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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Resiliency of Degraded Built Infrastructure

Infrastructure resiliency depends on the ability of infrastructure systems to withstand, adapt, and recover from chronic and extreme stresses. In this white paper, we address the resiliency of infrastructure assets and discuss improving infrastructure stability through development of our understanding of cement and concrete degradation. The resiliency of infrastructure during extreme events relies on the condition, adaptability, and recoverability of built infrastructure (roads, bridges, dams), which serves as the backbone of existing infrastructure systems. Much of the built infrastructure in the US has consistently been rated D+ by the American Society of Civil Engineers (ASCE). Aged infrastructure introduces risk to the system, since unreliable infrastructure increases the likelihood of failures under chronic and extreme stress and are particularly concerning when extreme events occur. To understand and account for this added risk from poor infrastructure quality, more research is needed on (i) how the changing environment alters the aging of new and existing built infrastructure and (ii) how degradation causes unique failure mechanisms. The aging of built infrastructure is based on degradation of the structural materials, such as concrete and steel supports, which causes failure. Current work in cement/concrete degradation is based on (i) the development of high strength and degradation resistance concrete mixtures, (ii) methods of assessing the age and reliability of existing structures, and (3) modeling of structural stability and the microstructural evolution of concrete/cement from degradation mechanisms (sulfide attack, carbonation, decalcification). Sandia National Laboratories (SNL) has made several investments in studying the durability and degradation of cement based materials, including using SNL-developed codes and methodologies (peridynamics, PFLOTRAN) to focus on chemo-mechanical fracture of cement for energy applications. Additionally, a recent collaboration with the University of Colorado Boulder has included fracture of concrete gravity dams, scaling the existing work to applications in full sized infrastructure problems. Ultimately, SNL has the experience in degradation of cementitious materials to extend the current research portfolio and answer concerns about the resilience of aging built infrastructure.

36 MATERIALS SCIENCE↗
DOE OSTI2022

BISON Capability to Account for Dopant Sensitivity in Relevant UO 2 Material Models

The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation program aims to develop predictive capabilities using computational methods for the analysis and design of advanced reactor and fuel cycle systems. This program has been supporting the development of BISON, a high-fidelity and high-resolution fuel performance tool at the engineering scale. Incorporation of more physics-based models in BISON for the accident tolerant fuel applications motivated this study. This document details integration of new modeling capabilities in BISON, including: a tensile strength model for uranium dioxide (UO 2 ) fuel to incorporate the microstructural effects (e.g., grain size, fabrication pore size, and porosity), and atomistic-informed creep model for UO 2 fuel that is developed by Los Alamos National Laboratory. Sensitivity analyses are conducted on these models separately as well as a two-dimensional full rod application under normal operating conditions. Lastly, these new modeling capabilities in BISON are exercised in Halden IFA-677.1 and IFA-716.1 assessment cases.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Acceleration of Thermochemistry Solves in MOOSE and Pronghorn

This work focuses on the development and implementation of strategies to accelerate thermochemical calculations within MOOSE-based multiphysics simulations, particularly for applications in MSRs. We highlight the inherent complexity of nuclear materials, which require a multiscale approach to accurately model their behavior across various physical domains, including mechanical, chemical, and thermal phenomena. Thermochemical equilibrium calculations are crucial for predicting material properties and enhancing the fidelity of these simulations. The integration of Thermochimica, a Gibbs energy minimizer, into MOOSE allows for the direct minimization of Gibbs energy at every point on the mesh. However, the computational cost of such integration is significant. To address this, we explored acceleration strategies such as multi-threading support and the use of a thermodynamic ValueCache to reduce redundant calculations. Additionally, we investigated modifications to Thermochimica to enable phase constraints and improve its coupling with phase-field models, which are essential for simulating microstructural evolution and corrosion in MSR. These efforts aim to optimize the computational efficiency and accuracy of multiphysics simulations, thereby supporting the development of reliable and efficient nuclear materials for next-generation reactor technologies.

36 - MATERIALS SCIENCE↗
NASA NTRS1985

Constitutive Cyclic Deformation Behavior in Single-crystal and Directionally Solidified SSME High-pressure Fuel Turbopump Airfoil Materials

The major goal of the project is to correlate mechanical properties with microstructural deformation behavior and to develop models for constitutive response under a variety of monotonic and cyclic loading cycles, temperatures, strain levels, strain rates, and environments. Two alloys are being studied as candidate SSME turbine blade materials. The first is PWA 1480, which is a single-crystal alloy whose nominal composition is reported. The second alloy being studied is D.S. Mar-M 246 + Hf. This is a directionally solidified material, and its nominal composition is also reported. The major areas of interest for the two materials will be slightly different. The single-crystal alloy lends itself well to fundamental deformation studies, since resolved shear stresses on slip planes are all known and only one grain is present. The D.S. material presents an excellent opportunity to study the effects of slightly misaligned grains on deformation behavior. The two materials will be studied by using approximately the same test matrix, so a good degree of direct comparison will also be possible.

Milligan, W. W.↗
NASA NTRS1989

A mechanics framework for a progressive failure methodology for laminated composites

A laminate strength and life prediction methodology has been postulated for laminated composites which accounts for the progressive development of microstructural damage to structural failure. A damage dependent constitutive model predicts the stress redistribution in an average sense that accompanies damage development in laminates. Each mode of microstructural damage is represented by a second-order tensor valued internal state variable which is a strain like quantity. The mechanics framework together with the global-local strategy for predicting laminate strength and life is presented in the paper. The kinematic effects of damage are represented by effective engineering moduli in the global analysis and the results of the global analysis provide the boundary conditions for the local ply level stress analysis. Damage evolution laws are based on experimental results.

Harris, Charles E.↗
NASA NTRS2002

Fracture Mechanisms For SiC Fibers And SiC/SiC Composites Under Stress-Rupture Conditions at High Temperatures

The successful application of SiC/SiC ceramic matrix composites as high-temperature structural materials depends strongly on maximizing the fracture or rupture life of the load-bearing fiber and matrix constituents. Using high-temperature data measured under stress-rupture test conditions, this study examines in a mechanistic manner the effects of various intrinsic and extrinsic factors on the creep and fracture behavior of a variety of SiC fiber types. It is shown that although some fiber types fracture during a large primary creep stage, the fiber creep rate just prior to fracture plays a key role in determining fiber rupture time (Monkman-Grant theory). If it is assumed that SiC matrices rupture in a similar manner as fibers with the same microstructures, one can develop simple mechanistic models to analyze and optimize the stress-rupture behavior of SiC/SiC composites for applied stresses that are initially below matrix cracking.

DiCarlo, James A.↗
DOE OSTI2019

EBSD characterization of metallic nuclear fuel

Grain structure and texture are important in all materials as they influence most mechanical properties. In particular for nuclear materials texture can influence material properties important for reactor performance, such as swelling, yield stress, fracture toughness etc. Moreover such data are of primary importance to develop and validate physics-based models for nuclear fuels based on microstructure evolution during irradiation (e.g. MARMOT). Scanning Electron Microscopy (SEM) coupled with Electron Back Scatter Diffraction (EBSD) has been proven as an effective technique for evaluating grain size, shape, and orientation. However it has been seldom used for nuclear fuels. This has been mostly related to difficulties in handling and preparing such materials for EBSD analyses. Particularly challenging remains sample preparation for metallic irradiated fuels, as they are prone to rapid oxidation. Indeed EBSD analyses require the elimination of any surface defect or oxide layer as the signal arise from 50-100 nm depth in the material. At Idaho National Laboratory (INL) great effort has focused in developing techniques to obtain suitable surfaces for EBSD analyses. In this paper the first results from EBSD analyses obtained from a wide range of nuclear materials will be presented. Sample analyzed included fresh U, U-Zr, Pu-Zr , and U-Mo, including some irradiated fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Digital Twin Model for Advanced Manufacture of a Rotating Detonation Engine Injector

A digital twin material model (DTMM) of an additive manufacturing (AM) process was created to advance the state of the art in rotating detonation engine (RDE) injector design. Current RDE injectors are designed with large pressure drops, enabling a stable and repeatable combustion process. However, this comes at the cost of system efficiency. For the technology to transition to commercial fossil-based power generation, it is important to develop injectors with reduced flow losses. Low-loss injectors are difficult to design and manufacture with conventional manufacturing techniques. AM enables new design options, but the AM manufacturing process must be thoroughly understood to result in a robust design. A DTMM provides the necessary insight by defining the cause-effect relationships between process parameters, microstructure features, and properties. Therefore, a DTMM to support the design and manufacturing process was developed and applied to the design of a new additively manufactured low-loss injector. The injector combustion behavior was characterized through hot-fire tests, and mechanical performance was compared to the DTMM predictions. The two project goals were the successful development of the DTMM and the demonstration of an improved RDE injector design. The RDE injector design and DTMM developments occurred on parallel but dependent paths. The injector was designed to reduce pressure drop by increasing the cross-sectional flow area ratio between the injector air passages and the combustor annulus. This resulted in less structural material, raising the concern that thin members would be susceptible to high-cycle fatigue (HCF) under the periodic loading inherent to an RDE. It was most important for the DTMM to predict behavior in these features; therefore, the injector design concept guided the material thicknesses used in fatigue tests. The DTMM development started by manufacturing a series of coupons over the range of possible AM process variations. A design-of-experiment approach was used to select which process variable combinations gave the most efficient coverage relevant to the injector design space. The microstructure in each of these coupons was characterized, and then computational methods were used to create a numerical model of the correlation between process variables and microstructure. Next, a set of HCF samples were tested to calibrate existing models that map microstructure to HCF performance. Together, these two links formed the DTMM that calculates HCF behavior from AM process variables. Two injector prototypes were additively manufactured. The first injector design strategy aggressively pursued low-loss performance by substantially increasing the oxidizer flow area. The combination of manufacturing lead times and the fatigue testing schedule meant that the DTMM was not available when building this first prototype. Therefore, its process parameters were chosen based on a manual review of the available coupon data. This prototype was built successfully and evaluated in 58 combustion tests. Sustained detonation was achieved with remarkably reduced pressure loss, and some tests even displayed pressure loss characteristics similar to conventional gas turbine combustors. This achieved the project goal of improving RDE injector design. The second injector was manufactured according to the optimized parameters predicted by the DTMM. The flow area modifications of this injector were less aggressive than the first injector since demonstrating low pressure loss was not an objective of the second hot-fire test series. Rather, the test objective was to cause high cycle fatigue failure in the part due to periodic loading from the rotating detonation wave. The observed number of cycles to failure was to be compared to the number predicted by the DTMM and thereby assess the utility of the DTMM in component design. However, the required level of vibration was not obtained during combustion. Therefore, high cycle fatigue was not experienced in the hot-fire tests of the second injector. Fatigue data was obtained by further testing the second injector in a conventional HCF test apparatus. The injector demonstrated HCF strength above the DTMM prediction. In fact, it did not fail and testing was only discontinued due to reaching the end of the period of performance. This points to some success in the project’s primary goal of successfully developing and applying the DTMM to a component design. Implementing the DTMM recommendations for optimal processing parameters led to a part with acceptable properties. The DTMM was also shown to be an efficient correlator of data and to provide insight into the relationship between process settings, microstructure, and property performance. However, the failure of the DTMM prediction to match the experimental result of the injector fatigue test also points to the need to include significantly more data in the model development. In this project, coupons made with identical processing parameters exhibited drastically different properties from each other and from the injector part, which clearly influences the accuracy of a model that predicts performance based on parameters. Uncertainties in the build process must be quantified to develop more robust models. A denser and broader matrix of coupon process and geometry variations, several repeated builds of every point, more in-situ build process measurements, and direct observation of tensile and HCF sample microstructure (as opposed to separate microstructure specimens) are recommendations to improve future AM modeling efforts.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Leveraging a Neural Network-Enhanced Reproducing Kernel Particle Method for Multiphysics Degradation Modeling of Energy Storage Materials

Energy storage materials exhibit strong electro-chemo-mechanical coupling and highly anisotropic material properties, contributing to the formation and propagation of micro-cracking during charge/discharge cycling and resulting in reduced performance and service life. A coupled electro-chemo-mechanical reproducing kernel particle method (RKPM) formulation has been developed to analyze this system. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), pixel-based model construction by RKPM is used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electro-chemo-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in meshing such complex geometries and capturing crack propagation due to mesh dependency. Here, a neural network-enhanced reproducing kernel particle method (NN-RKPM) [1, 2] is introduced to effectively model damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. NN-RKPM is additionally used to inform how crack opening and closure in turn affect the coupled chemical equations and material microstructure. Reference: [1] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, pp 4422-4454, https://doi.org/10.1002/nme.7040, 2022. [2] Baek, J., Chen, J. S., "A Neural Network-Based Enrichment of Reproducing Kernel Approximation for Modeling Brittle Fracture", Computer Methods in Applied Mechanics and Engineering Vol. 410, 116590, 2024.

degradation↗
DOE OSTI2023

Status of Mechanistic Fission Gas Model in High-Burnup Fuel

A desire to increase fuel burnup to decrease the cost of nuclear power plants has led to significant interest within the nuclear industry to develop improved understanding of high-burnup nuclear fuel microstructure and the potential for fuel fragmentation, relocation, and dispersal that contribute to burnup and safe operating limits. This milestone report describes joint research activities and program planning to develop mechanistic models for high-burnup UO 2 microstructure, including both intra- and intergranular gas bubble populations and fission gas release, specifically associated with transient release. This model development is being extensively leveraged against a rapidly growing experimental database of high-fidelity electron microscopy characterization of commercial, light water reactor fuel in the as-irradiated condition as well as that following simulated loss-of-coolant test conditions. This report describes the status of model development, highlights recent microstructural data, and summarizes the data needs to complete initial development and experimental validation of mechanistic models of fission gas and microstructural evolution at high burnup, as well as transient fission gas release.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

An active learning high-throughput microstructure calibration framework for solving inverse structure–process problems in materials informatics

Determining a process–structure–property relationship is the holy grail of materials science, where both computational prediction in the forward direction and materials design in the inverse direction are essential. Problems in materials design are often considered in the context of process–property linkage by bypassing the materials structure, or in the context of structure–property linkage as in microstructure-sensitive design problems. However, there is a lack of research effort in studying materials design problems in the context of process–structure linkage, which has a great implication in reverse engineering. In this paper, given a target microstructure, we propose an active learning high-throughput microstructure calibration framework to derive a set of processing parameters, which can produce an optimal microstructure that is statistically equivalent to the target microstructure. The proposed framework is formulated as a noisy multi-objective optimization problem, where each objective function measures a deterministic or statistical difference of the same microstructure descriptor between a candidate microstructure and a target microstructure. Furthermore, to significantly reduce the physical waiting wall-time, we enable the high-throughput feature of the microstructure calibration framework by adopting an asynchronously parallel Bayesian optimization to exploit high-performance computing resources. Case studies in additive manufacturing and grain growth are used to demonstrate the applicability of the proposed framework, where kinetic Monte Carlo (kMC) simulation is used as a forward predictive model, such that for a given target microstructure, the target processing parameters that produced this microstructure are successfully recovered.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Progress on continuum modeling of lithium–sulfur batteries

While lithium–sulfur batteries are a promising next-generation chemistry devices due to their high theoretical energy density, commercialization has been slow due to low coulombic efficiency and poor cycle life. This review explores the ways in which continuum modeling contributes to the understanding of lithium–sulfur (LiS) battery mechanisms and cell-level performance through the lens of micro- and macroscale phenomena. We examine different approaches to modeling important physical phenomena such as reaction mechanisms, cathode microstructure, shuttling, nucleation and precipitation, and transport limitations. This paper also emphasizes the significance and challenge of connecting typical modeling parameters and assumptions to systems-level metrics of a standard state-of-art high performing lithium–sulfur cell. Particularly important, the considerations for high energy density cells and the areas where continuum models can facilitate better collaboration are discussed. Here, we also summarize a few selected works to highlight experimentally-driven modeling, use of electroanalytical techniques, and parameter identification approaches to enable model-based design and advanced battery management systems.

25 ENERGY STORAGE↗
NASA NTRS1991

The Galactic distribution of free electrons

Various radioastronomical measurements are synthesized here to derive a large-scale Galactic model for the distribution of free electrons and for microstructure in the distribution that seems to be caused by turbulence in the ISM. A two-component axisymmetric model fitted on all scales from 100 km to a few pc, accounts for most of the data. A population of dense, discrete clouds is also needed, and there is some evidence for spiral structure. The model allows better distance estimates for pulsars to be made. The implications of the model for the structure and ionization of the ISM and for the distribution of interstellar turbulence and the diffusion of cosmic rays are discussed.

Cordes, J. M.↗
NASA NTRS2019

Pot-ability Assessment of Litz Wires for High Power Density Electric Motor

An alternative process technique, namely vacuum-assisted axial injection potting (VaAIP), has been developed to pot the Litz wires in the stator winding of high power density electric motors for the future electrified aircrafts. Initial trials of the process showed significant improvement in potting quality with less voids, thus potential improvement in thermal management of the motors. As an initial effort of pot-ability assessment, microstructures, 2-D and 3-D, of the Litz wires including dimensions and distribution of conductor filament, coating, and open spaces; packing patterns; shape/configuration changes of each bundles or the overall cross-sections per degree of twist were determined and quantified successfully. The microstructure analyses were performed not only for effective potting process development but also for more realistic electro-thermal modeling solutions. This paper will present results of the microstructure analyses, potentials of the VaAIP process from the trials, and future plans for scale-up and implementation of the process into a full-scale prototype stator winding.

Electrified aircraft↗
DOE OSTI2023

Additive manufacturing of nickel-based superalloys: A state-of-the-art review on process-structure-defect-property relationship

Fusion-based additive manufacturing (AM) has significantly grown to fabricate Nickel-based superalloys with design freedom across multiple length scales. Several phenomena such as feedstock/energy source/melt pool interactions, solidification and phase transformations occur during fusion-based AM processes of Nickel-based superalloys, which determine the ultimate microstructure and mechanical performance of the built parts. In this review, here we elaborate a comprehensive discussion on AM Nickel-based superalloys and influential factors including feedstock characteristics (powder morphology, chemistry, contamination, flowability, recycling) and AM processing (parameters, and powder spreading/wall/balling/spattering effects) on their microstructure (micro-segregation, phases formations and grain structures), defect generation (sub-surface/internal defects, microcracks, surface roughness, and residual stress). Furthermore, the mechanical properties of AM Nickel-based superalloys such as tensile, creep and fatigue at room/elevated temperatures are analyzed in accordance with the initial, and post processing effects. Additionally, the commonly utilized modeling approaches in literature to predict the microstructure and mechanical behavior of these alloys are highlighted. Finally, the current challenges and mitigation approaches for future research are identified considering the gaps in the AM Nickel-based superalloys.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Compositional Effects on Nickel-Base Superalloy Single Crystal Microstructures

Fourteen nickel-base superalloy single crystals containing 0 to 5 wt% chromium (Cr), 0 to 11 wt% cobalt (Co), 6 to 12 wt% molybdenum (Mo), 0 to 4 wt% rhenium (Re), and fixed amounts of aluminum (Al) and tantalum (Ta) were examined to determine the effect of bulk composition on basic microstructural parameters, including gamma' solvus, gamma' volume fraction, volume fraction of topologically close-packed (TCP) phases, phase chemistries, and gamma - gamma'. lattice mismatch. Regression models were developed to describe the influence of bulk alloy composition on the microstructural parameters and were compared to predictions by a commercially available software tool that used computational thermodynamics. Co produced the largest change in gamma' solvus over the wide compositional range used in this study, and Mo produced the largest effect on the gamma lattice parameter and the gamma - gamma' lattice mismatch over its compositional range, although Re had a very potent influence on all microstructural parameters investigated. Changing the Cr, Co, Mo, and Re contents in the bulk alloy had a significant impact on their concentrations in the gamma matrix and, to a smaller extent, in the gamma' phase. The gamma phase chemistries exhibited strong temperature dependencies that were influenced by the gamma and gamma' volume fractions. A computational thermodynamic modeling tool significantly underpredicted gamma' solvus temperatures and grossly overpredicted the amount of TCP phase at 982 C. Furthermore, the predictions by the software tool for the gamma - gamma' lattice mismatch were typically of the wrong sign and magnitude, but predictions could be improved if TCP formation was suspended within the software program. However, the statistical regression models provided excellent estimations of the microstructural parameters based on bulk alloy composition, thereby demonstrating their usefulness.

MacKay, Rebecca A.↗
NASA NTRS1992

Microstructure-failure mode correlations in braided composites

Explication of the fracture processes of braided composites is needed for modeling their behavior. Described is a systematic exploration of the relationship between microstructure, loading mode, and micro-failure mechanisms in carbon/epoxy braided composites. The study involved compression and fracture toughness tests and optical and scanning electron fractography, including dynamic in-situ testing. Principal failure mechanisms of low sliding, buckling, and unstable crack growth are correlated to microstructural parameters and loading modes; these are used for defining those microstructural conditions which are strength limiting.

Filatovs, G. J.↗