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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Microstructural evolution of an aluminide coating on alloy 625 during wet air exposure at 900 °C and 1000 °C

The microstructural changes of the aluminized alloy 625 during cyclic oxidation in air + 6% H 2 O at 900 °C and 1000 °C were analyzed using optical metallography (OM), scanning electron microscopy (SEM) with energy and wave length dispersive X-ray analysis (EDX/WDX) as well as electron backscatter diffraction (EBSD). An in-house developed thermodynamic-kinetic procedure was employed to predict the microstructural evolution of aluminized alloy 625 during high temperature exposure by considering simultaneously occurring surface oxidation and interdiffusion processes. Because of the lack of mobility data for the relevant alloying elements in the σ-phase, assumptions for the mobilities were made based on the value of the mobilities in α-Cr. Despite these assumptions, the calculated results were found to be in good agreement with experimental observations. The complete depletion of β-NiAl in the coating observed during exposure at 1000 °C was correctly predicted by the model. The model was also able to infer dissolution of the precipitate phases α-Cr and σ in the interdiffusion zone during exposures at 900 °C and 1000 °C. The model was yet unable to predict the formation of the μ-phase in the alloy after 1000 h of exposure at 1000 °C. The developed modelling method offers the potential to predict microstructural changes of aluminized nickel base alloys thus reducing cost and time consuming experimental efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Unravelling Microstructure Selection in an Additively Manufactured Eutectic High‐Entropy Alloy

High-entropy alloys (HEAs) are promising candidates for advanced structural applications due to their excellent mechanical properties. Additive manufacturing (AM), with its rapid solidification conditions, enables the creation of unique nonequilibrium microstructures. To fully leverage the synergy between AM and HEAs, understanding how processing affects structure and properties is essential. Here, how solidification rate influences microstructure evolution and phase transformation pathway in laser additively manufactured AlCrFe2Ni2 eutectic HEAs is investigated. By increasing the laser scan speed and hence the solidification rate, distinct solidification modes evolving from coupled eutectic to anomalous eutectic and eventually to single-phase solidification are revealed. These transitions result in distinct microstructures and a wide range of mechanical properties. Thermodynamic modeling and molecular dynamics simulations reveal that low cooling rates allow for sufficient atomic diffusion and phase separation, facilitating coupled eutectic growth. In contrast, rapid cooling suppresses diffusion and destabilizes the solid–liquid interface, promoting anomalous or single-phase solidification. This integrated experimental and computational approach provides a multiscale understanding of solidification mechanisms in HEAs and underscores how kinetic effects can over-ride thermodynamic predictions under nonequilibrium conditions. Furthermore, these results demonstrate that AM can serve as a powerful tool to design HEAs with tailored microstructures and properties.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Multiscale Modeling of Reconstructed Tricalcium Silicate using NASA Multiscale Analysis Tool

To study microstructure characteristics of cementitious materials hydrated in space; previously, cement binder formations were processed under microgravity conditions and was further compared against ground-based experiments. For accurate estimation of process-structure-property linkage, particularly on samples hydrated in the microgravity environment, it is desired to have a high-fidelity volumetric representation of the microstructure. However, owing to small sample size and high porosity of the space-returned samples, conventional experimental characterization techniques are not viable. Hence, a deep learning-based reconstruction algorithm was employed to obtain high fidelity 3D volumes from sparse high resolution 2D Scanning Electron Microscopy (SEM) images, as inputs to micromechanics-based modeling. This machine learning-based reconstruction methodology validated against low-order statistical descriptors, captured the microstructural topology of both sample types (ground, 1g and microgravity, μg). Due to the lack of gravity, hydration products of the samples processed in space differed from those processed-on ground. Such AI-generated virtual samples were analyzed in a multiscale recursive micromechanics approach using the NASA Multiscale Analysis Tool (NASMAT). Here, we present a methodology to rapidly integrate and evaluate these AI-generated volumes in NASMAT. The synthesized microstructural volumes are directly employed as Representative Volume Elements (RVEs) to preserve the fidelity (1 pixel = 0.54 m). Invariably, analysis of such largescale problems (5123 voxels) requires huge amount of computational resources. By taking advantage of the NASMAT architecture, we also focused on systematic multiscale integration of these AI-reconstructed virtual volumes to reduce the computational demands. In this work, this methodology is demonstrated on the ground-based, 1g samples. The estimated stiffness value of 15.90 GPa is comparable to experimentally obtained modulus of hydrated tricalcium silicate sample. The workflow presented here paves the way for utilizing the NASMAT tool to perform multiscale analyses of other multi-phase material systems using either 3D virtual datasets synthesized using AI or obtained via micro-CT.

Machine Learning↗
DOE OSTI2022

Three-dimensional microstructural characterization of FBR MOX fuel and the contribution of microstructural features to the thermal conductivity of the fuel

Combination of microstructural characterization, property measurements, and phase field modeling is used to investigate fast breeder reactor (FBR) mixed oxide (MOX) fuel irradiated to burnup of 13.7% fissions per initial metal atom (FIMA). Here, the fuel was characterized at different radial locations, which revealed that grey phase can be present in the central region if it nucleates on five metal precipitates (FMPs). In addition, in the mid-radial region FMPs do not diffuse out of the region once formed and the size of Pd–Te precipitates is dictated by the porosity present in the region. Thermal conductivity measurements were conducted as a function of radial location and the microstructure of the fuel was correlated with the observed trend. Reconstructions of the 3D solid and gaseous fission product structures in different regions of the fuel were used to simulate the effective thermal conductivity (ETC) of the respective regions and determine which microstructural feature has the strongest impact on thermal conductivity. Based on conducted assessment, FMPs and Pd-Te precipitates improve local conductivity of central and mid-radial regions even in the presence of grey phase, but defects are primary contributor to the degradation of thermal conductivity on the periphery of the fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Parameterization of vacancy production rate in phase-field models of fission gas bubble evolution in nuclear fuel

Phase-field modeling has increasingly been used to study microstructural evolution in fission gas bubbles in nuclear fuel to improve understanding of fission gas release. To improve computational efficiency, often only vacancies and gas atoms are included as defect species. In this case, the net effects of vacancy and interstitial production, recombination, and biased sink absorption are included as a net vacancy source, or net vacancy source combined with an effective sink. However, there has been a lack of clarity on what parameter values should be used for these approaches to best match the more complete physical picture that includes interstitials and vacancies. Here, we compare a phase-field model of void growth to analytical models for the source-only and source plus sink approach to gain insight into how the phase-field models can be parameterized effectively. The source-only approach provides greater flexibility to match growth rates determined from the full vacancy-interstitial picture. A strategy was developed for determining the value of the net vacancy source term by comparing to an analytical model that includes vacancy and interstitial production, recombination, and biased sink absorption. Finally, this strategy can be used to parameterize phase-field models of fission gas bubble growth.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Effects cascade debris and helium bubbles on the strength of aged plutonium

The radioactive decay of aging Pu is dominated by α-decay. This persistent α-decay produces crystalline defects in the form of dislocation loops and helium bubbles that evolve with time. Comparable defects are produced in other metallic alloys when subject to neutron irradiation, and these defects are known to modify the plastic deformation of irradiated materials. Models have been developed for these irradiated materials and validated against experimental confirmations of yield strength and the concomitant microstructural evolution. In this paper, we deploy those previously developed models and apply their mechanics to plutonium aging.

Chemical elements↗
NASA NTRS2010

Effect of Microstructural Parameters on the Relative Densities of Metal Foams

A detailed quantitative microstructural analyses of primarily open cell FeCrAlY and 314 stainless steel metal foams with different relative densities and pores per inch (p.p.i.) were undertaken in the present investigation to determine the effect of microstructural parameters on the relative densities of metal foams. Several elements of the microstructure, such as longitudinal and transverse cell sizes, cell areas and perimeters, ligament dimensions, cell shapes and volume fractions of closed and open cells, were measured. The cross-sections of the foam ligaments showed a large number of shrinkage cavities, and their circularity factors and average sizes were determined. The volume fractions of closed cells increased linearly with increasing relative density. In contrast, the volume fractions of the open cells and ligaments decreased with increasing relative density. The relative densities and p.p.i. were not significantly dependent on cell size, cell perimeter and ligament dimensions within the limits of experimental scatter. A phenomenological model is proposed to rationalize the present microstructural observations.

Raj, S. V.↗
DOE OSTI2021

Effect of Nanoscale Ce 0.8 Gd 0.2 O 2–δ Infiltrant and Steam Content on Ni–(Y 2 O 3 ) 0.08 (ZrO 2 ) 0.92 Fuel Electrode Degradation during High-Temperature Electrolysis

Studies of Ni–yttria-stabilized zirconia (YSZ) fuel electrode degradation mechanisms in solid oxide electrolysis cells (SOECs) are complicated by the different possible Ni–YSZ microstructures and compositions, and the variations in the H 2 /H 2 O ratio encountered in an electrolysis stack. Here, in this study, we describe a life testing scheme aimed at providing survey results on degradation as a function of the H 2 O–H 2 composition, with life tests carried out at five different steam contents from 90% to 10%. A Ni–YSZ-supported symmetric cell geometry is employed both with and without infiltrated nanoscale gadolinia-doped ceria (GDC). Impedance spectroscopy is utilized to observe changes in electrochemical characteristics during the life test, and a transmission-line-based equivalent circuit is used to model the data. Post-test electrode microstructures were observed. The results suggest that the GDC infiltrant reduces the electrode polarization resistance and provides more stable electrode polarization over a range of conditions.

08 HYDROGEN↗
DOE OSTI2025

Heterogeneous energetic material damage simulator (HEDS): A deep learning approach to simulate damage–sensitivity linkages

Damage in the microstructures of energetic materials (EMs), such as propellants and plastic bonded explosives (PBXs), can significantly alter their response to external loads. Both sensitization and desensitization can occur, causing concerns with safety and performance in the field; predictive models that connect damage and the sensitivity of EMs can enable design and provide confidence in their robustness and reliability. However, modeling of damage evolution is challenging for real microstructures of EMs; samples of damaged EMs are difficult to obtain, thereby hindering experiments and direct numerical simulations to determine the sensitivity of EMs at various stages of damage. Here, we develop an approach to generate synthetic, i.e., in silico produced, damaged microstructures for use in simulations to connect damage levels to sensitivity. The development of the present workflow to generate and impose varying levels of damage in microstructures, known as HEDS (Heterogeneous Energetic Material Damage Simulator), begins with a small set of images of damaged PBXs and combines a collection of deep neural network techniques to generate microstructures with varying levels of damage. By making the synthetic microstructures conform closely to those observed in available real, imaged microstructures, we develop an ensemble of damaged microstructures that can be used for in silico shock experiments. HEDS develops these microstructure ensembles as level set fields, which are directly employed in a sharp interface Eulerian hydrocode where shock simulations are performed to quantify the energy release rate from hotspot fields generated in the microstructure. These capabilities can be useful for the analysis and assessment of changes in the sensitivity of EMs and to design formulations that are less susceptible to damage-induced changes in sensitivity and performance.

Fang, Irene (ORCID:0009000844557122)↗
NASA NTRS1986

Investigation of long-lived eddies on Jupiter

Quasi-geostrophic, two layer models of the Jovian atmosphere are under development; these may be used to simulate eddy phemonena in the atmosphere and include tracer dynamics explicitly. The models permit the investigation of the dynamics of quasi-geostrophic eddies under more controlled conditions than are possible in the laboratory. They can also be used to predict the distribution and behavior of tracer species, and hence to discriminate between different models of the mechanisms forcing the eddies, provided suitable observations can be obtained. At the same time, observational strategies are being developed for the Near Infrared Mapping Spectrometer on the Galileo Orbiter, with the objective of obtaining composition measurements for comparison with the models. Maps of features at thermal infrared wavelengths near 5 micron and reflected sunlight maps as a function of wavelength and phase angle will be obtained. These should provide further useful information on the morphology, composition and microstructure of clouds within eddy features. Equilibrium chemistry models which incorporate advection may then be used to relate these results of the dynamical models and provide addtional means of classifying different types of eddies.

Lewis, S. R.↗
DOE OSTI2020

High-throughput experimentation for microstructural design in additively manufactured 316L stainless steel

In the present study, a combination of high-throughput (HT) and low-throughput (LT) techniques was used to rapidly determine the processing window and generate processing maps for Selective Laser Melting (SLM) of 316L stainless steel. The HT method includes the fabrication of hundreds of hex nut-shaped specimens, each processed with a unique combination of laser power, scanning speed, and hatch spacing. An easily removable scaffolding permitted rapid sample extraction from the base plate, thus saving machining cost and time. Hardness and immersion density measurements were used for HT characterization to identify a processing window for maximum strength and density. Within the defined processing window, a low-throughput (LT) microstructural interrogation of specimens were performed. The microstructural analysis included quantification at various length scales (i.e., grains size and morphology, texture, primary dendrite arm spacing, and melt pool geometry analysis). Microstructure-based processing maps as a function of volumetric energy density were generated. The combination of HT and LT methods produced a predictive relationship between hardness and primary dendrite arm spacing using a Hall-Petch relationship. A model is proposed to explain the dependence of microstructure on the melt pool geometry. Here, the HT method can be applied for the microstructural design of SLM-fabricated components in other alloys.

316L stainless steel↗
NASA NTRSDate not supplied

Simultaneous Development and Robust Optimization of a Microstructure Dependent Material

Recent microstructure characterization techniques combined with Symbolic Regression(SR)analysis has been proven to generate white box plasticity models well suited for incorporation into FEA software.The current work builds upon those efforts and demonstrates the applicability of Sequential Monte-Carlo (SMC) methods within SR analysis to condense model development and robust optimization into a single, co-dependent process. In this project, SMC methods provide a mechanism through which the observed microstructure features and associated variability can be incorporated into the discovery phase of model development and simultaneously recover approximate parameter distributions through SR analysis. The demonstration utilized a data set consisting of tensile test results from a limited number of sample specimens with corresponding EBSD data from which microstructure features were characterized.The maximum threshold stress model in the Visco-Plastic Self-Consistent (VPSC) code developed by Los Alamos National Laboratories was calibrated using mechanical test data.Synthetic volume elements with statistically equivalent microstructure were generated with DREAM3Dbased on the observed EBSD data. VPSC was used to simulate the corresponding tensile test response for each of the synthetic volume elements. The simulated microstructure and tensile test data was used astraining datafor SMC-SR algorithm and the resulting model was validated with data from the original empirical data set.

Karl Garbrecht↗
DOE OSTI2025

Stochastic parametric skeletal dosimetry model for humans: Anatomical-morphological basis and parameter evaluation

Radiation exposure of the hematopoietic system that results in a radiation dose to bone marrow of more than 100 mGy leads to an increase in the risk of leukemia in humans. Excess relative risk of leukemia was observed in cohorts whose members lived in the territories of the Southern Urals that were radioactively contaminated in the 1950s. As part of the dosimetric support of epidemiological studies of these cohorts, an original methodology for stochastic bone dosimetric modeling was developed, termed the Stochastic Parametric Skeletal Dosimetry (SPSD) model. The purpose of this work was to present the anatomical and morphological bases of the SPSD model, which includes an assessment of the parameters of the microstructure of the trabecular bone in the hematopoietic areas of the human skeleton, as well as a description of the macrostructural division (segmentation) of hematopoietic areas into simple bone segments. As a result, an anatomical-morphological basis of the SPSD model was created based on published data. Data collection work included the analysis of original articles, atlases, manuals, monographs and the formation of primary data files. Data on the duration of hematopoiesis in various parts of the skeleton; and data on age-related changes in the microstructure and linear dimensions of human bones and their segments were analyzed. The paper describes the full set of parameters to be used for the dosimetric model for newborns, children aged 1, 5 and 10 years, as well as for adolescents aged 15 years and adults; for the latter, sex differences in bone size were considered. In total, the SPSD model includes 289 unique basic (bone) phantom segments, each of which is described by 7 or more parameters describing the microstructure, thickness of the cortical layer and linear dimensions. Population variability was estimated for each parameter. The approach to SPSD modeling, i.e., the use of simple geometric shapes, was successfully verified using independent datasets on bone masses and volumes.

Science & Technology - Other Topics↗
DOE OSTI2019

Phase and Grain Size Dependence of the Pinning Strength of Nanocomposite Magnets

The pinning of grain interfaces plays an important role in determining the coercivity of nanocomposite magnets. Here, based on pinning effect, a simple model was proposed to correlate the pinning strength with microstructural parameters. A structural factor K has been used to describe the contribution of the phase composition and grain size of hard and soft phases to pinning strength. The model can be used to estimate the pinning strength of nanocomposite magnets, which is important for the design and fabrication of nanocomposite magnets with high coercivity.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Microstructural effects in the simulation of creep of concrete

The influence of the microstructure on the visco-elastic properties of concrete is investigated using finite element simulations at the meso-scale. We first derive a constitutive law for the creep of the cement paste which accounts for both recoverable and permanent deformations, as well as the influence of temperature and internal relative humidity. The model is calibrated on a set of experiments at the cement paste scale, and then validated after upscaling to the concrete scale. The model is then applied to study the influence of the microstructure on the macroscopic creep of concrete. We show that materials with finer particles exhibit less creep, and that the anisotropy of creep can be explained with the shape and orientation of the aggregates. Furthermore, the acceleration of the stress relaxation in the presence of damage is explained by the micro-mechanical interaction between the aggregates, the cement paste, and the micro-cracks.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Lower length scale informed improvements to Bison U-Pu-Zr fuel swelling model

Due to renewed interest in metallic fuels from the U-(Pu)-Zr material system, significant improvements have recently been made to BISON's capability to simulate metallic fuel, particularly in the area of swelling. In this report, lower length scale simulations that have been conducted to inform the engineering-scale models in BISON during FY20 are described. For the high-temperature regions of the fuel that are dominated by the $\gamma$ phase of U-(Pu)-Zr, two new models for swelling have implemented in BISON. Phase-field simulations were conducted to calculate parameters for these and other BISON models that control when gaseous swelling ceases and fission gas release begins. For the low-temperature regions of the fuel dominated by the phase of uranium, microstructurally resolved simulations of pore growth and crystal deformation were performed to understand the effect of irradiation-generated crystal shape changes. Conformally meshed microstructures with pores were simulated with a crystal plasticity model and with a burnup eigenstrain model. Plastic deformation will not cause pore size to increase; burnup eigenstrain (irradiation-induced crystal shape changes) will increase the volume of existing porosity and cause it to become anisotropic in shape. Additional model development work for early-stage fission gas cluster/bubble formation in the $\gamma$ phase were performed, by coupling with defect clustering within cluster dynamics framework. Sensitivity analysis were conducted to identify the critical thermo-kinetic parameters needed for rigorous assessment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1990

Numerical simulation of low Prandtl number turbulent mixing

Numerical simulations of turbulent mixing of strongly diffusive scalar fields were carried out with and without subgrid-scale modeling of the small-scale strain field. For low Reynolds number flows, when the rate of strain field (determined primarily by the small scales) is fully resolved, the scalar microstructure was found to collapse under Batchelor rate-of-strain scaling even for small Prandtl numbers, in agreement with Kerr. For high Reynolds number flows, when small-scale straining is modeled with a subgrid-scale model, the scalar microstructure follows the Batchelor, Howells, and Townsend predictions that the small-scale rate-of-strain is irrelevant.

Gibson, C.↗