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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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402 records · Page 23

Affine Transformations to Enable Machine Learning for Semi-Quantitative EDS Analysis

Energy Dispersive X-ray Spectroscopy (EDS) is an essential technique for determining elemental concentrations and distributions within microstructures, critical for materials discovery, optimization, and qualification. However, most published EDS data is qualitative because current quantitative EDS analysis methods require extensive calibration and post-processing, limiting their practicality and widespread adoption. This work seeks to establish a framework for accelerated EDS characterization and spectrum analysis that can leverage ML to analyze correlations between various elemental compositions and resulting EDS spectra. The complex physics and data result in a high-dimensional problem that grows exponentially with the number of elements in the system and the complexity of the spectrum analysis. ML provides a way to compute and optimize the results of this highly dimensional problem in a flexible way to tailor it to the user’s specific needs and material system. However, the framework emphasizes transparency through a strictly mathematical affine transformation, so the analysis remains understandable and reviewable to facilitate adoption by the scientific community. While currently implemented methods are simplistic and unvalidated, further development and demonstration of this framework could enable high-throughput, accurate, and accessible EDS characterization.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Affine Transformations to Correlate Experimental and Simulated EDS Spectra for Multi-Element Systems

Energy Dispersive X-ray Spectroscopy (EDS) is an essential technique for determining elemental concentrations and distributions within microstructures, critical for materials discovery, optimization, and qualification. However, most published EDS data is qualitative because current quantitative EDS analysis methods require extensive calibration and post-processing, limiting their practicality and widespread adoption. This work seeks to establish a framework for accelerated EDS characterization and spectrum analysis that can leverage ML to analyze correlations between various elemental compositions and resulting EDS spectra. The complex physics and data result in a high-dimensional problem that grows exponentially with the number of elements in the system and the complexity of the spectrum analysis. ML provides a way to compute and optimize the results of this highly dimensional problem in a flexible way to tailor it to the user’s specific needs and material system. However, the framework emphasizes transparency through a strictly mathematical affine transformation, so the analysis remains understandable and reviewable to facilitate adoption by the scientific community. While currently implemented methods are simplistic and unvalidated, further development and demonstration of this framework could enable high-throughput, accurate, and accessible EDS characterization.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Results of FY 2023 Alloy 617 and Alloy 709 High-Temperature Crack-Growth Testing

This report summarizes the work performed at Idaho National Laboratory under the “Creep, fatigue and creep-fatigue crack growth tests” task of the “Long-Term VHTR Material Qualification – INL” work package. Work was performed this year to validate the crack growth monitoring setup used with the test frames against both continuous crack length monitoring using an optical camera, as well as post-mortem analysis of marker bands on the fracture surface. Delays prevented the use of a gauge to measure load-line displacement for early tests, and so the creep-fatigue crack growth setup was evaluated using the actuator displacement for a load-line displacement setup. While not ideal, this allowed examination of the shortcomings with the current software setup that was originally designed for performing stress corrosion crack growth rate studies. The method for data collection was modified to link the crack growth monitoring software with Instron’s Wave Matrix software. Once the load-line displacement gauge arrived, the crack growth equipment was successfully modified to permit continuous monitoring of both load-line displacement and crack length. This is critical for creep-fatigue and creep crack growth rate studies for ductile material, as it permits the C* and Ct analyses. Test results are shown for Alloy 617 fatigue and creep-fatigue (without the gauge for load-line displacement measurements), as well as creep-fatigue of Alloy 709, which was performed with the completed test setup, allowing for crack length and load-line displacement monitoring.

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Advanced Manufactured Strain Sensors for Extreme Environments

Experimentation at irradiation test facilities are essential for reducing the innovation time of developmental fuels, fuel cladding, and structural materials employed in next-generation nuclear reactors. However, due to the harsh conditions generated in such reactors and limited instrumentation space, the evaluation of a material’s mechanical properties is often limited to characterization after the materials have been removed from reactor conditions, or post-irradiation examination. These experiments are costly, time-consuming, and fail to capture the critical time-evolving phenomena that occur during the irradiation experiments. Advanced manufactured digital image correlation patterns and strain sensor devices serve as two promising technologies that can be deployed in the confined and challenging orientations of these irradiation experiments while also providing key insight on salient materials phenomena (i.e., mechanical properties). To guide the development of the printed strain sensors prior to their deployment in critical experiments, the adhesion strength between the substrate and printed film interface is measured via tensile testing and a non-contact laser-induced spallation technique. The establishment of these process control steps helped guide the successful fabrication and testing of direct-write strain sensing devices discussed in this work. The fabrication process controls are necessary for enabling the sustained operation of these strain sensing device through experimentation and minimize the potential for premature failure.

36 - MATERIALS SCIENCE↗

FINITE ELEMENT MODEL MESH REFINEMENT EFFECTS ON QUALIFICATION OF NUCLEAR GRADE GRAPHITE COMPONENTS

The American Society of Mechanical Engineers (ASME) provides the full and simplified design-by-analysis probabilistic assessments for determining acceptance of nuclear grade graphite core components. The assessments can be characterized by three parts: (1) a component stress distribution, often determined by a finite element (FE) model; (2) a Weibull probability density function (pdf) that characterizes the experimental tensile strength distribution; and (3) the post-processor, which combines the FE model and the Weibull strength distribution in accordance with the full and simplified assessments to determine component acceptance. It is known that the level of mesh refinement in FE models can affect the modeled component’s calculated stress distribution. Depending on the component geometry, the stress distribution may converge with sufficient refinement. It was previously unknown whether the acceptance decision resulting from the full and simplified assessments might change even with sufficient mesh refinement. This study explores that question using experimental strength results for a dog-bone geometry for two graphite grades, IG-110 and PCEA. The simplified assessment has two criteria that must be met, the first limits the combined membrane stress by the allowable stress and the second limits the peak equivalent stress by the allowable stress scaled by the ratio of flexural to tensile strength. In the application of the simplified assessment, convergence of the peak equivalent stress required extreme mesh refinement, however, the acceptance decision was not affected. It is hypothesized that more complex geometries with stress concentrations may present mesh refinement effects on the simplified assessment acceptance decision. Mesh refinement did affect the acceptance decision in the full assessment for the applied pressure loadings in this study. This work suggests component stress distribution convergence is not a sufficient criteria for POF convergence in the full assessment and that mesh refinement should continue until the POF has converged, especially where the resulting POF is bordering the SRC acceptable POF limit.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Defect Production and Microstructural Feature Impact for Radiation Damage in Additively Manufactured 316 Stainless Steel

This milestone presents multi-scale modeling research results for additively manufactured 316 stainless steel. A combination of phase field, cluster dynamics, molecular dynamics, and density functional theory with machine learning is used, allowing for predictions of radiation-driven microstructural evolution in additively manufactured 316 stainless steel over a range of temperatures, damage rates, neutron spectra, and microstructures, and supporting the development of combined ion and neutron irradiation for material qualification. Informed by ion irradiation and neutron irradiation results across the Advanced Materials and Manufacturing Technologies program, we investigate the unique aspects of radiation-driven microstructure evolution in additively manufactured 316 stainless steel. In particular, we focus on understanding the impact of carbon concentration (varying, for example, between the 316L and 316H standards) on void formation; radiation-induced segregation at dislocation cells and grain boundaries; and the evolution of dislocation loops and network dislocation populations. We find that the unique characteristics of the additively manufactured microstructures must be accounted for in understanding the evolution of dislocation populations under thermal and irradiation conditions, such as the variation in sink strengths arising due to the variation in dislocation density. We also find that the radiation-induced segregation of Cr and Ni to grain boundaries and cell walls differs due to the differences in their defect sink biases. We also find that increasing the Ni content can slow vacancy diffusion, which may provide a mechanism for the observed reduction in transient swelling rate for austenitic Fe-Cr-Ni alloys with increasing Ni content. In addition, ion irradiations have shown that increasing carbon content in 316 SS results in a larger population of smaller voids, suggesting reduced vacancy diffusion. Our results show that the carbon content of additively manufactured 316 SS has a significant impact on the migration rate of defect clusters. The presence of carbon atoms results in carbon-vacancy trapping, significantly reducing the diffusion rate of vacancies. Carbon atoms may also be trapped near the surface of a void, which may reduce void growth by trapping vacancies that diffuse toward the void.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗