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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Development of process parameters and post-build conditions for qualification of LPBF 316 SS

To harness the potential of laser powder bed fusion (LPBF) 316H stainless steel (SS) for use in advanced nuclear reactors, extensive research efforts are needed to develop optimal laser processing parameters and appropriate heat treatments, taking into account various manufacturing platforms and locations. Furthermore, it is crucial to assess the material properties in environments relevant to reactor operating conditions. In collaboration with Oak Ridge National Laboratory (ORNL) and Los Alamos National Laboratory (LANL), Argonne National Laboratory (ANL) is dedicated to gaining insights into how the manufacturing process and post-build treatments impact the performance of LPBF 316H SS. This report provides an overview of ANL's research findings for FY23, focusing on LPBF 316H SS produced using a Renishaw AM400 laser system. Specifically, our research has concentrated on three key areas: 1) Optimum laser processing parameters: Leveraging the high-throughput printing technology, we systematically varied the laser power, exposure time and point distance within the same build. By measuring the as-printed porosity, we identified an optimum printing parameter window that produced materials with near-complete density; 2) Post-built treatment development: Materials printed with the optimum laser parameters underwent treatments including stress relief, solution annealing, and hot isostatic pressing. Subsequently, we fabricated tension, creep, and fatigue specimens from materials subjected to these different conditions. Over the next year, a series of scoping tests will be conducted to facilitate the selection of the most suitable post-build treatment condition; 3) Thermal aging effects on microstructure and properties: thermal aging at 550°C, 650°C and 750°C was conducted on LPBF 316H SS specimens up to 2500 h. Microstructural characterization was performed with electron microscopy, and the evolution of the dislocation cell structures and secondary phases was studied. Microhardness tests and tension tests were conducted to quantify changes in mechanical properties. The results revealed that the aged LPBF 316H SS exhibited a high density of Cr-rich and Mo-rich fine precipitates within grains due to the presence of a high density of dislocations and the globally distributed dislocation cell structures, which served as heterogeneous nucleation sites for secondary phases. Along grain boundaries, a Mo-Cr-rich phase, observed in 750°C-aged conditions, displayed significant thermal coarsening. Throughout the aging process, various mechanisms, including stress relaxation, dislocation cell structure recovery, solution hardening, and precipitation hardening, competed to influence materials strength. These results contribute towards establishing the technical basis for qualifying LPBF 316H SS for advanced nuclear reactor applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Simultaneous analysis of collinear neutron time-of-flight (nToF) traces applied to pulsed fusion experiment

On pulsed fusion experiments, the neutron time of flight (nToF) diagnostic provides critical information on the fusion neutron energy spectrum. This work presents an analysis technique that uses two collinear nToF detectors, potentially to measure nuclear bang time and directional flow velocities. Two collinear detectors may be sufficient to disambiguate the contributions of nuclear bang time and directional flow velocities to the first moment of the neutron energy spectrum, providing an independent measurement of nuclear bang time. In conclusion, preliminary results from measured nToF traces on the National Ignition Facility and additional applications of this technique are presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Survey of Additive Manufacturing Signatures for the Prevention of Nuclear Proliferation

Improvements in additive manufacturing technologies will enable multiple-material and advanced material capabilities, creating opportunities to improve and expand the nuclear fuel fabrication process. Additive manufacturing can allow fuel to have complex geometries and contain composites of materials that would otherwise be difficult or impossible to make with traditional manufacturing methods. This opportunity also has implications for nuclear proliferation, as nuclear parts may be printed and more easily acquired. Here, we present a survey of additive manufacturing technologies and relevant signatures that could be used to identify processes, materials, or part properties.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

Liquid lithium wetting and percolation in a porous tungsten/liquid Li plasma facing component (PFC)

This work explores the concept of a hybrid material system designed to protect the plasma from high-Z material emission while also protecting an underlying high-Z wall material from erosion by integrating a low-Z component in the liquid phase. Plasma-surface interaction properties of a porous tungsten (W)-liquid metal hybrid system, having the favorable bulk thermomechanical properties of W while serving as a scaffold for a liquid metal with self-healing and radiative vapor shielding characteristics, are examined. W-substrates with 70% density of bulk W and 1–5 μm sized pores have been fabricated with 50-nm W powders using spark plasma sintering. Enhanced lithium (Li) wettability, driven by percolation through the porous W architecture, is demonstrated with in-situ liquid Li drop measurements. Finally, results show complete wetting of liquid Li at 250 °C in the porous W, 100 °C lower temperature than what has been observed on traditional W surfaces. In operando ion beam analysis of Li films deposited on porous W substrates provides microscopic evidence of Li percolation into the substrate and a first look at D retention up to a depth of 100 nm after plasma exposure at a flux of 10 20 m –2 s –1 , 250 eV/amu D + plasma to a fluence of 1.16 × 10 23 m –2 at a temperature of 200 °C.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

ITER Toroidal Interferometer and Polarimeter (TIP) beam refraction in 3D density profiles

Calculations of the expected refraction of the five ITER Toroidal Interferometer and Polarimeter (TIP) chords are presented for a range of conditions including high-density axisymmetric, ELMing H-mode cases and shattered pellet disruption mitigation cases. The calculations are carried out with a newly developed ray tracing code capable of following TIP’s 10.59 μm laser beams through arbitrary 3D electron density profiles. Using JOREK simulations of ELM density perturbations in a 15MA ITER baseline plasma, it is shown that refraction from ELMs is expected to be negligible. It is found, however, that TIP interferometers will be able to clearly resolve the line-integrated density perturbation from ELMs and contribute to the ITER measurement requirement “14. H-mode, ELMs and L-H mode transition indicator”. Calculations of the expected refraction in a NIMROD simulated shattered pellet disruption mitigation scenario with peak local electron densities of n e = 3.7 x 10 21 m -3 (max line-averaged densities of n avg = 1.3 x 10 21 m -3 ) also show tolerable refraction and it is likely that most, if not all chords, would avoid signal loss. In conclusion, for both axisymmetric and structured plasmas with line-averaged densities in the mid to upper 10 21 m -3 range, values likely present only during disruption mitigation, refraction becomes significant and could limit the ability of TIP to make reliable density measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Under the microscope: Reduced activation ferritic martensitic steel Eurofer-97 following ion-Irradiation and high-temperature high-pressure water exposure

Here, this study is designed to characterise the microstructural behaviour of Eurofer-97 steel under ion irradiation and subsequent exposure to high-temperature high-pressure (HTHP) water. Eurofer-97, a ferritic-martensitic steel, has been developed to withstand the conditions of fusion reactors in the locations in contact with coolant with an elevated level of neutron flux, such as the breeder-wall blanket. The material has been studied after self-ion irradiation (using Fe ions) simulating the microstructural effects of neutron irradiation limited to the subsurface layer. The corrosion properties of the Eurofer-97 steel were studied by exposure to HTHP water up to 331 °C. Advanced microstructural characterisation using scanning, transmission electron and focused ion beam microscopy was performed on the as-received microstructure and after ion irradiation. This was then characterised after exposure for 240 h in high-temperature water. Eurofer-97 had a dense, columnar Cr-rich inner oxide, followed by a Fe-rich outer oxide layer. In the irradiated condition the grain structure and oxide itself was less ordered. No appreciable difference in oxide thickness was identified between the irradiated and unirradiated specimens after this short exposure time.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Strength stability at high temperatures for additively manufactured alumina forming austenitic alloy

Several fast-spectrum nuclear reactors designed to generate high power (~450 MWe) rely on forced convection of media such as supercritical CO 2 , sodium, or liquid lead to cool the nuclear core, operating at temperatures up to 600 °C. Cost-effective, high-strength Fe-based alumina forming austenitic (AFA) alloys are a promising candidate for the fabrication of critical nuclear components. This study investigated laser powder bed fusion (LPBF) processing of an AFA alloy composition optimized for improved creep resistance. Electron microscopy revealed an elongated grain structure along the build direction with a fine sub-grain cellular structure decorated with (Cr,Fe,Nb) 23 C 6 carbide precipitates at the intercellular boundaries. Finally, at temperatures of 20–900 °C, the LPBF alloy's superior tensile properties compared to its arc-melted counterpart and other advanced steels (e.g., SS316) were attributed to the distribution of nano-sized carbide precipitates, whereas the high ductility was attributed to the LPBF alloy's elongated grain structure.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hybrid particle-in-cell simulations of electromagnetic coupling and waves from streaming burst debris

Various systems can be modeled as a point-like explosion of ionized debris into a magnetized, collisionless background plasma-including astrophysical examples, active experiments in space, and laser-driven laboratory experiments. Debris streaming from the explosion parallel to the magnetic field may drive multiple resonant and non-resonant ion-ion beam instabilities, some of which can efficiently couple the debris energy to the background and may even support the formation of shocks. We present a large-scale hybrid (kinetic ions + fluid electrons) particle-in-cell simulation, extending hundreds of ion inertial lengths from a 3D explosion, that resolves these instabilities. We show that the character of these instabilities differs notably from the 1D equivalent by the presence of unique transverse structure. Additional 2D simulations explore how the debris beam length, width, density, and speed affect debris-background coupling, with implications for the generation of quasi-parallel shocks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

A Short-Lived Isotope Counting System (SLICS) to measure reaction cross sections producing light, beta-decaying nuclei on OMEGA

A new activation detector optimized for short-lived isotopes was designed, installed, and tested on OMEGA. The Short-Lived Isotope Counting System (SLICS) can be positioned as close as 35 cm from the OMEGA target chamber center in a ten-inch-manipulator. Stable target samples can be mounted on the front end of the detector assembly to undergo triton-, deuteron-, or neutron-induced reactions that produce short-lived reaction products that beta decay. The emitted betas are detected in a phoswich configuration to eliminate the gamma background. The detector is optimized for isotopes with half-lives from 150 ms to 20 s, filling a gap in OMEGA’s current activation detectors for isotopes with half-lives >5 min. In a pilot study, SLICS achieved an efficiency of 24.5% ± 2.0% for counting 8Li, with a total of 505.8 ± 4.4 qualifying events. Using the existing triton laser-ion acceleration platform on OMEGA, this detector can be used to measure rarely studied tritium-induced reactions on light nuclei with an estimated uncertainty of 12%. As a result, the design of the detector and its performance during a first experiment employing deuterium as a surrogate will be discussed.

Beta spectrometry↗
DOE OSTI2023

The Impact of Disruptions on the Economics of a Tokamak Power Plant

Tokamaks are often considered to be a leading candidate for near-term, cost-effective fusion energy, but these devices are susceptible to sudden loss of confinement events called disruptions. The threat of disruptions has garnered serious attention in research for the next generation of burning plasma experiments, such as ITER, but has received little treatment in economic studies of magnetic fusion energy. In this paper, we present a model for quantifying the effect of disruptions on the cost of electricity produced by a tokamak power plant (TPP). We outline the various ways disruptions increase costs and decrease revenues, introduce metrics to quantify these effects, and add them to a levelized cost of electricity (LCOE) model. Additionally, we identify several rate-limiting repair steps and introduce a classification system of disruption types based on the time to return to operations. We demonstrate how the LCOE model can be used to find the cost of electricity and the requirements for disruption handling of a TPP, and we further highlight where future research can have a strong impact in neutralizing the “showstopping” potential of disruptions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Data-Enabled Fusion Technology (Final Scientific/Technical Report)

Advancing Scientific Understanding in Fusion Energy and Machine Learning This research represented a significant step forward in machine learning (ML) applications for fusion energy experiments. The project integrated advanced data-driven modeling, optimization techniques, and artificial intelligence to enhance the predictive capabilities and operational efficiency of plasma-based fusion systems. Specifically, tasks focused on ML-enhanced diagnostics, operator guidance tools, and predictive modeling helped improve the ability to interpret complex fusion experiments. Key areas of advancement included: 1) data-driven plasma control, i.e., using ML algorithms to optimize experimental conditions and classify plasma behaviors based on historical data; 2) spectroscopy and diagnostics, i.e., applying AI models to extract previously inaccessible insights from experimental spectroscopy data; and 3) configuration mapping and operator guidance, i.e., developing a predictive framework to assist scientists in identifying the most effective experimental parameters, reducing reliance on manual adjustments. By refining these ML-driven techniques, the project contributed to the broader scientific community’s understanding of plasma dynamics and fusion energy viability. Technical Effectiveness and Economic Feasibility The methods investigated demonstrated high technical effectiveness, as reflected in milestones assessing the predictive accuracy, performance, and optimization of fusion configurations. The development of an Operator Guidance Tool (OGT), for example, led to more precise control of plasma conditions by learning from experimental data and offering real-time adjustments. From an economic standpoint, DeFT provided: 1) the ability to reduce trial-and-error experimentation, which lowered operational costs; 2) improved data interpretation methods, which enabled more efficient resource allocation in large-scale fusion research projects; and 3) the automation of key diagnostic tasks, which reduced manual labor and human error, increasing overall efficiency. 13 The final assessments of predictive models and optimization strategies demonstrated that these approaches were scalable and could be implemented across multiple fusion energy research programs. Public Benefit and Societal Impact This project contributed directly to the broader goal of achieving sustainable and commercially viable fusion energy, which had profound implications for clean energy production and climate change mitigation. The integration of AI-driven solutions into fusion research: 1) sped up scientific discovery, accelerating progress towards achieving energy breakthroughs; 2) reduced the cost of experimentation, making fusion research more accessible; and 3) provided a framework for future AI applications in high-energy physics, benefiting adjacent fields like space exploration, material science, and renewable energy. Additionally, by fostering collaborations between AI researchers and plasma physicists, this project promoted interdisciplinary innovation that could lead to broader applications beyond fusion research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

MORS Phalax Ad for Systems Analysis

At Lawrence Livermore National Laboratory, applying cutting-edge science and technology to challenging security questions is an everyday thing. Systems Analysis is one way we solve problems—by bringing analytic rigor to missions like strategic deterrence and critical infrastructure defense. Working with the brightest minds in science, technology, and engineering, systems analysts at LLNL bring state-of-the-art analytic tools to bear on problems of national importance. From ensuring the safety, security, and effectiveness of our nation’s nuclear stockpile to shaping the future of inertial fusion energy—if you have a penchant for problem-solving using modeling and analysis tools—we have a place for you.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS1982

Drops and Bubble in Materials Science

The formation of extended p-n junctions in semiconductors by drop migration, mechanisms and morphologies of migrating drops and bubbles in solids and nucleation and corrections to the Volmer-Weber equations are discussed. Bubble shrinkage in the processing of glass, the formation of glass microshells as laser-fusion targets, and radiation-induced voids in nuclear reactors were examined.

Doremus, R. H.↗
DOE OSTI2024

Yield requirements for studies of double (n,2n) reactions on dopant material in NIF Capsules

At the National Ignition Facility (NIF) inertial confinement fusion (ICF) ignition has been achieved, involving yields up to about 5 MJ. In addition, it has been suggested that proposed advances at the NIF facility, involving moderate upgrades in laser energy, could further increase fusions gains to yields in the 30-40 MJ range. Such high yield would open the possibility for new studies in many areas of science. In the present analysis, we focus on how these possible future fusion yields would make measurements of multi-step nuclear reactions on dopant material practical. For this, we consider the scenario of loading dopant material into the ablator of cryogenic capsules and estimate yields needed to measure previously inaccessible double (n,2n) reactions under ICF conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Development of Thermal Tomography Imaging System for In-Service Nondestructive Evaluation of Additively Manufactured Components

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of nuclear reactor parts. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to exposure to high temperature, radiation and corrosive environment in a nuclear reactor. Thermal tomography (TT) provides a capability for non-destructive evaluation of sub-surface defects in arbitrary size structures. We investigate TT of AM stainless steel 316L specimen with imprinted internal porosity defects using relatively low-cost, small form factor infrared (IR) camera based on uncooled micro bolometer detector. Sparse coding related K-means singular value decomposition (SVD) machine learning, image processing algorithms are developed to improve quality of TT images through removal of Additive white Gaussian noise without blurring the images. Following initial qualification of an AM component for deployment in a nuclear reactor, a compact TT can also be used for in-service nondestructive evaluation (NDE). With capability to perform in-service NDE of the AM component lifecycle, TT data can be used for development of a component digital twin. MIT research reactor (MITR) has been identified as a representative environment to perform investigation of feasibility of in-service NDE during shutdown. Preliminary study of radiation level in the MITR viewport, with geometric parameters potentially compatible with compact TT system, has been conducted.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Detection of Defects in Additively Manufactured Metallic Materials with Machine Learning of Pulsed Thermography Images

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of nuclear reactor parts. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to exposure to high temperature, radiation and corrosive environment in a nuclear reactor. Quality control (QC) requires nondestructive evaluation (NDE) of actual AM structures. Pulsed thermography is a potentially promising QC technique because it is scalable to arbitrary structure size. However, detection sensitivity of this method is limited by noises. We investigate separation of signal from noise in thermography images using several machine learning (ML) methods, including new spatio-temporal blind source separation (STBSS) and spatio-temporal sparse dictionary learning (STSDL) methods. Performance of the ML methods is benchmarked using thermography data obtained from imaging stainless steel 316L and Inconel 718 specimens produced LPBF method with imprinted calibrated porosity defects. The ML methods are ranked by F-score and execution runtime. The ML methods with higher accuracy require longer run time. However, this runtime is sufficiently short to perform QC within a realistic time frame.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗