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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 OSTI2025

Design of Defensive Cybersecurity Architectures for Sodium-Cooled Fast Reactors

This report presents the design of defensive cybersecurity architectures (DCSAs) for Sodium-Cooled Fast Reactors (SFRs). A DCSA is a cybersecurity design feature that places systems into security zones in a graded approach according to the importance of the functions performed by the systems. DCSA design efforts for advanced reactors may commence as early as the system-level design phase. This design approach is consistent with the draft regulatory guide for advanced reactor cybersecurity programs (DG-5075) and enables advanced reactor designers to consider the effects of security-by design (SeBD) features on their DCSAs. Integration of DCSA design and other cybersecurity activities with the traditional design process as part of a SeBD framework may enable advanced reactor designers to improve the security posture of their plants while reducing implementation and operating costs. This report provides a DCSA template for an exemplar SFR and how the template may be optimized for a given SFR design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

PyARC Status Report: New Integrations and Upgrades to the Fast Reactor Analysis Workflow Management Tool

PyARC was initially developed as an open source tool to support fast reactor analyses using the Argonne Reactor Computation (ARC) code suite as a part of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Workbench initiative in FY17. The goal of this initiative is to provide a common user interface for model generation, real-time validation, execution, output processing, and visualization for all integrated codes. This is accomplished through the reliance on tools available in the Workbench framework and runtime environment. While initially developed to support the ARC codes, PyARC was extended in FY22 to wrap other NEAMS and non-ARC codes, including Griffin and OpenMC, in the supported other neutronics workflows, and support users in the adoption of NEAMS-supported high fidelity analysis codes. Most recently, NUBOW-3D, a recently adopted ARC code, was integrated to support reactor bowing calculations as well. Integration of these codes into the NEAMS Workbench directly benefits the advanced reactor modeling community by: • Providing a set of controlled, maintained, documented and validated scripts to generate inputs, which promotes best practices, reduces the learning curve, and facilitates project collaboration. • Improving the user experience: the Workbench interface provides assistance for building an input through auto-completion, real-time validation, document navigation, and geometry and results visualization. • Automating complex calculations and workflows for reactor analysis. • Helping users transition to using high-fidelity NEAMS codes along-side the ARC codes. In FY22, a progress report was published that described the state of each of the tools integrated into PyARC. Since then, there have been many enhancements and upgrades to the existing integrations as well as entirely new code integrations as well. This report details all new integrations and major developments in PyARC since the version 2.0.0 release highlighted in the FY22 report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Computational Design of Improved Fast Reactor Cladding

HT9 ferritic-martensitic (FM) steel has served as a leading candidate for sodium-cooled fast reactor (SFR) cladding due to its favorable resistance to irradiation-induced swelling and good thermal and chemical properties. However, its limited creep strength at temperatures above 600 °C and susceptibility to α′ phase embrittlement under specific conditions could limit its application in next-generation SFRs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1977

Nuclear safety considerations in the conceptual design of a fast reactor for space electric power and propulsion

Some nuclear safety aspects of a 3.2 mWt heat pipe cooled fast reactor with out-of-core thermionic converters are discussed. Safety related characteristics of the design including a thin layer of B4C surrounding the core, the use of heat pipes and BeO reflector assembly, the elimination of fuel element bowing, etc., are highlighted. Potential supercriticality hazards and countermeasures are considered. Impacts of some safety guidelines of space transportation system are also briefly discussed, since the currently developing space shuttle would be used as the primary launch vehicle for the nuclear electric propulsion spacecraft.

Hsieh, T.-M.↗
DOE OSTI2026

Advanced Facility Design and AI/ML Enabled Safeguards to Establish Secure, Economical Recycling of Fast Reactor Fuels (Final Scientific/Technical Report)

The project, "Advanced Facility Design and AI/ML Enabled Safeguards to Establish Secure, Economical Recycling of Fast Reactor Fuels," represents a significant advancement in nuclear fuel recycling technology. It integrates cutting-edge multimodal sensor fusion, machine learning (ML), and digital twin (DT) technologies to address challenges in material safeguarding, process optimization, and regulatory compliance for pyroprocessing facilities. This research has significantly enhanced the understanding of pyrochemical fuel recycling processes by developing innovative tools and methodologies. The Multimodal Safeguards Monitoring Unit (MSMU) combines electroanalytical techniques, Raman spectroscopy, and differential thermal analysis (DTA) to enable high-fidelity, near-real-time material accountancy measurements. Machine learning techniques, such as Long Short-Term Memory (LSTM) autoencoders, are utilized to detect anomalies in material balances and sensor data, improving the reliability of safeguards monitoring. Additionally, digital twin technology has been established to provide real-time system-level monitoring and diagnostics, integrating physics-based models with sensor data to optimize process safety and efficiency.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Development and application of two-step uncertainty propagation and sensitivity analysis methodology for fast reactor safety analysis

Uncertainty quantification (UQ) in nuclear reactors for transients is directly linked with safety assessment through the cross-sections uncertainties, provided as a covariance matrix, which are propagated through the reactor system to output of interest pertaining to reactor safety, such as peak temperatures in fuel/clad/coolant. Using a two-step approach, uncertainties are first quantified and propagated from basic input variables (such as reaction cross-sections) to intermediate quantities (such as reactivity feedback coefficients) through lattice level calculations. Uncertainties of intermediate quantities (from the first step) are then propagated through the system transient calculations, in the second step, to obtain uncertainties on reactor safety output parameters of interest. The scope of this work consists of Uncertainty Quantification & Propagation of nuclear data uncertainties that are highly correlated through unprotected transient overpower and unprotected loss of flow to assess their impact on core safety parameters. This two-step approach in the presence of covariance renders the sensitivity analysis very challenging. In fact, usually the sensitivity analysis is restricted to each step, which limits its application since the sensitivities between the system output quantities and the basic input variables are difficult to obtain. Here, in this work, we address this issue by proposing a simple, general methodology to combine the sensitivity indices obtained in each step by assuming the model behavior being linear. For the first step Generalized Perturbation theory based indices are used while in the second step the recently studied Johnson indices. The uncertainty quantification and sensitivity methodologies discussed here are demonstrated on a generic LFR design which is based on the 500 MWth demonstration Lead-cooled fast reactor (DLFR) using oxide fuel, developed by Westinghouse Electric Company (WEC).

42 - ENGINEERING↗
DOE OSTI2024

CFD simulations of Molten Salt Fast Reactor core cavity flows

Computational Fluid Dynamics (CFD) has become increasingly important in the research and development of advanced nuclear reactors. Here, in the current study, extensive CFD simulations were conducted for the coolant flow in Molten Salt Fast Reactor (MSFR) core models using the state-of-the-art spectral element flow solver Nek5000 and multiscale coarse-mesh thermal-hydraulic software Pronghorn. The underlying motivation is to seek an in-depth understanding of how the internal velocity distribution can be influenced by the MSFR core cavity shape, the Reynolds number, turbulence modeling options and the inlet boundary conditions. The CFD techniques involved in this investigation range from coarse-mesh CFD, RANS modeling, to the high-fidelity LES calculations. Specifically, a series of RANS simulations were performed for the 2-D axisymmetric core model and 3-D wedge domains to study the flow distribution inside the MSFR core. It is observed that a proper representation of the MSFR inlet channel duct is important for the prediction of internal flow distribution. It is also showcased here how researchers can leverage the Nek5000 CFD results to calibrate more efficient coarse-mesh CFD tools, like Pronghorn, for the actual MSFR design needs. Moreover, this paper highlights a 3-D LES model for an entire MSFR core using the spectral element method and demonstrates the feasibility of this modeling approach. The readiness and potential limitations of the RANS approach are examined with respect to the high-fidelity LES simulations. The present investigation lays a solid foundation as we are leveraging the high-fidelity CFD capabilities to inform MSFR design efforts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

SAS4A/SASSYS-1 Verification Testing for Sodium Fast Reactor Applications (Acceptance Testing Report)

SAS4A/SASSYS-1 (SAS) is a simulation tool used to perform deterministic analyses of anticipated events as well as design basis and beyond design basis accidents for advanced liquid-metal- cooled nuclear reactors. With its origin as SAS1A in the late 1960s, the SAS series of codes has been under continuous use and development for over fifty years and represents a critical investment in safety analysis capabilities for the U.S. Department of Energy. To support demonstration of software pedigree and confirm key functional requirements, this report has been generated to provide detailed verification of the software. Although SAS was developed to support the analysis of any liquid-metal-cooled nuclear reactor, the acceptance testing described in this document focuses on the verification of SAS capabilities as they relate to pool-type Sodium Fast Reactors (SFRs). This report includes documentation of the test problem definition, analytical solution(s), computational solution(s), acceptance criteria, comparisons of analytical/computational solutions, and determination of acceptance of the computational solution(s). Deviations from acceptance criteria are noted.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

SCALE Demonstration for Sodium-Cooled Fast Reactor Fuel Cycle Analysis

In support of the US Nuclear Regulatory Commission non-light-water reactor fuel cycle demonstration project, SCALE 6.3.1 capabilities for radionuclide characterization, criticality, and shielding were demonstrated for scenarios in the sodium-cooled fast reactor (SFR) nuclear fuel cycle. Three postulated accident scenarios were selected for analysis in this work. As a basis for all scenarios, irradiated fuel inventories were generated using SCALE/ORIGAMI. To cover multiple SFR design choices, two different types of SFR fuel, uranium/transuranic-loaded and U-based fuels, were considered. For the first scenario, SCALE/MAVRIC was used to calculate the radiation shielding and dose rates inside and outside of the containment building due to a drop of a spent fuel assembly from the fuel-handling system during unloading inside the containment building. For the second scenario, potential critical configurations in an electrofiner were investigated through criticality calculations with SCALE/CSAS. For the third scenario, the activity of the waste salt from an electrorefiner was evaluated using SCALE/ORIGEN. The dose rate produced by the analyzed SFR assemblies is similar to that produced by a typical pressurized water reactor (PWR) fuel assembly with a discharge burnup of 50 GWd/MTU, with the same cooling time of 10 days. The criticality analyses suggested that the different electrorefiner configurations have a large margin to criticality. The activity analysis of the electrofiner waste revealed that shielding and cooling may be required for the waste salt that contains transuranics and fission products produced by the electrorefiner because of the high activity of the waste salt. In general, the application of various capabilities in the SCALE code system for SFR fuel inventory generation, criticality, and shielding was successfully demonstrated for the selected scenarios in the SFR nuclear fuel cycle. Additional analyses can be performed to provide more accurate results when more details of the SFR nuclear fuel cycles are available, for example, the dimension of the electrorefiner and the salt compositions during reprocessing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

SCALE 6.3.1 Radiation Source Terms and Shielding Analysis for a Postulated Sodium-Cooled Fast Reactor Accident Scenario

In support of the US Nuclear Regulatory Commission non–light-water reactor fuel cycle demonstration project, SCALE 6.3.1 capabilities for radiation source term and shielding calculations are demonstrated for scenarios in the sodium-cooled fast reactor (SFR) fuel cycle. A postulated accident scenario, which consists of a seismic event causing the refueling machine to fall and release a spent fuel assembly inside the containment building (CB), is analyzed in this paper. Radiation source terms were generated for a U/TRU-10Zr metal fuel assembly with a 16.5% initial transuranic waste content and a discharge burnup of approximately 95 GWd/tHM; source terms were also generated for a high-assay low-enriched uranium metal fuel assembly (U-10Zr) with a 16.5% initial enrichment and a discharge burnup of 149.74 GWd/tHM. These radiation source terms were then used to determine the dose rate inside the CB and near the outer surface of the CB for a range of spent fuel assembly cooling times. The dose rate produced by the analyzed SFR assemblies is similar to that produced by a typical pressurized water reactor assembly with a discharge burnup of 50 GWd/MTU. Ultimately, the validation of the source terms predicted for SFRs with SCALE will need to be demonstrated via the use of assay measurements.

Radulescu, Georgeta↗
DOE OSTI2025

SAS4A/SASSYS-1 Verification Testing for Sodium Fast Reactor Application: Acceptance Testing Report

AS4A/SASSYS-1 (SAS) is a simulation tool used to perform deterministic analyses of anticipated events as well as design basis and beyond design basis accidents for advanced liquid-metal-cooled nuclear reactors. With its origin as SAS1A in the late 1960s, the SAS series of codes has been under continuous use and development for over sixty years and represents a critical investment in safety analysis capabilities for the U.S. Department of Energy. To support the dedication effort, this report has been generated to provide a detailed description of the available verification testing. The verification testing presented in this report captures functionality testing, focusing mainly on the testing of specific functions and algorithms for accuracy and precision of output, and interface testing, focusing mainly on the testing of critical input parameters and their valid ranges. Although SAS was developed to support the analysis of any liquid-metal-cooled nuclear reactor, the testing described in this document primarily focuses on the verification of SAS capabilities as they relate to a generic pool-type Sodium Fast Reactor (SFR).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Nuclear Data Impact on Key Metrics for a Representative Molten Chloride Fast Reactor Model

Nuclear data are an essential component of the foundation on which all modeling and simulation methods and tools are relying upon, from the front end to the back end of the nuclear fuel cycle. In this study, the impact of uncertainties in nuclear data is investigated for a representative molten chloride fast reactor, for several important metrics, including eigenvalue, reactivity differences, and nuclide inventories in fuel at 5-yr irradiation. Uncertainty of keff for a full core model was found to be similar between the fresh fuel and the irradiated fuel states (1.7-1.8%), with its primary driver being the uncertainty in the 235U (n,γ) cross section. The results obtained for the reactivity differences show large uncertainties, of over 100%, in elastic scattering sensitivities of several nuclides, which led to large uncertainties of temperature reactivity differences for cladding and reflector. These results provide evidence that the currently applied methods may not be sufficiently adequate for ensuring the reliable determination of such metrics.

Procop, Germina [ORNL] (ORCID:0000000342226393)↗
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 OSTI2024

Utilizing a Virtual Sodium-Cooled Fast Reactor Digital Twin to Aid in Diversion Pathway Analysis for International Safeguards Applications

We report digital twin technology has the potential to improve the effectiveness of international safeguards inspectors by providing a tool which can: first, perform an accurate diversion path analysis, identify their indicators, and required sensors to detect them; and second, monitor facilities in real-time using critical data streams that benefit from this safeguards-by-design approach. Safeguards inspectors are required to visit facilities and verify the nuclear material to ensure no diversion has taken place and detect misuse of the facility; however, this analysis and verification effort is time consuming, and with limited funding it is imperative that time spent at a nuclear facility is focused on key areas. A virtual digital twin of three prototypic sodium fast reactors was developed, where diversion and misuse scenarios were explored to determine how a digital twin could provide inspectors with an understanding of how proliferation may occur and where the most likely areas for proliferation would be. For each of the three reactors, an optimization algorithm was able to find core designs which would be difficult to detect via sensors alone; however, the use of a machine learning adapter provided by the digital twin was able to show general trends in where proliferation as likely to take place.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Development of a Representative Molten Chloride Fast Reactor Model to Assess the Impact of Nuclear Data

The SCALE code system was employed to conduct a preliminary investigation of nuclear data impacts for a fast spectrum molten chloride salt reactor. A computationally effective depletion model that is representative of the reactor system was successfully developed and used to conduct fuel depletion simulations. Development of this model draws from the SLICE method that was developed at Oak Ridge National Laboratory to enable generation of fuel compositions for an advanced reactor core at equilibrium operation. Eigenvalue uncertainty calculations using the ENDF/B-VII.1 nuclear data library were performed for the reactor in the fresh fuel state and an irradiated fuel state. It was determined that the primary driver of eigenvalue uncertainty was the uncertainty in the 235U (n, 𝛾) cross section. Uncertainty calculation results from this study were compared to results available for a different fast system, a sodium-cooled fast reactor, to confirm similarities and identify differences with respect to nuclear data impacts between the two fast advanced reactor systems.

Hirji, Rakim [Georgia Institute of Technology]↗