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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Development of a numerical model for simulating stress corrosion cracking in spent nuclear fuel canisters

Abstract Prediction and detection of the chloride-induced stress corrosion cracking (CISCC) in Type 304 stainless steel spent nuclear fuel canisters are vital for the lifetime extension of dry storage canisters. This paper conducts a critical review that focuses on the numerical modeling and simulation on the research progress of the CISCC. The numerical models emphasizing the residual stress, susceptible microstructure, and corrosive environment are summarized individually. Meanwhile, the simulation studies on the role of hydrogen-assisted cracking are reviewed. Finally, a multi-physical numerical model, which combines the different fields is proposed based on our recent investigation.

Materials Science↗
DOE OSTI2020

Enabling fast charging of lithium-ion batteries through secondary- /dual- pore network: Part I - Analytical diffusion model

Battery performance is strongly correlated with electrode microstructural properties. Enabling fast charging of lithium-ion batteries requires improved through-plane ionic diffusion that can be achieved through, among other strategies, structured electrodes with a secondary- or dual-pore network (SPN). In this work, an analytical model investigates the impact of such an SPN on ionic diffusion with a composite electrode, considering various pore-channel geometries and comparing to standard electrodes with identical gravimetric- and volumetric-specific theoretical capacities. Relevant SPN design parameters and tortuosity coefficients are identified according to three optimization objectives that aim to balance the improved overall through-plane diffusion, thanks to the coarse aligned channels, and degraded in-plane diffusion because of the porous matrix densification required to maintain gravimetric- and volumetric-specific theoretical capacities. The model indicates that a relatively low amount of SPN is required and that electrodes with high through-plane tortuosity and low in-plane tortuosity benefit most from such architecture.

25 ENERGY STORAGE↗
NASA NTRS2003

High-Fidelity Micromechanics Model Enhanced for Multiphase Particulate Materials

This 3-year effort involves the development of a comprehensive micromechanics model and a related computer code, capable of accurately estimating both the average response and the local stress and strain fields in the individual phases, assuming both elastic and inelastic behavior. During the first year (fiscal year 2001) of the investigation, a version of the model called the High-Fidelity Generalized Method of Cells (HFGMC) was successfully completed for the thermo-inelastic response of continuously reinforced multiphased materials with arbitrary periodic microstructures (refs. 1 and 2). The model s excellent predictive capability for both the macroscopic response and the microlevel stress and strain fields was demonstrated through comparison with exact analytical and finite element solutions. This year, HFGMC was further extended in two technologically significant ways. The first enhancement entailed the incorporation of fiber/matrix debonding capability into the two-dimensional version of HFGMC for modeling the response of unidirectionally reinforced composites such as titanium matrix composites, which exhibit poor fiber/matrix bond. Comparison with experimental data validated the model s predictive capability. The second enhancement entailed further generalization of HFGMC to three dimensions to enable modeling the response of particulate-reinforced (discontinuous) composites in the elastic material behavior domain. Next year, the three-dimensional version will be generalized to encompass inelastic effects due to plasticity, viscoplasticity, and damage, as well as coupled electromagnetothermomechanical (including piezoelectric) effects.

Pindera, Marek-Jerzy↗
DOE OSTI2023

Python codes for the paper - "Trade-offs in the latent representation of microstructure evolution"

SAND2024-00946O Python codes used in "Trade-offs in the latent representation of microstructure evolution," a manuscript accepted for publication in Acta Materialia, are part of a repository. The code was developed to perform analysis of microstructure evolution. The repository consists of two main directories: models, which train and test models such as autoencoders and diffusion maps, and analysis, which analyzes microstructures. Source code is used to perform dimensionality reduction of microstructure data for analysis of its evolution in time. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Dingreville, Remi↗
DOE OSTI2025

Effect of pore fluid chemistry on the mechanical behavior of a divalent compacted bentonite, an experimental and constitutive study

Ongoing research in isolating high-level nuclear waste and spent fuel has highlighted compacted bentonite as a suitable material for engineered barrier systems in deep geological repositories due to its extraordinary swelling and retention properties. This research focuses on the chemo-mechanical behavior of compacted bentonite exposed to different pore fluids with different concentrations and loading conditions. The study involves swelling pressure and compressibility experiments along with mineralogy analysis employing X-ray diffraction (XRD) and Cation exchange. The tests were conducted on BCV (a Mg/Ca- bentonite) compacted at a dry density of 1.48 ± .02 Mg/m 3 . An advanced chemical-mechanical constitutive model for unsaturated highly expansive clays was adopted to simulate the material response and better understand its behavior. The model is able to account for the main phenomena at both macro and microstructural levels and the interactions between them. The model successfully replicated experimental observations. The XRD analyses support the macroscopic observation, indicating that salinity impacts crystalline swelling as demonstrated by the reduction of basal spacing from 19.27 Å to 15.68 Å when the osmotic suction increases from 0 MPa to 33 MPa. The results suggested that the osmotic pressure generated by the concentration in the pore fluids promotes a reduction in swelling pressures, swelling strains, and crystalline swelling of clay minerals. Also, it affects the pre-consolidation stress and the compressibility of the compacted samples. In conclusion, it was also observed that both solution type and solution concentration impact the clay swelling pressure.

Chemo-mechanical constitutive model↗
DOE OSTI2022

Advanced Microscopy for Characterization of High Burnup Commercial UO 2 Fuel Before and After LOCA Testing

This report presents the results from the microstructural examination of high burnup UO 2 under pre- and post- loss of coolant accident (LOCA) conditions. The work in this report builds and expands upon work previously conducted on high burnup UO 2 fuel at Oak Ridge National Laboratory (ORNL). This work investigates the microstructural evolution that occurs during steady state irradiation of UO 2 , particularly in high burnup fuel. Several high burnup fuel samples were available from historic fuel shipments to ORNL. Microstructural characterization will aid in understanding why the fuel is susceptible to fuel fragmentation and support future work to investigate the formation mechanisms of certain features that form under irradiation. High burnup UO 2 microstructural data is also needed to improve constitutive models intended to predict high burnup fuel fragmentation (HBFF). This report summarizes the microstructural evaluation of these fuel samples to interpret and analyze high burnup fuel microstructures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Multiscale, mechanistic modeling of irradiation-enhanced silver diffusion in TRISO particles

Tristructural isotropic (TRISO) particles are under consideration for use in several proposed advanced nuclear reactor concepts. The silicon carbide (SiC) layer in TRISO acts as a barrier to prevent the release of the fission products. However, despite remarkable retention, silver (Ag) release has been observed from intact particles, which requires investigation since the Ag isotope ( 110m Ag) has a long half-life. Previous work focused on developing a multiscale, mechanistic model for Ag diffusion accounting for temperature and microstructure effect and has been successfully validated. In this work, we expand the previous model to account for irradiation-enhanced Ag diffusivity in SiC and improve its accuracy over a wider grain size and temperature ranges relevant for advanced reactor conditions. A temperature, grain size, and flux dependent diffusivity is therefore derived using the mesoscale code MARMOT and implemented in the fuel performance code BISON. The irradiation-enhanced Ag diffusivity in SiC is compared against experimental data and validated using BISON against Ag release measurements from the Advanced Gas Reactor Fuel Development and Qualification Program (AGR-1 and AGR-2). Herein, we quantify the impact of SiC grain size, irradiation, and temperature on Ag release. In agreement with previous studies, we find accounting for SiC grain size improves agreement between BISON predictions and experimental observations for most cases. In conclusion, we also find that accounting for irradiation improves agreement for cases where Ag release was underestimated, but the impact was less significant than accounting for microstructure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2012

Development of Matrix Microstructures in UHTC Composites

One of the major issues hindering the use of ultra high temperature ceramics for aerospace applications is low fracture toughness. There is considerable interest in developing fiber-reinforced composites to improve fracture toughness. Considerable knowledge has been gained in controlling and improving the microstructure of monolithic UHTCs, and this paper addresses the question of transferring that knowledge to composites. Some model composites have been made and the microstructures of the matrix developed has been explored and compared to the microstructure of monolithic materials in the hafnium diboride/silicon carbide family. Both 2D and 3D weaves have been impregnated and processed.

Johnson, Sylvia↗
DOE OSTI2019

Modeling of the Kinetics of Carbonitride Precipitation Process in High-Strength Low-Alloy Steels Using Cellular Automata Method

Proposition of a cellular automata (CA) model of carbonitride precipitation to simulate image of microstructure in HSLA steels and to predict the mechanical properties is presented in the paper. CA model proved to be very efficient in modeling various phenomena in material science. Numerical modeling played an important role in development of new processing technologies taking advantage of precipitation. By modeling, we mean a mathematical description of the relation between the main process variables and the resulting material properties, based on sound physical principles. In microalloyed steels, the microalloying elements Ti, Nb and V are added in order to control their microstructure and mechanical properties. High chemical affinity of these elements for interstitials (C, N) results in precipitation of binary compound, nitrides and carbides and products of their mutual solubility—carbonitrides. The model accounts for an increase in dislocation density due to plastic deformation and predicts kinetics of precipitation as well as shape of precipitates.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Deep operator network surrogate for phase-field modeling of metal grain growth during solidification

A deep operator network (DeepONet) has been constructed that generates accurate representations of phase-field model simulations for evolving two dimensional metal grain morphology growing from melt. These representations serve as lower resolution, computationally efficient stand-ins for quick parameter space exploration of solutions to the the Allen-Cahn equations that dictate the phase-field model simulations. The experimental target for the phase-field model is a uranium casting system cooling a 434 g uranium charge from a maximum temperature of 1400° C at an average rate of 30° C / min , traversing the crystallographic phases of the pure metal. Experimental parameters inform the phase-field model, whose higher resolution computational model solutions are used to train the DeepONet in a given parameter space with the aim of developing a faster, more efficient method for predicting the solidifying metal's microstructure at different potential experimental values. The final DeepONet generates high accuracy, lower resolution predictions with cumulative relative approximation error over all timesteps of less than 0.5%, while ensuring solutions remain within physically feasible ranges. Further, these relative error values are comparable with other state-of-the-art DeepONet models for microstructure evolution, while significantly reducing the amount of training data required. Training a convolutional neural network simultaneously with the DeepONet, enforcing realistic values at the complex metal grain boundaries, and mathematically encoding boundary conditions into the structure of the DeepONet improved prediction accuracy and computational efficiency over a standard DeepONet model.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Patch-Based Convolutional Neural Networks for Multiple Microstructural Features Detection in FIB-SEM Micrographs of Irradiated Nuclear Fuel

Focused ion beam scanning electron microscopy (FIB-SEM) tomography has increasingly been utilized for acquiring three-dimensional (3D) microstructure features at the sub-micron scale in irradiated nuclear materials. This technique involves sequential ion beam slicing followed by electron beam imaging and compositional mapping using energy dispersive spectroscopy (EDS). Despite its growing use, several challenges persist. These include the time-intensive nature of data collection of EDS data, difficulties in distinguishing between various microstructures, and issues with image alignment. These challenges currently limit the broader application of FIB-SEM tomography in the field. To overcome these limitations, we propose using convolutional neural networks (CNNs) to automate microstructure identification in SEM images. Our study introduces a new framework for identifying microstructures in irradiated U-10Zr (wt. %) metallic fuel with limited annotated data. The framework includes the creation of a reliable annotated dataset with paired SEM and ground truth data from EDS maps, the applications of CNNs for microstructure identification, and the validation of model performance. Specifically, we employed the Segment Anything Model (SAM) to align SEM images with corresponding EDS maps and focused ion beam (FIB) tomography SEM data. We evaluate several models, including Patch-based U-Net, Attention U-Net, and Residual U-Net, finding that patch-based U-Net exhibits superior segmentation performance and consistency. This approach reduces reliance on EDS detectors and aids in accelerating nuclear material analysis process, highlighting the potential of advanced deep learning techniques to improve microstructural understanding in nuclear material. This is the first framework to integrate SAM and Patch-based CNN models for semantic segmentation of irradiated nuclear materials, with potential applicability to other tomography datasets.

36 - MATERIALS SCIENCE↗
DOE OSTI2019

Hot Deformation Behavior and Processing Map of a Fe-11Mn-10Al-0.9C Duplex Low-Density Steel Susceptible to κ-Carbides

The hot deformation behavior of a Fe-11Mn-10Al-0.9C duplex low-density steel has been investigated, based on a series of isothermal compression tests at temperatures of 800-1100 °C and strain rates of 0.001-10 s{sup −1}. At relatively lower temperatures, with austenite decomposing, continuous dynamic recrystallization of ferrite and the formation of inter-granular κ-carbide were responsible for significant softening. At high deformation temperature where austenite was a dominant phase, dynamic recrystallization (DRX) is the restoration mechanism. Processing maps were developed at different plastic strains employing dynamic materials model and further verified through microstructural characterization. The optimal hot deformation condition at a large strain (0.7) was identified as deformation temperature of 950-1100 °C and strain rate of 0.01-1.0 s{sup −1}. In this domain, the original coarse grains could be replaced by the fine and uniform recrystallized grains, indicating that the high efficiency was dissipated by DRX. Meanwhile, two instable regions resulted from the formation of inter-granular κ-carbides and necklace structure should be avoided during hot processing.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Hot Deformation Behavior and Processing Maps of As-Cast Hypoeutectic Al-Si-Mg Alloy

The hot deformation behavior of as-cast hypoeutectic Al-Si-Mg alloy has been investigated through hot compression tests at temperatures between 573 and 773 K and the strain rate of 0.001-1 s{sup −1}. A modified Hansel-Spittel constitutive model is proposed, which takes the effect of strain rate on strain hardening into account. The processing maps are established based on the dynamic material model and the Murty criterion. Microstructure observations show that dynamic recovery dominates the dynamic softening behavior, and recrystallized grains are found in the sample tested at 773 K with strain rate of 0.01 and 0.001 s{sup −1}. The size of Si particles decreases by about 64.73% with the effective strain increasing from 0 to 1.2. The optimal hot processing parameters of as-cast hypoeutectic Al-Si-Mg alloy are established based on the processing maps.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Slip localization behavior at triple junctions in nickel-base superalloys

Incipient slip localization in the vicinity of hundreds of grain boundary triple junctions (TJs) in a lightly deformed nickel-base superalloy IN718 is studied using a combination of three-dimensional (3D) crystal plasticity finite element (CPFE) modeling, high resolution digital image correlation (HR-DIC) and 3D electron back-scatter diffraction tomography (3D EBSD). A 3D reconstruction method enables identification of thousands of TJs and correspondence of any observed slip bands with their originating TJ lines below the specimen surface. Here, we present a large-scale CPFE model of the experimental 3D microstructure composed of high-fidelity representation of the TJ lines and the boundaries and interiors of the parent grains and use it to calculate the local micromechanical response and slip activity of all TJs at the onset of macroscopic yielding. Statistical analysis of the calculated quantities reveal TJs develop larger stress concentration and grain-average re-orientation than grain interiors and grain boundaries, however no substantial differences in cumulative slip were found among these microstructural regions. We find that TJs with observed slip bands generate lower grain-average re-orientation, fewer active slip systems, and more localized slip on a single system than those without. The distinctions in the reorientation and slip activity are stronger in TJs that experience more intense slip.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Influence of fine-scale B2 precipitation on dynamic compression and wear properties in hypo-eutectic Al0.5CoCrFeNi high-entropy alloy

The near equiatomic high-entropy alloys based on Al, Co, Cr, Fe, Ni have provided a novel microstructural template for alloy design. The face-centered cubic (FCC) matrix strengthened by body-centered cubic (BCC) based ordered B2 precipitates can be used to develop a new generation of precipitation strengthened alloys. The present study focuses on an Al0.5CoCrFeNi hypo-eutectic alloy consisting of an as-solidified FCC+B2 microstructure. Guided by solution thermodynamic modeling, this alloy has been isothermally aged for solid-state precipitation of a high fraction of fine-scale intragranular B2 particles. The dynamic compressive strength, hardness, and sliding wear response of the alloy as a function of B2 phase fraction is examined. The flow stress at 0.02% true strain increased from ~ 670 MPa to ~1350 (102%) MPa, the ultimate compressive strength increased from ~1160 MPa to 1500 MPa (20%), and the wear resistance increased more than 5 times with progressively increasing phase fraction of B2 precipitates.

Gwalani, Bharat↗
DOE OSTI2024

Analysis of radially resolved thermal conductivity in high burnup mixed oxide fuel and comparison to thermal conductivity correlations implemented in fuel performance codes

The thermal diffusivity and thermal conductivity of high burnup (19 % FIMA) mixed oxide (U, Pu)O 2 nuclear fuel has been measured along the radial direction using a thermoreflectance-based method. Measured thermal conductivity exhibits a notable radial variation consistent with the expectations that a large temperature gradient across the annular fuel pellet leads to a heterogeneous microstructure. A common fuel performance model of thermal conductivity, the Lucuta-Inoue model, is used to analyze the measured thermal conductivity profile. Further, this model adequately captures the radial dependence of thermal conductivity except in the periphery. The analysis suggests that the characteristic radial shape of the thermal conductivity profile follows the burnup profile within the fuel pin. In the periphery, the high burnup structure is formed and the conductivity model, not capturing this effect, likely overestimates the thermal conductivity.

36 MATERIALS SCIENCE↗
DOE OSTI2021

From classical thermodynamics to phase-field method

Phase-field method is a density-based computational method at the mesoscale for modeling and predicting the temporal microstructure and property evolution during materials processes. The focus of this article is on connecting the most common phase-field equations to the very basic first and second laws of classical thermodynamics through rudimentary irreversible thermodynamics. It briefly discusses the relations of the continuum phase-field equations to their counter parts at the microscopic and atomic levels. It attempts to clarify the contributions of long-range elastic, electrostatic, and magnetic interactions to domain structure evolution during structural, ferroelectric, and ferromagnetic phase transformations by separating order parameter changes due to the presence of quasi-static fields and those arising from phase transformations. A few examples are presented to demonstrate the possibility of employing the phase-field method to provide guidance to designing materials for optimum properties or discovering novel mesoscale phenomena or new materials functionalities. Here, the article ends with a brief perspective on a number of potential future directions on the development and applications of phase-field method beyond its traditional applications to structural alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Synchrotron Imaging of Pore Formation in Li Metal Solid-State Batteries Aided by Machine Learning

High-rate capable, reversible lithium metal anodes are necessary for next generation energy storage systems. In situ tomography of Li/LLZO/Li cells is carried out to track morphological transformations in Li metal electrodes. Machine learning enables tracking the lithium metal morphology during galvanostatic cycling. Nonuniform lithium electrode kinetics are observed at both electrodes during cycling. Hot spots in lithium metal are correlated with microstructural anisotropy in LLZO. Mesoscale modeling reveals that regions with lower effective properties (transport and mechanical) are nuclei for failure. Advanced visualization combined with electrochemistry represents an important pathway toward resolving non-equilibrium effects that limit rate capabilities of solid-state batteries.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗