the Large multi-Institutional Scintillator Array (LISA) at FRIB. Advancements in nuclear structure from theory and experiment along the neutron dripline have presented opportunities to understand the nature of unbound systems in higher mass nuclei. The GEometry ANd Tracking (Geant4) platform has been used in high-energy and nuclear physics to simulate particle interactions with as much detail as the user desires. Geant4 currently does not have a physics class to simulate neutron unbound systems. Given the advancement of accelerator facilities and active searches along the neutron dripline, detailed simulations to study the breakup of neutron unbound systems, are necessary. Furthermore, the implementation of the breakup of neutron unbound systems in Geant4 will be presented.

Neutron dripline↗
DOE OSTI2026

Cost estimation of balance of plant equipment scale up for proton exchange membrane water electrolyzer systems

Water electrolyzers that use electricity to split water into hydrogen and oxygen could be a key technology for increasing hydrogen supply to meet expanded and emerging market applications, although currently the capital costs of these electrolyzers are high. Here we examine cost reductions that might be achieved by scaling up proton exchange membrane (PEM) electrolyzer systems and leveraging economies of scale through balance of plant (BOP) components for system sizes between 1 MW and 1 GW. We estimate BOP equipment capital costs of about $\$$848/kW at 1 MW, potentially decreasing to $\$$87/kW at 1 GW (2022-dollar year basis) with most of the cost reduction happening as systems scale from 1 MW to 100 MW. We find that BOP subsystems hydrogen drying and water knockout benefited the most from economies-of-scale cost reductions, and piping, instrumentation, and housing and power electronics were less impacted. These cost reductions from economies of scale could be more significant than estimated cost reductions from manufacturing scale-up reported in literature. These results add to the knowledge base that could guide optimal system designs that balance process scale-up with plant modularization and numbering-up. We also estimate that scaling up BOP could potentially lower the levelized cost of hydrogen (LCOH) by $\$$1.7-$\$$4.6/kg, depending on the scale-up magnitude and the plant capacity factor.

08 HYDROGEN↗
DOE OSTI2024

Performance of cross-flow turbines with varying blade materials and unsupported blade span

Cross-flow turbines could play a larger role in the diversification of the global energy supply if the impact of more cost-competitive design choices on performance and rotor dynamics was better understood. This study focuses on rotor performance and blade strain measurements while varying the following parameters: blade materials and blade free end length by changing strut support position. Towing tank experiments were performed with a modular 1-meter diameter cross-flow turbine consisting of three NACA 0018 blades with two support struts. One strut was fixed at the lower end of the turbine, while the second strut was adjustable, thereby changing the length of the free end. The blade materials tested were carbon, E-glass, and hollow E-glass fiber composites, in decreasing order of stiffness and cost. High-resolution distributed fiber optic sensors were embedded in two of the three rotor blades for each material and provided hundreds of strain measurements per blade. Turbine performance and blade strain were measured while varying tow speed and tip speed ratio. Performance tests were conducted at towing speeds sufficiently high for the performance to be independent of Reynolds number. E-glass blades and carbon blades performed similarly for the most rigid strut configurations. Higher strain was measured on the E-glass blades, and their performance was reduced for less rigid configurations compared to the carbon fiber blades. The performance of the highly deflective hollow E-glass blades was lower overall and became even more degraded for longer unsupported blade span. Furthermore, the results provide insight into the use of various blade materials in cross-flow turbines and guidance on allowable free end length for each material type.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Bayesian Optimized Deep Ensemble for Uncertainty Quantification of Deep Neural Networks: a System Safety Case Study on Sodium Fast Reactor Thermal Stratification Modeling

Deep neural networks (DNNs) are increasingly important to scientific computing and engineering system simulations. Accurate uncertainty quantification (UQ) for DNNs is critical in safety-sensitive engineering domains. Traditional Deep Ensemble (DE) methods, while easy to implement, frequently suffer from poorly calibrated uncertainty estimates and limited predictive accuracy due to reliance on fixed architectures with varied weight initializations. To address these issues, we introduce a workflow that combines Bayesian Optimization (BO) and DE. The workflow is modular, scalable, and integrates parallel BO initialized with Sobol sequences to individually optimize the hyperparameters of each ensemble member. This method enhances ensemble diversity, improves predictive accuracy, and provides reliable uncertainty estimates. We evaluate the proposed BODE approach in a sodium fast reactor thermal stratification modeling case study, where we used a densely connected convolutional neural network to predict turbulent viscosity during the reactor transient with consideration of data noise. We benchmark its performance against several optimization approaches, including baseline deep ensemble, evolutionary algorithm-optimized ensemble, ensemble formed via random search combined with greedy selection, and a BO ensemble using random initialization. Here, our results demonstrate superior performance of the developed BODE approach. In noise-free scenarios, BODE notably reduces incorrect aleatoric uncertainty and significantly enhances predictive accuracy. Under conditions of 5% and 10% Gaussian noise, BODE adaptively quantifies uncertainty proportional to data noise, achieving up to an 80% reduction in root mean square error compared to baseline methods and producing well-calibrated prediction intervals.

Bayesian optimization↗
DOE OSTI2026

Investigating the impact of a multi-module operation environment on the task performance time of human operators – An explanatory study

The worldwide demand for Small Modular Reactors (SMRs) has surged in recent years due to their enhanced safety and versatility in supporting diverse industrial sectors. A unique feature of SMR operation is that a single human operator is responsible for managing multiple modules. Therefore, securing a sufficient amount of human performance data pertaining to this new environment is essential for the safe operation of SMRs. In this explanatory study, a series of experiments were conducted using the NuScale simulator, a representative SMR design, with student operators. A total of 12 student operators were assigned two types of off-normal events and asked to cope with them using paper-based procedures. Subsequently, their task performance times were compared with those of student operators responsible for a single unit based on the Task Complexity (TACOM) measure. Results indicate that the performance of student operators under the experimental conditions of this study degraded by a factor of 2 to 3, depending on the characteristics of the off-normal events.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Advanced nuclear reactor integration opportunities for the pulp and paper industry in the U.S. context: Technical perspectives, gap analysis, and preliminary technoeconomic assessment

Pulp and paper (P&P) manufacturing requires a large amount of low-pressure (LP) steam to digest, wash wood fibers and dry pulp into paper. Most of the LP steam is extracted from backpressure turbines that produce power from high-pressure (HP) steam. This HP steam is generated from burning wood waste material; bark is burned in hog boilers, and lignin is boiled in a black liquor recovery boiler. In a typical integrated P&P mill, 50–100% of the steam is produced from these sources, while additional steam is produced in natural gas (NG), fuel oil, or coal boilers. The other energy-intensive process in the plant is the chemical-recovery section (e.g., lime kiln), which requires high-temperature processing from NG combustion to retrieve and recirculate spent chemicals. This paper assesses the energy and heat demand and material balances of a typical generic kraft pulp mill, along with the nuclear heat, steam, and power integration opportunities to replace conventional combustion systems. The paper also addresses steam and electricity generation through a comprehensive technical and engineering gap analysis of five different nuclear-integration opportunities and their process economics, thus enabling the lignin and bark to be further processed into biobased chemicals or fuels, as well as the potential to reduce overall emissions from kraft pulping. Preliminary findings have shown that the P&P industry could achieve technological benefits by integrating their current manufacturing process with small modular nuclear reactors (SMNRs) on a national level. This research aims to set the path forward for a cleaner and more resilient P&P industry.

Advanced nuclear reactor↗
DOE OSTI2026

PyHydroGeophysX: An extensible open-source platform for integrating hydrological models with geophysical measurements

Hydrological models and geophysical measurements are widely used tools for understanding subsurface hydrological processes relevant to water resource management, yet they typically remain disconnected due to technical barriers. We present PyHydroGeophysX, an open-source Python platform bridging this gap by providing standardized interfaces between hydrological modeling software (MODFLOW, ParFlow) and geophysical simulation tools (PyGIMLi, SimPEG). The platform implements bidirectional workflows: translating hydrological outputs into simulated geophysical responses through petrophysical models, and extracting hydrological information from geophysical inversions. Key features include bidirectional workflow modules, configurable petrophysical models, time-lapse inversion with temporal regularization, parallel computing, and mesh utilities for property transfer between geophysical and hydrological grids. The modular architecture of PyHydroGeophysX enables researchers to incorporate additional models and methods, fostering broader adoption of integrated hydrogeophysical approaches. The software is freely available on GitHub and is intended for researchers and practitioners working at the intersection of hydrology and geophysics.

Hydrogeophysics↗
DOE OSTI2026

Prediction of dynamic behavior of a system undergoing an exchange of components using a transmission simulator method

In systems with modular design, it is of interest to perform component exchanges to upgrade components and explore new system configurations. If the dynamics of the components are known, then dynamic substructuring can be used to obtain a prediction of system performance for the new configuration. The transmission simulator method is a substructuring technique that utilizes an additional fixture to apply an elastic boundary condition to a test article such that an appropriate dynamic response can be obtained for a given substructuring application, and the technique has been used widely for performing coupling and decoupling operations. Here, in this work, a modified transmission simulator method is proposed that allows a direct exchange of components to be performed. In a numerical demonstration, the proposed method is shown to accurately predict the dynamics of an assembly that has undergone a component exchange in which the exchanged components have different material properties and different geometric properties. This approach can be applied to dynamic qualification frameworks in which structures undergo modifications or upgrades rather than complete redesigns.

Component exchange↗
DOE OSTI2024

Coil optimization for quasi-helically symmetric stellarator configurations

Filament-based coil optimizations are performed for several quasi-helical stellarator configurations, beginning with the one from Landreman & Paul ( Phys. Rev. Lett. , vol. 128, 2022, 035001), demonstrating that precise quasi-helical symmetry can be achieved with realistic coils. Several constraints are placed on the shape and spacing of the coils, such as low curvature and sufficient plasma–coil distance for neutron shielding. The coils resulting from this optimization have a maximum curvature 0.8 times that of the coils of the Helically Symmetric eXperiment (HSX) and a mean squared curvature 0.4 times that of the HSX coils when scaled to the same plasma minor radius. When scaled up to reactor size and magnetic field strength, no fast particle losses were found in the free-boundary configuration when simulating 5000 alpha particles launched at $3.5\,\mathrm {MeV}$ on the flux surface with a normalized toroidal flux of $s=0.5$ . An analysis of the tolerance of the coils to manufacturing errors is performed using a Gaussian process model, and the coils are found to maintain low particle losses for smooth, large-scale errors up to amplitudes of approximately $0.15\,\mathrm {m}$ . Another coil optimization is performed for the Landreman–Paul configuration with the additional constraint that the coils are purely planar. Visual inspection of the Poincaré plot of the resulting magnetic field-lines reveal that the planar modular coils alone do a poor job of reproducing the target equilibrium. Additional non-planar coil optimizations are performed for the quasi-helical configuration with $5\,\%$ volume-averaged plasma beta from Landreman et al. ( Phys. Plasma , vol. 29, issue 8, 2022, 082501), and a similar configuration also optimized to satisfy the Mercier criterion. The finite beta configurations had larger fast-particle losses, with the free-boundary Mercier-optimized configuration performing the worst, losing approximately $5.5\,\%$ of alpha particles launched at $s=0.5$ .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Overview of the physics basis for the ARC fusion power plant

Commonwealth Fusion Systems plans to build ARC as the first fusion power plant at a site in Chesterfield County, Virginia, USA by the early 2030s. We present an overview of analysis comprising the physics basis of the ARC V3A design, a high-magnetic-field tokamak with 𝐵 0 =11.4 T, 𝐼 𝑝 =12.0 MA, 𝑅 0 =4.62 m, 𝑎 =1.18 m. ARC V3A is designed to produce 𝑃 𝑓⁡𝑢⁢𝑠 ≈1.13 GW DT fusion power and deliver ⩾400 MW net electric power to the grid. This overview includes quantitative analysis of fundamental issues for design of and operational plasma scenarios for a tokamak power plant, and lays out the design targets and strategic choices for ARC, including empirical fusion performance projections, assessment of H-mode access, ion cyclotron resonance heating simulations, alpha particle physics and time-dependent full-pulse simulations. This is complemented by topical papers on fusion performance and transport, disruption physics, boundary physics and magnetohydrodynamic stability. Critically, these studies identify key model uncertainties and physics risks to be retired through SPARC operation. Due to the modular nature of ARC, early results from SPARC can be incorporated into the design of the first ARC as well as subsequent replacements of the ARC vacuum vessel.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗