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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Decoding Early Candidacy of High Entropy Alloys for Nuclear Application using the Advanced Test Reactor through Predictive Methods and Combinatorial Testing

High Entropy Alloys (HEAs) are identified candidates for nuclear applications owing to their superb mechanical and thermal properties. In line with evaluating their candidacy, a challenge remains in their validity as structural replacements for extreme environments. Each compositional graded specimen consists up to four different compositions spanning the fueled zone for non-prototypical neutron irradiation testing in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). We have fabricated a set of four compositionally graded specimens using spark plasma sintering that include at least five of the following elements: Cr, C, Al, Zr, Mo, Nb, Ta, V, Ti, W, and Fe. In time for this meeting the role of temperature expected to play a role in-pile cladding chemical interactions (FCCI), mechanical interactions (FCMI), irradiation damage, creep, and resistance will be reported. The irradiated portion has a scheduled irradiation date in April 2020 and with post irradiation examination (PIE) to follow.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1968

Early nuclear rocket applications.

Nuclear rocket applications, discussing performance, lunar logistics, solar system missions, orbital operations and payload data

Johnson, P. G.↗
DOE OSTI2020

Characterization of Urbix Resources Natural Flake Graphite Material for Nuclear Applications (CRADA NFE-18-07340 Final Report)

Urbix Resources is a company specializing in graphite powder processing and purification. Urbix is looking to become the first domestic supplier of nuclear-grade graphite in the United States. This has led to a Cooperative Research and Development Agreement (CRADA) being established between the Oak Ridge National Laboratory (ORNL) and Urbix Resources, with the goal of characterizing a purified graphite feedstock supplied by Urbix Resources. The resulting data will then be used to determine the viability of a large-scale nuclear graphite production and qualification campaign. These characterization methods have been performed on the as-received graphite feedstock, a heat-treated batch of the feedstock, a milled batch of the feedstock, and a nuclear-grade graphite powder historically used in fuel production. The data from the heat-treated and milled feedstock will determine how different processing methods affect the powder’s physical properties, whereas the data from the nuclear grade graphite will provide information about the characteristics of a graphite previously accepted for nuclear applications. All of these powders have been characterized individually and as part of a resin-graphite blend (herein referred to as matrix) that has been used in past fuel experiments. The results of these experiments show that the Urbix powder and nuclear-grade graphite powder display notably different properties from one another in many cases, but this discrepancy may have been the result of the typical particle size of each powder. This hypothesis is supported by tests conducted on the milled powder, which showed a closer resemblance in properties to the nuclear-grade graphite than the as-received powder. The method for pressing the graphite matrix also had a noticeable effect on the measured properties.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Machine Vision-based Robot Manipulators for Nuclear Applications - 20370

Decommissioning and dismantling of nuclear facilities are major challenges facing the nuclear industry. Robot manipulators with capabilities of restoring nuclear structures and significantly prolonging nuclear power generation in addition to their applications in decommissioning and dismantling (D and D) would immensely ease the above-mentioned challenge. Ability to remotely sense/monitor and analyze dangerous and hazardous environments such as nuclear reactors as well as performing reparatory tasks in such environments using robot manipulators require additional information from vision sensors. Structural sample collection and inspection as well as restoration require object and position information. Computer vision is used to obtain precise 3D position information. The current work uses the Sawyer robot with the integrated Cognex camera. The research presents an approach to facilitate and improve operations in a nuclear reactor using robotic vision control. The vision control system is modeled with Augmented Image Space-based visual servoing approach. Results showing accurate robot control. Object recognition is used to recognize the image and calculate it poses. To transform coordinates of the object's pose from the camera frame to the robotic frame transformation matrices are employed. Future work will employ a 3D camera (with depth information) using Denso robot. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Design considerations for high entropy alloys in advanced nuclear applications

The demanding operating environments of advanced nuclear reactors require the development of new nuclear materials that can withstand their increased physical, chemical, thermal, and radiation-related challenges. High-entropy alloys (HEAs) have shown often-impressive mechanical, thermomechanical, and corrosion-resistant properties, and offer a massive, unexplored compositional space which allows for the targeted development of application-specific materials. Furthermore, although still in a nascent stage, research has shown that HEAs may exhibit unique irradiation tolerance, including reduced defect production and resistance to irradiation-induced swelling and hardening. The mechanisms behind this increased tolerance are not yet well-understood, although the HEA-specific attributes of a complex energy landscape, reduced thermal conductivity, and shift in defect migration energies and pathways provide promising explanations. Here this work assesses the current and future challenges faced by structural nuclear materials, identifying the specific applications in which HEAs may provide a competitive advantage compared to industry-standard materials with the aid of Ashby material selection maps. Considerations are provided for the design of future nuclear HEAs, including calculations of nuclear-relevant properties to assist in the initial down-selection of elements depending on application requirements (e.g., low neutron capture for in-core applications), narrowing the existing compositional space of HEAs to a manageable scope.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Statistical and Neural Network for Real Sensor-Data-Driven Anomaly Detection in Nuclear Applications

Anomaly detection (AD) in sensor data is critical to ensure uninterrupted functionality of nuclear power plants (NPPs). Consequently, AD model validation through real-world sensor data is important for applications in nuclear facilities. In this paper, we propose an Autoencoder (AE)—a multi-layered neural network, for AD in sensor data from an operational NPP testbed. Since the dataset lacks labels for irregularities, we introduce random noise and label them to effectively train our model. The proposed AE model assigns a higher reconstruction error to the abnormal samples that deviate from those encountered during the training phase and uses the reconstruction loss to detect anomalies in a representative imbalanced dataset. We also introduce an analytical solution—seasonal trend decomposition (STD)—as another AD scheme for identifying irregularities withinthe same time-series dataset. In contrast to the AE model which relies on reconstruction loss, the STD scheme decomposes the entire dataset into its trend, seasonality, and residual components to pinpoint irregularities. Our findings indicate that the proposed AE and STD models individually achieve recall scores of 97% and 92%, respectively. We validate the performance of the two models on both balanced and imbalanced data. We further solidify the results by picking the combined selected anomalies of the two solutions with an "AND" operator for more reliable predictions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Statistical and Neural Network for Real Sensor-Data-Driven Anomaly Detection in Nuclear Applications

Anomaly detection (AD) in sensor data is critical to ensure uninterrupted functionality of nuclear power plants (NPPs). Consequently, validation of AD models through real-world sensor data is important for their application in nuclear facilities. In this paper, we propose an Autoencoder (AE)— a multi-layered neural network, for AD in sensor data from an operational NPP testbed. Since the dataset lacks labels for irregularities, we introduce random noise and label them to effectively train our model. The proposed AE model assigns a higher reconstruction error to the abnormal samples that deviate from those encountered during the training phase and uses the reconstruction loss to detect anomalies in a representative imbalanced dataset. We also introduce an analytical solution—seasonal trend decomposition (STD) — as another AD scheme for identifying irregularities within the same time-series dataset. In contrast to the AE model which relies on reconstruction loss, the STD scheme decomposes the entire dataset into its trend, seasonality, and residual components to pinpoint irregularities. Our findings indicate that the proposed AE and STD models individually achieve recall scores of 97% and 92%, respectively. We also validate the performance of the two models on both balanced and imbalanced data. We further solidify the results by picking the combined selected anomalies of the two solutions with an "AND" operator for more reliable predictions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Technical Challenges and Gaps in Integration of Advanced Sensors, Instrumentation, and Communication Technologies with Digital Twins for Nuclear Application

This paper explores integrating advanced sensor, instrumentation, and communication technologies with digital twin technologies for nuclear energy application. Digital twins and digital-twin-enabling technologies are expected to integrate with future nuclear reactor designs and have the potential to impact currently operating nuclear power plants. Greater digital integration, advanced instrumentation and control systems, and advanced operations and maintenance practices are all associated with digital-twin-enabling technologies. Advanced sensors, instrumentation, and communication technology are expected to comprise important elements of the infrastructure required to develop and operate a nuclear digital twin system. This paper identifies and discusses challenges and gaps in developing and implementing advanced sensors and instrumentation and communication technology to be integrated with a digital twin in current and advanced reactor applications. It is important to address some challenge and gap to enable a successful near-term deploying advanced sensors, instrumentation, and communication technologies integrated with digital twins.

Yadav, Vaibhav↗
DOE OSTI2020

Thermal Process Technology for Nuclear Applications - 20379

ANSTO's Synroc technology has been developed to provide a safe, secure matrix for the immobilization and final disposal of radioactive waste. Synroc technology will be used to manage radioactive wastes from the production of the radioisotope Molybdenum-99 (Mo-99). This paper shall outline various stages of the process development with specific reference to the thermal treatment technology of calcination. Calcination is a key step in the Synroc process [1-2].The rotary thermal processing system includes: an advanced heating element design for increased robustness and ease of remote operation and maintenance, an enhanced modular design of components for ease of remote maintenance in a hot cell and in compliance with hot cell radioactive environment requirements for safety, reliability and maintainability. In addition to thermal treatment of waste from nuclear medicine production, this technology provides solutions for a variety of nuclear materials processing applications including sintering UO{sub 2} pellets for reactor fuel rods, oxidation of UO{sub 2} pellets, swarf, and powder to U{sub 3}O{sub 8}, de-nitration of Uranyl nitrate and hydrofluorination of UO{sub 2} pellets. The paper will also discuss thermal processing solutions for a range of nuclear applications. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

International database of reference gamma spectra for nuclear safeguards applications

Nuclear safeguards missions use gamma spectroscopy as a non-destructive measurement technique for examining nuclear materials. Despite advances in the development of detection equipment as well as software codes, one of the concerns is the lack of well-documented spectra needed to test and validate isotopic analysis codes for their applicability. To address this need, this work introduces IDB, an international database of the reference gamma spectra of uranium, plutonium and mixed oxide nuclear material samples. IDB provides access to well-characterized sets of gamma spectra described by rich metadata, including information on the sample, measurement configuration and detector specifications. These spectra are accessible in different formats, also compatible with analysis code standards, thus promoting their sustainability and maintenance.

None, Dipti [International Atomic Energy Agency (I↗
DOE OSTI2020

Modeling Nondestructive Defect Detection in Additively Manufactured Metallic Structures for Nuclear Applications

The future of quickly, economically produced metallic nuclear reactor parts with minimal supply-chain dependence lies in Laser Powder Bed Fusion (LPBF) Additive Manufacturing (AM): a 3D printing method involving laser melting and net shaping stainless steel and Inconel metallic powder into a solid structure. However, intrinsic features in LPBF frequently leads to the formation of materials defects, such as pores, within 3D printed structures. As safe long-term use in energy applications requires knowledge of all relevant defects before deployment in a reactor, we must develop methods for nondestructive detection of these defects. We are investigating Pulsed Thermal Tomography (PTT), which is a non-contact nondestructive imaging method scalable to arbitrary structure size. Thermal tomography (TT) is a computational method for 3D spatial reconstruction of material thermal effusivity from flash or pulsed thermography temperature data cube. Thermography data cube consists of 2D surface temperature measurements at different times. The objective of the present work is to investigate limits on defect detection in AM metallic structures with PTT. To this effect, we modeled PTT with COMSOL heat transfer computer simulations. We developed a layered media COMSOL simulation consisting of a Stainless Steel 316 (SS316) plate with an internal layer of un-sintered SS316 powder. Thermophysical properties of the powder layer were modeled with equivalent volume mixing model. To account for partial sintering at the boundary of the defect, the transition between solid and powder layers was modeled as a Gaussian. Using data from COMSOL simulations, we reconstructed depth-dependent thermal effusivity, which allowed defect visibility estimation. A series of parametric studies determined that at 1mm depth, 50µm is the smallest detectable defect. In addition, classification of the defects which can lead to early fatigue of the metallic structure in a reactor is briefly discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Progress on Design and Production of Oxide Dispersion–Strengthened Alumina-Forming Austenitic Alloys for Nuclear Applications

Alumina-forming austenitic (AFA) alloys are a promising class of nuclear materials due to their high-temperature oxidation/corrosion resistance and mechanical properties. Unfortunately, these alloys are limited in use for core material applications, specifically in their use as nuclear fuel cladding. Improving these alloys through a fine dispersion of oxide precipitates and thus increasing the effective irradiation sink strength of the alloy system may mitigate many of the degradation phenomena expected during alloy deployment (such as high-temperature helium embrittlement for lead-cooled fast reactor applications). This work package has started using a combination of conventional and advanced manufacturing approaches to the fabrication of oxide dispersion–strengthened (ODS) AFA materials. As such, this report summarizes progress to date in the fabrication of new compositions of these ODS AFA materials with a focus on reactor-specific design and a multifaceted manufacturing approach. Two different compositions of AFA gas-atomized powders were procured, and 200 g of each have been prepared using mechanical alloying with the expectation of high-temperature consolidation in Q1 of FY24. In addition, an approach to use reactive cover gases to promote additional precipitate formation has been developed for implementation in FY24 as a direct comparison with conventionally manufactured alloys.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Nondestructive Evaluation of Concrete within Nuclear Applications

Structural defects that develop over the lifetime of nuclear power plants (NPPs) could threaten the safety and security of the concrete infrastructure. Developing a reliable nondestructive evaluation (NDE) method to evaluate the damage in NPPs and their associated structures will greatly improve the long-term operation and safety of NPPs. The purpose of the US Department of Energy Office of Nuclear Energy’s Light Water Reactor Sustainability program is to develop technologies and other solutions that can improve the reliability, sustain the safety, and extend the operating lifetimes of NPPs beyond 60 years. This report describes the progress made toward growing NDE capabilities for NPPs. It also documents expanded collaborations with the Electric Power Research Institute (EPRI) and future opportunities to collaborate with industry partners (i.e., vendors and utilities) and university partners. These collaborations will continue to stand as a framework to provide value to stakeholders by reducing uncertainties and potential delayed maintenance costs in NPPs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Laser Powder Directed Energy Deposition of Steels for Nuclear Applications

This comprehensive investigation examines the structure–property relationships in two nuclear alloy systems—Alloy 709 (A709) austenitic stainless steel and Grade 92 (G-92) ferritic/martensitic (F/M) steel—manufactured via directed energy deposition (DED) for sodium-cooled fast reactor applications. This study establishes the fundamental mechanisms for controlling microstructures for optimizing the mechanical performance of additively manufactured nuclear materials through systematic heat treatment optimization and multiscale characterization. As-deposited A709 steel develops a complex multiscale strengthening architecture consisting of a fine cellular solidification structure with diameter of 2-3 µm within10–50 µm grains, elevated dislocation densities from rapid thermal cycling, and grain boundary precipitates that activate concurrent Hall–Petch, dislocation, and precipitation hardening mechanisms to achieve exceptional properties [yield strength (YS): 603 MPa, ultimate tensile strength (UTS): 844 MPa, Vickers hardness: 220 HV] that achieve a 44% superior strength compared to that of the wrought material. Heat treatments produce different results. Solution annealing (SA) dissolves the cellular structure and reduces the hardness to 190 HV. Precipitation treatment (PT) keeps the cellular structure but adds carbides, allowing the hardness to reach 205 HV. The best approach combines both treatments (SA+PT) and creates uniform precipitate distributions with M 23 C 6 carbides at the grain boundaries and MX carbonitrides in the matrix, achieving a hardness of 195 HV. However, directional differences persist, with a 12%–15% strength variation between orientations due to the inherited layered microstructural architecture that survives aggressive heat treatment. While tensile testing at 550°C demonstrates 40%–50% thermal softening with dynamic strain aging, DED A709 steel still maintains a 71% higher YS than that of the wrought material. Ion irradiation studies (100–400 dpa) of DED A709 steel reveal progressive radiation damage with increasing void density and radiation-induced segregation causing nickel enrichment and chromium depletion, which will ultimately compromise mechanical properties. As-deposited G-92 exhibits exceptional strength (UTS: 1650–1700 MPa, 430 HV) through a complex microstructure containing both ferrite and martensite phases, a high geometrically necessary dislocation (GND) density (17.04×10 14 /m 2 ), and fine carbides. Heat treatments create distinct changes. Normalizing produces fresh martensite with the highest hardness (460 HV) and an increased GND density (20.23×10 14 /m 2 ). Tempering develops dual precipitation systems and reduces the hardness to 290 HV. The optimal approach uses sequential normalizing plus tempering, achieving balanced properties with the lowest hardness (250 HV) and a reduced GND density (11.01×10 14 /m 2 ). A processing-dependent anisotropy is observed: horizontal specimens achieve superior ductile behavior, while vertical specimens exhibit brittle failure. A tempering heat treatment successfully mitigates this anisotropic behavior by transforming the hard martensitic as-deposited structure into tempered martensite enabling both horizontal and vertical specimens to exhibit similar stress–strain characteristics with visible necking behavior. Remarkably, testing at 550°C reveals a reversal in the anisotropy, where as-deposited specimens achieve near isotropy with superior thermal stability (a 15%–20% strength reduction), while tempered specimens develop an orientation dependence with a 25%–30% strength reduction. Both alloy systems demonstrate that DED processing creates specimens with a superior strength through refined microstructural features, though with distinct strengthening mechanisms—austenitic through cellular structures and precipitates versus F/M through phase transformations and precipitates. Heat treatment optimization requires alloy-specific approaches, with A709 benefiting from controlled precipitation while G-92 requires careful phase transformation control. The results show that DED manufacturing can produce nuclear materials with exceptional performance, but directional effects and temperature-dependent behavior must be carefully considered for reactor component design and qualification.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Creep Property of Intermetallic Dispersive Steels for Nuclear Applications

To meet the materials performance demands of next-generation nuclear and high-temperature energy systems, a new class of intermetallic-dispersive steels (IDS) has been designed through integrated computational thermodynamics and alloy design strategies. The IDS alloys incorporate coherent L1₂ (γ′-Ni₃Al) nanoprecipitates within an Fe–Ni–Cr austenitic matrix, engineered to achieve both high temperature strength and thermodynamic stability while suppressing the formation of detrimental δ-Ni₃Nb and η-Ni₃Ti phases. Initial creep testing of Ti-IDS and TiTa-IDS alloys demonstrates rupture lives comparable to or exceeding those of Inconel 718 and ODS steels, despite being fabricated through conventional ingot metallurgy. Step-load creep tests identified a stress threshold near 300–350 MPa for the onset of tertiary creep, and in-situ neutron diffraction experiments on Ti-IDS revealed clear load partitioning between the matrix and γ′ precipitates: elastic strain is shared by both phases, while plastic strain localizes in the matrix. These results confirm that stable γ′–matrix interfaces play a dominant role in retarding dislocation motion and enhancing creep resistance. In FY26, the program will conduct repeat creep rupture testing of TiTa-IDS at 650 °C/400 MPa, initiate long-term rupture testing of TiNb-IDS, and perform TEM-based microstructural characterization to elucidate dislocation–precipitate interactions and microstructural stability. Collectively, these efforts will establish the mechanistic foundation for next-generation high-temperature structural materials based on the IDS concept.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Advanced Manufacturing Techniques and Compositions of High Entropy Alloys for Nuclear Applications

In line with the objectives of the Department of Energy, Office of Nuclear Energy, Advanced Materials and Manufacturing Technologies (AMMT) program, this work focuses on new materials development and qualification research and development for next-generation, high-temperature nuclear reactors. High entropy alloys (HEAs) have the potential to serve in these extreme environments of next-generation nuclear reactors because of their unique phase transformation pathways and nanoscale and mesoscale microstructures. The current work focuses on understanding such nuclear-energy-relevant HEAs through a detailed literature survey, selected experimental work, and developing a decision matrix with criteria for the identification of HEAs that may have the most impact and value for further examination.

36 MATERIALS SCIENCE↗