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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Effect of Material Porosity on Residual Stress in an Additive Manufacturing Simulation using the Generalized Method of Cells

The effect of material porosity on final part distortion and residual stresses in a selective laser sintering manufacturing simulation is presented here. A time-dependent thermo-mechanical model is used with the open-source FEA software CalculiX. Effective homogenized material properties for Inconel 625 are precomputed using NASA’s Micromechanics Analysis Code with the Generalized Method of Cells. The evolving porosity of the material is estimated with each pass of the laser beam during simulation runtime. A comparison with a homogenous model and the evolving model shows that the model with evolving porosity predicts larger distortions with greater residual stresses.

Additive Manufactuirng↗
NASA NTRS2024

Exploring the Role of Type-II Residual Stresses in A Laser Powder Bed Fusion Nickel-Based Superalloy Using Measurement and Modeling

Far-field high-energy X-ray diffraction microscopy (ff-HEDM) and the crystal plasticity finite element method (CPFEM) are used to investigate the role of grain-scale (Type-II) residual stresses on the fatigue life of additively manufactured (AM) Inconel alloy 625 (IN-625). Grain-averaged orientations, centroids, and residual elastic strain tensors from ff-HEDM data are used to instantiate a crystal plasticity model to simulate the effect of residual stresses at the grain scale. Simulation results indicate that the presence of tensile residual strains increase stress localization and heterogeneity within grains, triggering an earlier onset of plasticity. A microscale fatigue indicator parameter (FIP) is computed to model the impact of these residual strains on the cycles to fatigue crack nucleation. The crack nucleation model, based on the computed FIPs, predicts a significant reduction in the number of cycles for fatigue crack nucleation for mid- and high-cycle fatigue due to the residual strain induced localization, while the residual strains have minimal impact on low-cycle fatigue life.

Inconel↗
DOE OSTI2022

High Temperature Ternary Chloride Molten Salt Pump

This work investigates the design criteria considering thermal, structural, and mate-rial selection of a ternary chloride (MgCl2-NaCl-KCl) molten salt pump that is capable of running at temperatures above 720 °C. In this work, preliminary testing of salt-wetted hydrodynamic bearings was done to investigate different material pairings including colmonoy grades, stellite grades, and a novel NiWC-based alloy (i.e. HybrimetTM NiWC3b) used as a High Velocity Ox-ygen Fuel (HVOF) coating. The coating has shown to withstand the corrosive nature of the salt, and is additionally used to protect a 316L stainless steel pump reservoir. The pump wetted components are made of Inconel 625, and it features a carbon ring seal developed by Flows-erve flooded with a N2 gas flow on the overhead to keep salt vapors from interacting with the external ambient air. This research showcases a promising design for use in the CSP Gen 3 liquid-pathway and sets the ground for further development and use of the HybrimetTM NiWC3b as a competitive alternative to available superalloys. Further work will further characterize the pump by performance & cycle testing in molten salt at higher temperatures.

14 SOLAR ENERGY↗
DOE OSTI2020

Filter 'Cook-Off': Filter Selection via Side-by-Side Testing at Actual Process Conditions - 20040

In 2005, the THOR steam reforming fluidized-bed reactor technology was selected by the U.S. Department of Energy for treatment of sodium-bearing waste at the INL. During the final phase of commissioning prior to radiological operations, regeneration of the high temperature filters in the process gas filter (PGF) vessel became ineffective. After approximately 50 days of testing, the differential pressure across the filters began increasing exponentially and the plant had to be shutdown. Subsequent investigation revealed that the Inconel 625 (I625) sintered metal filter media was corroding in the 550 deg. C reducing environment. A pilot plant run tested four candidate replacement filter media. The top candidate was further tested during a long-term pilot plant run to validate the selection. Data from the testing indicate the selected filters will provide reliable service throughout the life of the project, including after in-situ radiological decontamination. This paper presents the data from this effort and reinforces the value of pilot plant testing. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
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↗