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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Embedded Aluminum Nitride Sensors for Advanced Reactors

This project aims to manipulate the of growth of aluminum nitride (AlN) inclusions in an iron-chromium-aluminum (FeCrAl) alloy, using the principle of powder metallurgy and heat treatment methods. to promote the formation of AlN phase within FeCrAl for embedded sensing. This effort seeks to fill in a gap with respect to robust sensor hardware for ubiquitous structural health monitoring of advanced nuclear reactors. A systematic evaluation of various solid-state methods will be performed to understand the influence of process conditions on AlN growth and to promote the growth of desirable AlN phase. Fabricated specimens will be analyzed to investigate the AlN structures that are formed using a suite of tools to characterize the concentration, morphology, and distribution of AlN within the FeCrAl substrate.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Surface Preparation of Additively Manufactured 316H Stainless Steel for Molten Salt Applications

Additive manufacturing (AM) has the potential to revolutionize the manufacturing process and speed up deployment of advance nuclear reactors. However, more information is needed on preparing AM materials for extreme reactor environments to qualify AM materials for nuclear applications. This project studies the surface preparation of AM 316H stainless steel using acid pickling and reports a successful procedure for descaling heat-treated AM material.

316H Stainless Steel↗
DOE OSTI2025

Phenomena Identification and Ranking Table (PIRT) for Heat Pipes

This Phenomena Identification and Ranking Table (PIRT) report provides an evaluation of key phenomena affecting the performance and operational regimes of heat pipes, particularly in the context of heat pipe microreactors (HPMRs). Heat pipes are advanced passive thermal management devices that utilize phase change and capillary action to achieve efficient heat transfer. However, due to the complexity of the phenomena coupled in the heat pipe, including phase change, turbulent transition, and compressibility effects, among others, there is high uncertainty in identifying and ranking the important phenomena affecting the operation of heat pipes and the current knowledge for their modeling and simulation and experimental measurements and instrumentation. This PIRT exercise, conducted as a collaborative effort involving the Department of Energy (DOE) Microreactor Program (MRP), the Nuclear Regulatory Commission (NRC), and university partners systematically identifies, reviews, and prioritizes critical phenomena affecting the operation of heat pipes based on their importance and knowledge levels. The report analyzes phenomena with high importance and low knowledge, such as wick de-wetting, critical heat flux, contact angles, and pressure dynamics, discussing challenges and future research directions for improving their modeling and simulation and experimental measurements. Additionally, the report addresses phenomena with low knowledge that could impact heat pipe operation during non-normal or transient operation, including frozen startup, laminar to turbulent transition, geysering, wick priming, underfilling conditions, surface roughness of the wick, NCGs trapped in the wick, and the timescales of startup and shutdown. This comprehensive evaluation serves as a valuable resource for guiding future research and development efforts, supporting the successful integration of heat pipes into critical applications such as nuclear reactors, and contributing to the advancement of heat pipe technologies in safety-critical industries.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2024

Environmentally Assisted Fatigue in Light Water Reactor Environment

This report summarizes the Environmentally Assisted Fatigue (EAF) research conducted at ANL under the US DOE Light Water Reactor Sustainability (LWRS) program. Starting from a rich background in theoretical and experimental EAF, ANL previously developed an approach to evaluate fatigue performance of reactor materials in light water reactor environments with the correction factor F en . The approach was based on a large body of experimental work performed at ANL and elsewhere, and was consistent with American Society of Mechanical Engineers (ASME)’s methodology governing the design and construction of reactor components. In recent years, the program was focused on component fatigue prediction and made several major and fundamental contributions in this area. These accomplishments help meet the needs identified by the industry concerning component level fatigue predictions in complex, transient conditions. The main contribution of the ANL program involved the development of a system-level model for estimating residual strain and life of nuclear reactor coolant system components under connected-system-thermal-mechanical boundary conditions. The goal was to predict the stress hotspots, strain residuals, strain amplitudes and the resulting fatigue lives. Thermal-mechanical stress analysis was performed considering thermal stratification and a design-basis reactor loading cycle. Based on the finite element (FE) model results, the strain residuals, strain amplitudes and resulting fatigue lives of reactor coolant system (RCS) components were predicted. The results show that some of the RCS components can have significantly different strain amplitudes, residual strain, and fatigue lives, despite having similar geometry and material. In addition, the simulated component-level strain profile can guide the selection of appropriate test inputs for conducting laboratory-scale EAF tests. Building upon the system-level model, ANL developed a digital twin (DT) framework to predict the structural states and associated fatigue life of components in real-time. This framework is a comprehensive system designed to predict the structural states and fatigue lives of reactor components. It includes multiple models and integrates artificial intelligence (AI), machine learning (ML), and FE based modeling tools to evaluate the structural states and fatigue lives.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Multi-physics Modeling of Radiative Heat Transfer and Fluid Flow for the Reactor Cavity Cooling System

High-temperature gas-cooled reactors (HTGRs) are notable for their high thermal efficiency and potential for combined heat and power applications. These reactors are particularly appealing due to their advanced passive safety features. HTGRs utilize passive safety systems that function without requiring active components like pumps or compressors during emergencies. These reactor designs depend on a Reactor Cavity Cooling System (RCCS) to manage decay heat removal from the reactor pressure vessel (RPV) during accident conditions. The RCCS consists of vertical rectangular channels known as "risers" or riser ducts positioned around the RPV. These risers receive heat from the RPV through both convective and radiative heat transfer mechanisms. Understanding the interplay of multiple physical phenomena, such as fluid dynamics, heat transfer, and neutron interactions, is essential for the effective design and operation of nuclear reactors, particularly for systems like the RCCS. Multi-physics simulations provide a comprehensive approach to studying these interactions, offering detailed insights and enhancing accuracy. They are especially important in RCCS designs, where the interaction between radiative and convective heat transfer can significantly impact system performance. By leveraging multi-physics simulations, complex reactor behaviors can be modeled without compromising the fidelity of the underlying physical processes. This work aims to establish a robust methodology for coupling multiple physical processes in an air-cooled RCCS. By focusing on validating this multi-physics approach, the study involves designing test cases that simulate various conditions to verify the numerical models employed. The outcomes of this research will provide critical insights for accurately modeling and optimizing complex nuclear systems like the RCCS.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Bayesian Optimization for Reactor Design Optimization

This study present a test case in which the Bayesian Optimization method is applied to a simulation-based reactor core design optimization problem. The test case aims to showcase the potential of an automated design optimization algorithm for reactor designs by streamlining the reactor core design workflow, given the high computational cost of simulations. The contributions of this work are threefold. First, the existing HTGR model is converted into a simulation-based design optimization test case by developing a pipeline that enables modification of key design parameters and evaluates design performance based on simulation outputs. Second, Bayesian Optimization is implemented and adapted to demonstrate the feasibility of automatic design optimization for nuclear reactor core. Proposed approach leverages Gaussian Process models to characterize the relationship between design variables and performance metrics, while incorporating novel acquisition functions that balance exploration of the design space with exploitation of promising configurations. This implementation lays the foundation for the future developments of reactor design optimization algorithms.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Laser-spectroscopy testbed for impurity monitoring in liquid metal-cooled fast reactors

A significant challenge in sodium-cooled fast reactors is controlling impurities, in particular oxygen impurities, within the sodium coolant, as they can accelerate corrosion and indicate leaks. Optical methods offer the potential to rapidly detect small concentrations of both gaseous and metal impurities that accelerate corrosion, plug coolant channels, and lead to increased activation of isotopes in the coolant. We present the design and performance of an apparatus designed to enable the application of multiple optical analytical techniques, such as laser-induced breakdown spectroscopy, to detect elemental impurities in the sodium melt with high sensitivity. Here, we experimentally demonstrate the detection of characteristic sodium and oxygen spectral lines in liquid sodium, which sets the stage for the optimization of its analytical sensitivity. A robust sensor of this type integrated with the sodium cooling loop has the potential to significantly improve the safety and operational efficiency of generation IV nuclear reactors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

A Study of the Transition to Turbulence in a Bed of 67 Spherical Pebbles

Packed beds are commonly found in many engineering systems and have been widely studied for decades. A relatively new packed bed system is the Pebble Bed Reactor, a type of generation-IV nuclear reactor. Unlike many of the packed beds encountered in chemical and process engineering applications, Pebble Bed Reactors are larger and operate at significantly higher Reynolds numbers. As a result of these differences, there is a very limited amount of information on the detailed flow physics that exist in these complex geometries. This work seeks to contribute to a growing database of flow data for Pebble Bed Reactor systems by performing Direct Numerical Simulations of the flow in an experimental bed of 67 pebbles for a range of conditions. Simulations are performed at a Prandtl number of 0.66 and Reynolds numbers from 300–600. These Reynolds numbers are chosen to gain additional knowledge on the spatial development of turbulence in these systems. Analysis of the Turbulent Kinetic Energy, turbulence anisotropy, and Turbulent Heat Flux is performed. Results demonstrate significant development of the TKE across the tested range of Reynolds numbers. Examination of both the TKE and THF reveal that development first occurs near the center of the bed and propagates radially as the flow moves further into the bed. Notable regions of negative production of turbulent kinetic energy are observed in regions where flow accelerates around pebble contact points. Furthermore, these regions are found to coincide with regions of 1-component turbulence.Kindly check and confirm, all authors email id is correctly identified.These are correct

Direct numberical simulation↗
DOE OSTI2024

Annual Report on NCSP Technical Support task in BNL during FY24

This work reports on the investigations done during FY 24 in collaboration with two 2024 Summer undergraduate interns through the DOE SULI and BNL SURP programs. These efforts were partially funded by the Nuclear Criticality Safety Program through the Technical Support Succession Plan task. The first project, developed by Ian Snider, focused on testing the impact of uncertainties in thermal cross sections for multiple materials in nuclear reactor simulations. The second project aimed implement concurrent into BNL’s machine-learning code to correct spin mis-assignments in neutron resonances, the Bayesian Resonance Reclassifier (BRR).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2008

Flow Components in a NaK Test Loop Designed to Simulate Conditions in a Nuclear Surface Power Reactor

A test loop using NaK as the working fluid is presently in use to study material compatibility effects on various components that comprise a possible nuclear reactor design for use on the lunar surface. A DC electromagnetic (EM) pump has been designed and implemented as a means of actively controlling the NaK flow rate through the system and an EM flow sensor is employed to monitor the developed flow rate. These components allow for the matching of the flow rate conditions in test loops with those that would be found in a full-scale surface-power reactor. The design and operating characteristics of the EM pump and flow sensor are presented. In the EM pump, current is applied to a set of electrodes to produce a Lorentz body force in the fluid. A measurement of the induced voltage (back-EMF) in the flow sensor provides the means of monitoring flow rate. Both components are compact, employing high magnetic field strength neodymium magnets thermally coupled to a water-cooled housing. A vacuum gap limits the heat transferred from the high temperature NaK tube to the magnets and a magnetically-permeable material completes the magnetic circuit. The pump is designed to produce a pressure rise of 5 psi, and the flow sensor's predicted output is roughly 20 mV at the loop's nominal flow rate of 0.5 GPM.

Polzin, Kurt A.↗
NASA NTRS2007

Liquid Metal Pump Technologies for Nuclear Surface Power

Multiple liquid metal pump options are reviewed for the purpose of determining the technologies that are best suited for inclusion in a nuclear reactor thermal simulator intended to test prototypical space nuclear system components. Conduction, induction, and thermoelectric electromagnetic pumps are evaluated based on their performance characteristics and the technical issues associated incorporation into a reactor system. The thermoelectric electromagnetic pump is recommended for inclusion in the present system based on favorable quantitative and qualitative measures relative to the other options under consideration.

Polzin, Kurt A.↗
NASA NTRS2007

Liquid-Metal Pump Technologies for Nuclear Surface Power

Multiple liquid-metal pump options are reviewed for the purpose of determining the technologies that are best suited for inclusion in a nuclear reactor thermal simulator intended to test prototypical space nuclear system components. Conduction, induction, and thermoelectric electromagnetic pumps are evaluated based on their performance characteristics and the technical issues associated with incorporation into a reactor system. The thermoelectric pump is recommended for inclusion in the planned system at NASA MSFC based on its relative simplicity, low power supply mass penalty, flight heritage, and the promise of increased pump efficiency over earlier flight pump designs through the use of skutterudite thermoelectric elements.

Polzin, K. A.↗
NASA NTRS2007

Liquid Metal Pump Technologies for Nuclear Surface Power

Multiple liquid metal pump options are reviewed for the purpose of determining the technologies that are best suited for inclusion in a nuclear reactor thermal simulator intended to rest prototypical space nuclear surface power system components. Conduction, induction and thermoelectric electromagnetic pumps are evaluated based on their performance characteristics and the technical issues associated with incorporation into a reactor system. A thermoelectric electromagnetic pump is selected as the best option for use in NASA-MSFC's Fission Surface Power-Primary Test Circuit reactor simulator based on its relative simplicity, low power supply mass penalty, flight heritage, and the promise of increased pump efficiency over those earlier pump designs through the use of skutterudite thermoelectric elements.

Polzin, Kurt A.↗
DOE OSTI2025

Feasibility Assessment of Using Electrical Impedance Tomography for Damage Localization in Graphite Microreactor Components

Microreactors have great potential to decrease capital costs and construction timelines, reducing the barriers to implementing advanced nuclear reactor technologies. However, the lower power output of these microreactors introduces economic challenges if the operation and maintenance costs cannot be reduced sufficiently. Many microreactor concepts use graphite materials for in-core moderator and structural purposes, which will require periodic inspection or, ideally, in situ structural health monitoring. This work describes an initial evaluation of the feasibility of leveraging graphite’s semiconducting properties to perform electrical impedance tomography (EIT) for defect localization. First, a study was performed to identify the best methods for bonding electrical contacts to minimize the effects of contact resistance that interfere with impedance measurements of the graphite. After determining the best bonding approach, electrodes were attached to multiple graphite components with varying geometries (e.g., simple block and more representative microreactor hexagonal block). In parallel, finite element analysis approaches were developed and implemented to analyze the impact of defects and contact resistances and to inform an iterative inverse model for reconstructing the conductivity distribution. The results of this study show that defect localization in graphite components is possible using EIT if a sufficient number of electrodes (to improve spatial resolution) can be bonded using a technique with very low contact resistance and those contact resistances remain stable during reactor operation. If the reactor core and vessel design do not allow electrodes to be bonded during reactor operation, then it may be possible to detach/reattach electrodes between reactor operation and outages if a suitable mechanical connection that offers repeatable contact resistance can be identified. Alternatively, future work could focus on identifying contacts that can survive the harsh reactor operating environment so that contacts do not need to be removed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Deployment of Traditional and Hybrid Machine Learning for Critical Heat Flux Prediction in the CTF Thermal-Hydraulics Code

Critical heat flux (CHF) marks the transition from nucleate to film boiling, where heat transfer to the working fluid can rapidly deteriorate. Accurate CHF prediction is essential for efficiency, safety, and preventing equipment damage, particularly in nuclear reactors. Although widely used, empirical correlations frequently exhibit discrepancies when compared to experimental data, limiting their reliability in diverse operational conditions. Traditional machine learning (ML) approaches have demonstrated potential for CHF prediction but often suffer from limited interpretability, data scarcity, and insufficient knowledge of physical principles. Hybrid model approaches, which combine data-driven ML with base models, mitigate these concerns by incorporating prior knowledge of the domain. This study integrates an externally trained purely data-driven ML model and two hybrid models (using the Biasi and Bowring CHF correlations) within the CTF subchannel code via a custom Fortran framework. Performance was evaluated using two validation cases: a subset of the Nuclear Regulatory Commission (NRC) CHF database and the Bennett dryout experiments. In both cases, the hybrid models demonstrated significantly lower error metrics compared to conventional empirical correlations, with the best models often reducing relative error by about 5 percentage points. The pure ML model achieved comparable accuracy, outperforming the hybrid Biasi model in the NRC test case (3.3% versus 5.5% relative error) but exhibiting slightly higher error against the hybrid Bowring model in the Bennett test case (7.7% versus 6.1%). Trend analysis of error parity indicated that ML-based models reduced the tendency for CHF overprediction, improving overall accuracy. These results demonstrate that ML-based CHF models can be effectively integrated into subchannel codes and could potentially increase performance compared to conventional methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Using Generative AI to implement the discrepancy checker for a Nearly Autonomous Management and Control System for Advanced Reactors

Developments related to generative artificial intelligence (AI) have brought a major breakthrough in AI. These developments are rapidly accelerating developments in different science and engineering applications. Nearly Autonomous Management and Control (NAMAC) system provides recommendations to the operator for maintaining the safety and performance of the reactor. The discrepancy checker (DC) is an important component of the NAMAC) system, whose goal is to determine if the plant is moving towards the expected system state after the control actions are injected. In this work, we explore generative AI methods, particularly, a generative pretrained transformer (GPT) for implementing the DC function in NAMAC. The GPT-based DC aims to alert the operator in situations outside NAMAC’s scope and act as a chatbot the operator can use to retrieve relevant information. This study involves two versions of GPT developed by OpenAI: GPT-3.5 and GPT-4. These GPTs are trained on huge amounts of undisclosed general domain datasets. We explored two methods to adapt GPTs for DC implementation in NAMAC: fine-tuning and retrieval augmented generation. A small knowledge base (information file) that encompasses rules for DC implementation and some general information related to NAMAC has been created to support DC implementation using GPT. In this work, the GPT-based DC implementations have been tested for their reasoning abilities, comprehension, information retrieval, and extraction abilities. It should be noted that this paper only presents a preliminary study to test the feasibility of DC implementation using generative AI technology. Given the potential risks and severe consequences associated with nuclear reactor applications, combined with the black-box nature of AI, extensive offline and online testing and reliability analyses of GPT-based DCs are needed for further developing such capabilities.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

The Impact of Europium as a Fission Product Surrogate on Chromium Corrosion in Molten Chloride Salt

The rising interest in molten salts, both as thermal energy storage media and as high-temperature solvents for fissile materials in advanced nuclear reactors, has spurred significant growth in research on structural and functional salt-facing materials. Impurities, such as water, play a significant role in the degradation of materials in molten salt environments. Other impurities, such as fission products, are expected to accumulate in molten salts during normal reactor operation and can affect the properties of the salt and salt-facing materials. During normal reactor operation, rare-earth element species are expected to form as byproducts of fission reactions, potentially degrading or altering the performance of both structural and functional materials exposed to salts. Here, in this work, fission product surrogates, europium metal and EuCl 3 , were added to the KCl-MgCl 2 salt while exposing pure Cr specimens in the melt at 600 and 700 °C for 1000 h. Low reactivity was observed with the baseline salt, while both the Eu and EuCl 3 additions to the salt resulted in increased mass loss of Cr specimens. A capillary electrophoresis technique was developed to enable the detection of low parts-per-million (ppm) concentrations of europium (Eu) in chloride salt both before and after exposure of Cr metal. This technique provides a sensitive and reliable method for monitoring trace levels of Eu, which is critical for understanding the interactions and potential contamination effects in salt-facing materials during reactor operation. This quantification technique can be applied to other cationic and anionic contaminants in halide salts.

chloride salt↗