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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Elucidating the corrosion mechanism of commercial Ni-based superalloys in UCl3 containing-chloride molten salt systems

Elucidating the role of UCl3 in the corrosion mechanism of Ni-based superalloys exposed to chloride molten salts Trishelle Copeland-Johnson1, Michael Woods1, Ruchi Gakhar1, Daniel J. Murray1, Guoping Cao1, Lingfeng He1 1Idaho National Laboratory, Idaho Falls, ID, United States The United States Department of Energy (DOE) aims to diversify the domestic energy portfolio towards more sustainable options, including implementation of molten salt reactor (MSR) technology. Chloride molten salts have been investigated as an appropriate MSR coolant and fuel because their relatively inexpensive, abundant, and exhibit favorable thermophysical properties. However, the corrosivity of chloride molten salts have not been extensively studied, especially with the inclusion of actinide products, such as UCl3. Accordingly, the development of nuclear structural materials with excellent corrosion performance is critical to the successful implementation of MSRs, particularly from a mechanistic perspective. In this investigation, we attempt to elucidate the interfacial corrosion mechanism between Ni-based structural materials, such as Inconel 617, and UCl3-containing salt systems through a multi-modal advanced characterization approach, including electron microscopy techniques. The findings from this investigation will expand the knowledgebase of chloride molten salt corrosion of MSR structural materials for strategic property-to-performance design.

36 - MATERIALS SCIENCE↗
DOE OSTI2021

Hydrothermal catalysis of waste greases into green gasoline, jet, and diesel biofuels in continuous flow supercritical water

Production of green gasoline, jet, and diesel biofuels from waste greases was achieved using a novel hydrothermal, continuous-flow catalytic process operating under supercritical water conditions, with recycled water the only added chemical. Thermally and chemically stable catalysts were explored to optimize yields of liquid biofuels and to minimize production of gases and acidic compounds. A 50:50 mixture of brown and yellow waste greases converted into 76.6 wt% liquid biocrude (BC); the remainder converted to water and gases. Less than 0.2% of the FS formed carbon char (mainly amongst catalyst particles). Various tubular reactors (Inconel, ® Hastelloy®, titanium, stainless) showed no interior defects, erosion, or mass loss after runs. Here, the titanium catalyst was fully recovered and regenerated back to its original potency. The BC was further refined into 28%, 48%, 20%, and 4 wt%, respectively for green gasoline, jet, diesel, and bunker. Biofuels were analyzed for compound class compositions and reaction mechanisms were proposed. The hundreds of identified fuel products (C3-C35) from processing oleic acid as a pure model compound were identified. The neat green gasoline and diesel biofuels along with a 50% green jet blend (with petroleum Jet A) were tested in appropriate spark ignition, turbine, and diesel engines at University of MN Engine Labs. Biofuels achieved 107.7%, 97.2%, and 101.3% engine power performance levels relative to petroleum fuels (91-Octane, Jet A, #2 Diesel) along with lower CO and pollutant emissions. Biofuels passed ASTM fuel specifications (D4814, D7566, D975) including mandated corrosion and low sulfur limits of all three biofuels.

09 BIOMASS FUELS↗
DOE OSTI2023

Assessing Manufacturability of the Oxide Dispersion Strengthened (ODS) 14YWT Alloy Fuel Cladding Tube Using SolidStir™ Technology

The 14YWT (Fe–14Cr–3W–0.4Ti–0.3Y2O3 (wt.%)) alloy is a potential candidatematerial for fabricating fuel cladding tubes and other structural components to be used in next-generation advanced nuclear reactors. Due to inherent limitations of current processing routes, this research explored a new variant of friction stir processing, commercially referred to as SolidStir™ Extrusion (patent pending) technology from Enabled Engineering to consolidate and extrude 14YWT powder into a fuel cladding tube. Several single-layer and multiple-layer consolidation experiments were carried out in an Inconel 625 die to determine the suitable processing parameters for SolidStir™ extrusion of the 14YWT alloy cladding tube. With these processing parameters, a 16–18 mm long tube of the 14YWT alloy with no visible defects was successfully extruded using this novel technology. Microstructural characterization results obtained using optical microscopy, scanning electron microscopy, energy dispersive spectroscopy, electron backscatter diffraction, and transmission electron microscopy will be presented.

Advanced Materials and Manufacturing Technology↗
DOE OSTI2024

Inhomogeneous Distribution and Coarsening of y″ Precipitates in a Ni-Based Superalloy and Their Effect on Creep

It has been reported that the addition of Nb or Ta in the high Ti/Al ratio alloys promotes the formation of y″ precipitates solely and greatly contributes to the elevated temperature strength and resistance to creep deformation. In this study, the y''-dominant INCONEL alloy 725 (IN725) variants (named M725-Nb/Ta) modified with a high level of Nb/Ta additions and high Ti/Al ratio was chosen as a model alloy for microstructural observation of y'' variants upon creep. Following the high temperature aging (HTA), y'' was found to be the main strengthening precipitate with no detectable y’ in both M725 alloys. After creep, the grip/gage sections of the crept M725-Nb/Ta exhibited preferential coarsening and inhomogeneous distribution of y''. That is, one or two of the variants were preferentially coarsened at the expense of another variant, and sandwich-like structures, comprising of cubic y′ precipitates with small y″ discs on each face, were formed. This variant selection behavior taking place in the grip section with no stress applied was different from the typical stress-induced variant selection in previous literature. However, the sample with prior high temperature exposure (700 °C for 500 hours) with varying y″ characteristics demonstrated a similar trend of creep when compared with those in the HTA sample, suggesting that the coarsening and the inhomogeneous distribution of y'' was not the determinant of creep life in bulk M725-Nb/Ta alloys.

Hung, Chang-Yu↗
DOE OSTI2025

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗
DOE OSTI2022

Physics-Informed and Data-Driven Prediction of Residual Stress in Three-Dimensional Machining

Efficient and reliable prediction of machining-induced residual stress (RS) is a key requirement for truly integrated computational materials engineering (ICME). Currently available process modeling approaches, including empirical, analytical, and numerical methodologies lack predictive power and require substantial calibration and validation data. Moreover, most model-based approaches consider only two-dimensional (2D) (i.e., orthogonal), cutting processes. Meanwhile, industrial processes such as milling, turning, and drilling are inherently three-dimensional (3D). The present work attempts to bridge the gap between 2D and 3D through careful consideration of the process physics, including geometric, kinematic, and size-effect constraints to realize robust prediction of how RS develops in 3D machining. Using a novel in-situ experimental technique and digital image correlation (DIC) to determine equivalent Hertzian contact widths, contact pressures, and friction coefficients, the proposed methodology leverages a discretized conversion algorithm that includes multi-pass shakedown effects. This paper presents a semi-analytical model to predict machining-induced RS in 3D turning operations, which are used representatively for 3D processes more generally. Rather than follow a ‘brute force’ 3D FEM approach or conduct countless experiments to train a purely data-driven machine learning algorithm, the proposed approach builds on previous 2D modeling work. Through careful consideration of the process physics, including complex geometry/kinematic considerations of 3D turning, the authors demonstrated an experimentally calibrated approach, as well as validation based on published RS data. Model predictions and previously published measurement data of RS depth profiles for turning of Inconel 718 were compared for a range of process parameters. Correlation between the proposed 3D model and validation data was found to be within the margin of experimental error for most conditions. The proposed model appears to capture the overall behavior of 3D RS depth profiles with acceptable accuracy, particularly the key metrics of near-surface stress, peak stress magnitude and location, as well as overall stress profile depth. This report presents a physics-informed, data-driven approach for efficient calibration of a 2D model for machining-induced RS through DIC analysis of in-situ characterized subsurface displacement fields.

42 ENGINEERING↗
DOE OSTI2020

Quality Control of Additively Manufactured Metallic Structures with Machine Learning of Thermography Images

Additive manufacturing (AM) of high-strength metals is currently based on the laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Quality control (QC) requires nondestructive evaluation of actual AM structures. Flash thermography is a potentially promising QC technique because it is scalable to arbitrary structure size. However, the detection sensitivity of this method is limited by noise. We investigate separation of signal from noise in thermography images using several machine learning (ML) methods, including new spatial–temporal blind source separation and spatial–temporal sparse dictionary learning methods. Performance of the ML methods is benchmarked using thermography data obtained from imaging stainless steel 316L and Inconel 718 specimens produced by the LPBF method with imprinted calibrated porosity defects. The ML methods are ranked by F-score and execution runtime. Finally, the ML methods with higher accuracy require a longer runtime. However, this runtime is sufficiently short to perform QC within a realistic time frame.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Prediction of Creep-Induced Strain Using a Symbolic Regression-Based Model

Material creep under high-temperature conditions limits the lifetime and safety of structural systems such as advanced nuclear reactors. Conventional creep testing is slow and often produces inconsistent results across nominally identical experiments, making lifetime prediction uncertain. Here, to address these challenges, this work develops a data-driven symbolic regression (SR) model that consolidates results from duplicate creep tests and predicts the remaining strain-time curve of an ongoing experiment. The method uses piece-wise multi-objective SR with physical constraints to generate analytic, interpretable functions describing transient creep strain. Applied to Inconel Alloy 617 data, the approach achieved relative mean absolute errors of 1.0–9.5%, providing closed-form predictions of strain evolution. These results demonstrate a first step toward reducing the duration and cost of long-term creep testing while retaining physically interpretable model forms.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

AFRL Additive Manufacturing Modeling Series: Challenge 4, In Situ Mechanical Test of an IN625 Sample with Concurrent High-Energy Diffraction Microscopy Characterization

In this work, we describe 3D characterization of an additively manufactured Inconel 625 nickel-base superalloy specimen conducted during a uniaxial tension test using a suite of nondestructive x-ray techniques. High-energy diffraction microscopy in both near- and far-field modalities are employed in situ to track evolution of the material orientation and stress–strain fields at six points during the mechanical test, and these data streams are registered with micro-computed tomography reconstructions which probe the material density. This data volume was matched to a multi-modal serial sectioning characterization of the specimen taken after loading, described in this article’s companion. Twenty-eight grains which were monitored throughout the experiment were selected to form the basis for AFRL AM Modeling Series Challenge 4, Microscale Structure-to-Properties.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Predicting Sintering Window of Binder Jet Additively Manufactured Parts Using a Coupled Data Analytics and CALPHAD Approach

Batch-to-batch variation in powder compositions for binder jet additive manufacturing (BJAM) can significantly deter defining an “ideal” sintering window for a given alloy. One way to overcome the problem is by running sintering experiments at various temperatures for each batch of the powder. However, such an approach increases the time required to achieve large-scale production of parts. The predictive capabilities of computational thermodynamic tools like CALPHAD can be leveraged to overcome the challenge, especially for binder jet additive manufacturing, since the process occurs under near-equilibrium conditions. However, calculating the sintering window using CALPHAD can be computationally expensive, considering many possible feedstock compositions within “specification”. Here, we generate high throughput CALPHAD data for nickel-based superalloys to develop machine learning models to predict the sintering window rapidly. The predictive capability of the models has been validated using published results on BJAM of Inconel 718 and 625. Further, validated models are lightweight and can be deployed in an industrial setting to get sintering window in an accelerated manner.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Heterogeneous creep deformation behavior of functionally graded transition joints (GTJs)

Dissimilar metal welds (DMWs) made between ferritic steels and austenitic alloys are used extensively in high-temperature power plant components. These DMWs experience premature creep failure in the ferritic steel’s heat affected zone (HAZ), close to the weld interface. Steep variations in microstructure and chemical composition across the dissimilar weld interface have been the contributing factors for the failure. Graded transition joints (GTJs), developed by functionally grading the chemical composition in layers, have been proposed as potential candidates to replace DMWs. In this research, GTJ coupons were fabricated between 2.25Cr-1Mo steel and Alloy 800H base material using two filler materials: (i) Inconel 82 and (ii) P87. These samples were aged at 600°C for 2000h to accelerate high-temperature microstructural evolution seen in service conditions, before subjecting them to short-term (~1 month) creep tests. Surface strains were measured using digital image correlation (DIC) technique to extract creep strain rates at different locations within GTJs. Both the GTJs exhibited heterogeneous creep strain distribution. Creep strain accumulated in the FGHAZ of 2.25Cr-1Mo steel, similar to type IV failure associated with Cr-Mo steel weldments. Microstructure based creep model framework was developed to describe the discrete creep strain rates observed in various 2.25Cr-1Mo steel regions of GTJs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Development of a heterogeneous nanostructure through abnormal recrystallization of a nanotwinned Ni superalloy

This work explores the development of a heterogeneous nanostructured material through leveraging abnormal recrystallization, which is a prominent phenomenon in coarse-grained Ni-based superalloys. Additionally, through synthesis of a sputtered Inconel 725 film with a heterogeneous distribution of stored energy and subsequent aging treatments at 730°C, a unique combination of grain sizes and morphologies was observed throughout the thickness of the material. Three distinct domains are formed in the aged microstructure, where abnormally large grains are observed in-between a nanocrystalline and a nanotwinned region. In order to investigate the transitions towards a heterogeneous structure, crystallographic orientation and elemental mapping at interval aging times up to 8 h revealed the microstructural evolution and precipitation behavior. From the experimental observations and the detailed analysis of this study, the current methodology can be utilized to further expand the design space of current heterogeneous nanostructured materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Direct observations and characterization of crack closure during microstructurally small fatigue crack growth via in-situ high-energy X-ray characterization

This study provides direct observation of the crack closure mechanism of a naturally occurring, tortuous, 3D microstructurally small fatigue crack (SFC) in additively manufactured Inconel 718. In-situ non-destructive characterization is performed using high-energy X-ray diffraction techniques to capture the evolution of the 3D microstructure and micromechanical response in the vicinity of the crack front. Based on the stress state of twelve grains analyzed at the crack tip, the crack closure events of the SFC front was found to be spatially heterogeneous with respect to loading progression governed by the local stress state of the grains (specifically the stress reversal from compression to tension). From this analysis, three grains that displayed different degrees of crack closure were further investigated, based on the orientation of the crack relative to the grains and the associated modality of crack growth. The stress normal to the crack plane and the associated degree of Mode I crack behavior were correlated with events of the crack opening earlier during the loading cycle. This was further corroborated by diffraction spot spreading analysis that quantified the crystallographic lattice distortion caused by the opening crack. Additionally, the detailed characterization of the opening behavior of the grains located at the crack tip and their associated states of stress elucidates the mechanism governing crack closure and will inform future modeling efforts of this phenomenon.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Vector-level feedforward control of LPBF melt pool area using a physics-based thermal model

Laser powder bed fusion (LPBF) is an additive manufacturing technique that has gained popularity thanks to its ability to produce geometrically complex, fully dense metal parts. However, these parts are prone to internal defects and geometric inaccuracies, stemming in part from variations in the melt pool. Here, this paper proposes a novel vector-level feedforward control framework for regulating melt pool area in LPBF. By decoupling part-scale thermal behavior from small-scale melt pool physics, the controller provides a scale-agnostic prediction of melt pool area and efficient optimization over it. This is done by operating on two coupled lightweight models: a finite-difference thermal model that efficiently captures vector-level temperature fields and a reduced-order, analytical melt pool model. Each model is calibrated separately with minimal single-track and 2D experiments, and the framework is validated on a complex 3D geometry in both Inconel 718 and 316L stainless steel. Results showed that feedforward vector-level laser power scheduling reduced geometric inaccuracy in key dimensions by 62%, overall porosity by 16.5%, and photodiode root-mean-squared deviation by 38.5% on average. Overall, this modular, data-efficient approach demonstrates that proactively compensating for known thermal effects can significantly improve part quality while remaining computationally efficient and readily extensible to other materials and machines.

Additive manufacturing↗
DOE OSTI2026

Micromechanical and fatigue in situ synchrotron characterization of an additively manufactured superalloy with porosity

Additive manufacturing (AM) has the potential to transform component production, but its widespread adoption is constrained by defects, such as pores, that compromise structural integrity. Here, this study investigates the influence of porosity on the micromechanical and fatigue response of AM Inconel 718 (IN718), a widely used aerospace superalloy. One baseline specimen with minimal stochastic porosity and another intentionally seeded with lack of fusion (LOF) pores were examined using high-energy X-ray diffraction microscopy (HEDM) and micro-computed tomography during cyclic loading. Fatigue cracks in the LOF specimen initiated more frequently and at lower cycle counts than in the baseline specimen. The number fraction of fatigue cracks that grew was comparatively higher in the LOF specimen. Grain-level metrics, including stress and diffraction spot widths, were quantified using far-field HEDM. Across the thousands of grains detected in both specimens, the pores in the LOF specimen increased the variability of stress and spot width evolution in the azimuthal direction, the latter serving as a surrogate measure of plastic deformation. However, no correlations emerged between these metrics and grain proximity to fatigue crack initiation sites or pores, underscoring the limitations of grain-averaged metrics for predicting fatigue. Nonetheless, the rich dataset reported here provides a foundation for future modeling efforts.

High-energy X-ray diffraction microscopy↗
DOE OSTI2025

Hydrogen diffusion induced dislocation transformations in a nickel superalloy

The diffusion of hydrogen in metals and alloys induces embrittlement that can adversely affect the structural properties. We examine the adsorption and diffusion of hydrogen in Inconel-718 (IN-718), and scrutinize the ensuing effects on the dislocation behavior in the alloy to elucidate the fundamental mechanisms of hydrogen-microstructure interactions from classical molecular simulations. Hydrogen adsorption increases with time until the surface saturates, while hydrogen diffusion exhibits strong temperature dependence, with diffusion coefficients converging above 1300 K regardless of the initial hydrogen concentration in the alloy. The diffusion in IN-718 is significantly sluggish than in pure Ni, Fe, or Cr, and is strongly impacted by hydrogen concentrations, resulting in an order of magnitude higher diffusion coefficient for hydrogen (10-14 m2/s relative to 10-15 m2/s) at high concentrations, especially below 600 K. Hydrogen diffusion coefficient varies from 10-12 to 10-15 m2/s in IN-718 depending on temperature (500–1400 K). More critically, our results reveal that increasing hydrogen concentration induces microstructural changes in the alloy, transforming perfect dislocations into stair-rods and Shockley partials, with higher temperatures favoring the latter. The results are significant for hydrogen fuel applications to gain insights into the materials chemistry for designing safer and more efficient propulsion systems, particularly in high-performance environments related to controlled hydrogen combustion applications.

Banerjee, Tanumoy↗
DOE OSTI2026

The solubility of ErPO 4 and Er speciation in hydrothermal fluids at varying pH and salinity between 350 and 450 °C

The rare earth elements (REE) are important for the green-energy transition and can be incorporated into the REE phosphates, such as xenotime-(Y), which also hosts heavy REE (Tb– Lu). Xenotime-(Y) is a common accessory mineral in metamorphic rocks and a range of mineral deposits where it controls the mobility of heavy REE, however, the impact of high temperature aqueous fluids on the behavior of heavy REE is largely unknown. Thermodynamic modeling can be utilized as a tool to predict the mobility of REE in hydrothermal aqueous fluids, but must be supported by accurate experimental data. Here, we measured the solubility of endmember synthetic xenotime-structured ErPO4 in NaCl-HCl-NaOH-bearing aqueous solutions at 350 °C and water vapor saturation pressure, at 400 and at 450 °C and 500 bar using batch-type Inconel reactors. Erbium speciation was investigated as a function of pH from 2.8 to 8, where Er chloride species are predominant at acidic conditions (pH <3) and Er hydroxyl complexes are predominant at near- neutral to alkaline conditions (pH >3). At pH 7–9, the measured ErPO 4 solubility (-9.8 to -7.5 log m Er ) is up to 2.5 orders of magnitude lower than thermodynamic predictions (-9.4 to -6.7 log m Er ) using existing thermodynamic databases. At pH 2–3, the predicted ErPO 4 solubility is ~0.5 orders of magnitude higher at 350 °C and ~1 order of magnitude lower at 450 °C compared to experimentally measured Er concentrations. The thermodynamic properties of aqueous Er species were therefore revised in this study. The partial molal Gibbs energy of formation (Δ f G 0 T,P ) for aqueous Er hydroxyl and chloride species are optimized using GEMSFITS and the logarithmic formation constants (logβ n ( Cl,OH) ) were derived at each experimental temperature and pressure. The updated thermodynamic properties for Er hydroxyl species (Er(OH) +2 , Er(OH) 2 + , and Er(OH) 3 0 ) show that their stability shifts to more acidic conditions at and below 400 °C. The Er chloride species (ErCl +2 and ErCl 2 + ) show increased stability compared to Er hydroxyl species at temperatures of 450 °C and 0.01 mol/kg NaCl. The updated thermodynamic properties are implemented into the GEM-Selektor modeling package to investigate the mobility of Er in saline hydrothermal fluids in equilibrium with alkaline rocks. Importantly, the updated properties for Er hydroxyl species result in low Er solubility at rock equilibrated pH conditions due to an expanded hydroxyl predominance zone, but lower aqueous complex stability overall, whereas previous models suggest greater stability for aqueous Er species. Furthermore, ErPO 4 solubility increases with decreasing temperature due to the deprotonation of HCl, which increases the acidity of hydrothermal fluids and the availability of Cl - to complex with the REE. These simulations highlight how fluid-rock reaction and temperature affect the mobility of REE in hydrothermal ore-forming systems.

58 GEOSCIENCES↗
DOE OSTI2022

Using real-time data analysis to conduct next-generation synchrotron fatigue studies

Next-generation experimental techniques, like high energy X-ray diffraction microscopy (HEDM), usher in new opportunities to collect the grain-scale data necessary for understanding the evolving processes that drive fatigue failure. In this study, we present a framework for monitoring the evolution of a deforming polycrystal, in real-time, by applying principal component analysis (PCA) to raw X-ray diffraction image data. We applied this framework to inform in-situ HEDM measurements of a cyclically loaded Inconel-718 superalloy. Further, we discovered correlations between PCA of the diffraction data and the physical processes in the polycrystal. Lastly, we discuss extending this framework in future HEDM fatigue studies.

36 MATERIALS SCIENCE↗