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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Build orientation, surface roughness, and scan path influence on the microstructure, mechanical properties, and flexural fatigue behavior of Ti–6Al–4V fabricated by electron beam melting

In the present work, microstructure and fatigue behavior of Electron Beam Melted (EBM) Ti–6Al–4V have been systematically studied. Fatigue behavior was investigated using four-point bend tests of rectangular bars with internal features fabricated with different build orientations, scan paths, and surface conditions. Microstructural variations were evaluated by optical microscopy and Vickers micro-hardness indentations, both of which were found to be consistent throughout the build and within ranges reported in the literature. The fatigue performance of the EBM material was comparable to wrought Ti–6Al–4V when the loading direction was parallel to the build direction, but severely limited when loaded perpendicular to the build direction or if surface roughness defects were present. Scanning electron microscopy and interrupted fatigue tests were utilized to characterize fracture surfaces, failure mechanisms, crack initiation, and propagation behavior. Crack initiation sites in the vertically-oriented specimens were identified to be melt-related defects formed by insufficient melting.

36 MATERIALS SCIENCE↗
DOE OSTI2023

FY23 Progress Report: SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking

Algorithms for Machine Learning (ML) and data analysis for the 3013 Surveillance Program have been developed in an ongoing collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). The objective of the algorithms is to automate the identification of corrosion and crack formation in the Inner Container Closure Weld Region (ICCWR) of the canister system used to store Pu-bearing material. Data for corrosion and cracking is collected from large binary files generated by a Laser Confocal Microscope (LCM), the Wide Area 3D Measurement System (WAMS), and in a recent proposal, by a Scanning Electron Microscope (SEM). The ML software uses the physical attributes in the data files (e.g., one or all of: height, color, and grayscale values as functions of position in a plane projection) to detect the presence of surface corrosion and cracking after being trained on similar data with the features to be detected labeled.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

FY24 Progress Report: SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking

Algorithms for Machine Learning (ML) and data analysis for the 3013 Surveillance Program have been developed in an ongoing collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). The objective of the algorithms is to automate the identification of corrosion and crack formation in the Inner Container Closure Weld Region (ICCWR) of the canister system used to store Pu-bearing material. Data for corrosion and cracking is collected from large binary files generated by a Laser Confocal Microscope (LCM), the Wide Area 3D Measurement System (WAMS), or,in a recent proposal, by a Scanning Electron Microscope (SEM). The ML software uses the physical attributes in the data files (e.g., one or more of: height, color, and 16-bit grayscale values as functions of position in a plane projection) to detect signs of surface corrosion and cracking after being trained on similar data, with the features to be detected. Although the initial scope included screening for broader indicators of corrosion, e.g., pitting, identification of potential cracks was prioritized for the past several years at the request of program leadership. Labeled training data is essential to developing the ML algorithm, and enhancements to data labeling capability have been developed to address this essential precursor to application of ML routines. Efficient labeling is particularly important in view of the large volume of data required to train ML algorithms and the relative rarity of cracks in the ICCWR data set. The updated program will read binary data from either LCM, WAMS or SEM files, interrogate data attributes, facilitate user labeling of data for training ML algorithms, execute ML algorithms, output parameters from trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. In FY24, hourglass neural networks (HNNs) that were initiated in FY22 were further developed and tested using available LCM data, and their performance was tested against that of the alternative U-Net Neural Network algorithm structure. HNNs along with previously developed Convolutional Neural Networks (CNNs) and Deep Neural Networks (DNNs) comprise a suite of ML tools for identification of cracks in the ICCWR

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

FY25 Progress Report: SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking

Algorithms for Machine Learning (ML) and image analysis for the 3013 Surveillance Program have been developed in an ongoing collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). The objective of the algorithms is to automate the identification of corrosion and cracks in the Inner Container Closure Weld Region (ICCWR) of the canister system used to store Pu-bearing material. Data for corrosion and cracking is collected from large binary files generated by a Laser Confocal Microscope (LCM), the Wide Area 3D Measurement System (WAMS), or, in a recent proposal, by a Scanning Electron Microscope (SEM). The ML software uses the physical attributes in the data files (e.g., one or more of: height, color, and 16-bit grayscale values as functions of position in a plane projection) to detect signs of surface corrosion and cracking after being trained on similar data with the features to be detected. Although the initial scope included screening for broader indicators of corrosion, e.g., pitting, the identification of potential cracks was prioritized for the past several years at the request of program leadership.

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

Three-Dimensional Heat Flux and Thermal Analysis of Angled Tungsten Samples on DIII-D

ITER-grade tungsten and dispersoid-strengthened tungsten samples with the top surface angled at ~15° towards the incident plasma flux were exposed to 9 H-mode discharges with edge-localized modes (ELMs) in the lower divertor of DIII-D tokamak using the Divertor Material Evaluation System (DiMES). Surface damage included cracking and flaking of material on the two samples farthest away from the plasma strike point, and significant melting of the two samples closest to the strike point. Heat flux and thermal analysis tools new to DIII-D have been applied to better understand this material response and to help optimize the exposure conditions for future experiments. SMITER field-line tracing simulations based on IRTV data and EFIT equilibria estimate an average inter-ELM perpendicular heat flux, 𝑞⊥,𝑖nter−𝐸LM , on the angled surfaces of 10.1 – 19.6 MW/m² for a majority of the 9 discharges, increasing to 15.6 – 24.5 MW/m² for the single, higher-power shot where samples melted. Fast camera data showed shallow intra-ELM melting and re-solidification, which transitioned to bulk inter-ELM melting with melt motion in the 𝐽⃗ 𝑥 𝐵⃗ direction. About 50% of the protruding volume of the most affected sample was displaced via melt-motion. SIERRA thermal modeling software was able to reproduce an onset time of melting consistent with fast camera data and final sample conditions, within < 200 ms. Maximum surface temperatures of 3122 K and 2787 K are estimated for the samples farthest away from the strike point, while the closest samples achieve melting at 4067 ms and 4750 ms into the ~5000 ms plasma exposure. A +10% increase in both the SMITER 𝑞⊥,𝑖nter−𝐸LM calculations and the estimated ELM heat loads 𝑞⊥, 𝐸LM was required to achieve this result, which is within the uncertainty of the diagnostic data but likely accounts for non-ideal geometry effects plus other physics uncertainties not included in this first iteration of modeling. This work provided valuable estimates of the 3D temperature evolution to help better understand the observed surface morphology and internal recrystallization of samples, which are discussed in detail in a complementary manuscript [1]. Benchmarking efforts with more diagnosed DIII-D experiments are underway to further refine the SMITER and SIERRA models for DiMES. Future use of these tools will enable researchers to precisely target heat flux exposure conditions in DIII-D to test, but not exceed, the thermomechanical limitations of novel plasma-facing materials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
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↗
NASA NTRS1974

Stress intensity factors for deep cracks emanating from the corner formed by a hole intersecting a plate surface

A technique consisting of freezing photo-elasticity and a numerical method was used to obtain stress intensity factors for natural cracks emanating from the corner at which a hole intersects a plate surface. Geometries studied were: (1) crack depth to thickness ratios of approximately 0.2, (2) 0.5 and 0.75; (3) crack depth to crack length ratios of approximately 1.0 to 2.0; and (4) crack length to hole radius ratios of about 0.5 to 2.0. All final crack geometries were grown under monotonic loading and growth was not self similar, with most of the growth occuring through the thickness under remote extension. Stress intensity factors were determined at the intersection of the flaw border.

Mcgowan, J. J.↗
DOE OSTI2021

Enabling aqueous processing for LiNi 0.80 Co 0.15 Al 0.05 O 2 (NCA)-based lithium-ion battery cathodes using polyacrylic acid

Replacing N-methyl-2-pyrrolidone (NMP) with water in the production of lithium-ion battery cathodes is critical to realizing process cost savings and improved worker safety. LiNi 0.80 Co 0.15 Al 0.05 O 2 (NCA) is a poor fit for aqueous processing due to destructive Al current collector corrosion resulting from highly basic slurries and detrimental surface reconstruction reactions that occur in water. In this study, polyacrylic acid (PAA, MW = 450,000 g·mol -1 ) is examined as a corrosion-mitigating and surface-stabilizing agent. Adding PAA to an aqueous NCA slurry can provide a stable pH (4.0–8.5) for at least 4 h, since the carboxyl groups from PAA dissociate and increase the proton concentration in the slurry. Further, these groups can also adsorb to the surface of NCA particles and provide electrostatic stability from active material particle agglomeration, as revealed by zeta potential measurements. Minor cracking does occur at the electrode surface; this cracking likely caused poorer adhesion to the Al current collector in the aqueous-processed film when compared to the NMP-processed baseline. Electrochemically, the leached Li does cause a lower initial capacity for the aqueous-processed cathode, though the capacity retention of the aqueous-processed cathode is better than the baseline. The cracks in the coating led to a rise in charge transfer resistance that hindered rate capability above 1C.

25 ENERGY STORAGE↗
DOE OSTI2020

An adaptive space-time phase field formulation for dynamic fracture of brittle shells based on LR NURBS

Here, we present an adaptive space-time phase field formulation for dynamic fracture of brittle shells. Their deformation is characterized by the Kirchhoff–Love thin shell theory using a curvilinear surface description. All kinematical objects are defined on the shell’s mid-plane. The evolution equation for the phase field is determined by the minimization of an energy functional based on Griffith’s theory of brittle fracture. Membrane and bending contributions to the fracture process are modeled separately and a thickness integration is established for the latter. The coupled system consists of two nonlinear fourth-order PDEs and all quantities are defined on an evolving two-dimensional manifold. Since the weak form requires C 1 -continuity, isogeometric shape functions are used. The mesh is adaptively refined based on the phase field using Locally Refinable (LR) NURBS. Time is discretized based on a generalized-α method using adaptive time-stepping, and the discretized coupled system is solved with a monolithic Newton–Raphson scheme. Finally, the interaction between surface deformation and crack evolution is demonstrated by several numerical examples showing dynamic crack propagation and branching.

42 ENGINEERING↗
DOE OSTI2022

Mechanical evaluation of WC-Co materials with varying microstructures

Tungsten carbide–cobalt materials are useful in a variety of extreme applications due to a desirable blend of properties, yet the technology has not significantly changed since their initial development in the 1920s. The mechanical properties of this class of materials is highly dependent on two variables, the size of the tungsten carbide grains, and the amount of binder phase present in the final body. In this study, the amount of binder phase is isolated across three commercial materials from the same manufacturer with three different grain sizes to investigate the effect on mechanical properties. The mechanical properties investigated are indentation hardness, flexure and tensile strength, as well as fracture toughness. In general, an increase in hardness and tensile strength with decreasing grain size was observed, while the fracture toughness showed the opposite trend with toughness increasing with increasing grain size. The flexure strength results did not show a correlation to grain size. Fractographic analysis identified the dominant strength-limiting flaw for each sample, which largely were in the form of porosity. Other flaws types, such as inclusions from the milling process, clusters of large grains, and machining cracks from the surface finishing process, were also identified. Finally, Weibull analysis was performed and deemed appropriate for analysis of these materials, but strength-size scaling was not conducted due to the variability in the strength-limiting feature between the different specimen geometries.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Post-irradiation examination of UN-Mo-W fuels for space nuclear propulsion

The National Aeronautics and Space Administration's return to space nuclear propulsion stems from the need for a more efficient method of space travel. Nuclear thermal propulsion systems have been shown to be two times more efficient than chemical propulsion. NASA's Sirius program was created to fabricate and test fuels for space nuclear propulsion, specifically to determine their performance under prototypical startup conditions. The Sirius project featured 4 test capsules, Sirius-1 featured uranium nitride fuel dispersed in a matrix of tungsten and rhenium, while Sirius-2A, -2B, and -3 featured uranium nitride-molybdenum-tungsten fuel (UN-Mo-W). This study discusses the Sirius-2A and -2B irradiation experiments at the Idaho National Laboratory, specifically their performance under irradiation at the Transient Reactor Test Facility. It was found that the fuel samples overall did not exhibit significant cracking, though the Sirius-2A fuel did have one large crack on the surface of the fuel. There was minimal hydrogen absorption in the samples, though it is unknown if the absorption occurred during irradiation or during fabrication. Mechanical testing indicated that the UN fuel demonstrated ceramic behavior as expected, and the Mo/W matrix demonstrated linear elastic behavior to failure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Strengthening of Calcite Assemblages Through Chemical Complexation Reactions

Abstract Utilization of subsurface reservoirs, including fluid extraction/injection, can induce stress changes and modify in‐situ chemical equilibrium causing subcritical fracturing and deformation. Here, we show that chemical complexation reactions at the newly created fracture surfaces within the crack tip limit fracturing during consolidation of granular calcite assemblages. Previously, we showed that analogous chemical complexation reactions can increase in‐situ fracture toughness in pre‐fractured single crystal calcite. To test the chemical complexation effect under subsurface conditions, we consolidated samples under increasing hydrostatic pressure to induce widespread intergranular fracturing in the presence of fluid containing common anions. Measured consolidation, acoustic emissions, and microfracturing demonstrate that deformation correlates with complexation affinity for calcium in calcite and aqueous anions. We observed that deformation is lowest in the presence of strongly complexing anions (e.g., sulphate), provided sufficient anion diffusion rates. This understanding is important for predicting reservoir effective strength in the presence of complex aqueous fluids.

Choens, R. C.↗
NASA NTRS1969

Radiographic threshold detection levels of aluminum weld defects

Test program is used in the design and fabrication of special graduated aluminum penetrometers. The program evaluates the threshold detection capabilities of a fixed radiographic technique in detecting surface and subsurface cracks in one-quarter inch aluminum welds. The radiographic films were evaluated and the threshold detection capabilities defined.

Tryon, R. W.↗
NASA NTRS1971

Basic failure mechanisms in advanced composites

Fundamental failure mechanisms in carbon-epoxy composites were studied for more reliable prediction of the performance of these materials. Single and multiple fiber specimens were tested under tensile loads, and the sequence of failure events was observed. Parameters such as resin crack sensitivity, fiber surface treatment and variations in fibers from batch to batch are being evaluated. The analysis of bulk composite fracture processes using acoustic emission techniques is being studied in order to correlate microscopic observations with bulk composite behavior. Control of the fracture process through matrix and interface modification is being attempted, and study of failure processes in composite/metal specimens is being conducted. Most of the studies involved DEN 438 epoxy novolac as the matrix, but some experiments are now underway using the higher temperature resin ERLA 4617.

Mullin, J. V.↗
NASA NTRS1976

Two-layer thermal barrier coating for turbine airfoils - furnace and burner rig test results

A simple, two-layer plasma-sprayed thermal barrier coating system was developed which has the potential for protecting high temperature air-cooled gas turbine components. Of those coatings initially examined, the most promising system consisted of a Ni-16Cr-6Al-0.6Y (in wt%) thermal barrier coating (about 0.005 to 0.010 cm thick) and a ZrO2-12Y2O3 (in wt%) thermal barrier coating (about 0.025 to 0.064 cm thick). This thermal barrier substantially lowered the metal temperature of an air-cooled airfoil. The coating withstood 3,200 cycles (80 sec at 1,280 C surface temperature) and 275 cycles (1 hr at 1,490 C surface temperature) without cracking or spalling. No separation of the thermal barrier from the bond coating or the bond coating from the substrate was observed.

Stecura, S.↗
NASA NTRS1977

Two-layer thermal barrier coating for high temperature components

A simple two-layer plasma-sprayed thermal barrier coating system was developed which has the potential for protecting high temperature air-cooled gas turbine components. Of the initially examined coatings, the most promising system is an Ni-16Cr-6Al-0.6Y (in wt%) bond coating (about 0.005 to 0.010 cm thick) and a ZrO2-12Y2O3 (in wt%) thermal barrier coating (about 0.025 to 0.064 cm thick). This thermal barrier substantially lowered the metal temperature of the air-cooled airfoil. The coating withstood 3200 cycles (80 s at 1280 C surface temperature) and 275 cycles (1 hr at 1490 C surface temperature) without cracking or spalling. No separation of the thermal barrier from the bond coating or the bond coating from the substrate was observed.

Stecura, S.↗