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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Integrated Computational Materials and Mechanical Modeling for Additive Manufacturing of Alloys with Graded Structure Used in Fossil Fuel Power Plants

Wire-arc additive manufacturing (WAAM) has demonstrated its unique capability of producing large-size alloy components with a significantly reduced fabrication time and enhanced geometry design freedom. In this project, the team has developed an ICME (Integrated Computational Materials Engineering) modeling framework, which supports the WAAM of the AUSC (Advanced Ultra-Supercritical) power plant components. The manufacturing design has been applied to Inconel 740H, steel P91, as well as the dissimilar alloy components between steel P91 and Inconel 740H. The ICME model framework is developed by considering two types of modeling. First, mechanistic modeling has been applied to control the printing quality and understand the sequence of the dissimilar printing of the wall structure. The following models have been included in the developed ICME framework: finite element thermal model, grain structure model, residual stress simulation, crystal plasticity model, CALPHAD-based precipitation kinetic model, phase stability prediction, thermal expansion predictive model, and heuristic creep model. Secondary, a physics-based machine learning model has also been developed based on the ICME model structure. The machine learning model development is based on the ICME model prediction with calibration of the experiments. In addition, the WAAM has been utilized as a high-throughput experimental tool rapidly generating a gradient of alloy composition to facilitate experimental database generation for process-structure-property relationships. Such a database directly supported the ICME-enhanced machine learning, which further assisted in intermediate composition block design between P91 and 740H. A high-throughput screening study of the oxidation resistance has been performed based on such high-throughput experimentation. Based on the computational design, several dissimilar alloy manufacturing with post-heat treatment have been performed with a comprehensive evaluation of mechanical performance, including hardness mapping, yield strength, creep resistance. In this project, the single component of P91 and 740H processed by WAAM after heat treatment designed by ICME has demonstrated higher performance in yield strength and creep resistance than the wrought materials. The P91 sample prepared by WAAM with ICME-designed heat treatment performs better than P92 in creep resistance. The designed graded alloy printing with intermediate block shows a promising performance that exceeds the traditional welding. Moreover, the current research indicates the high need for location-specific design analysis with uncertainty quantification, an important topic that deserves more dedicated research. The achievement of this project demonstrated the promising future of WAAM in structural alloy manufacturing for energy power plant development. Successful printing requires synergetic efforts made by manufacturing, mechanical, and materials sciences.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Multi-modal Approach to Modeling Creep Deformation in Nickel-base Superalloy

This study developed the multi-modal modeling approaches to elucidate the physical and overall mechanical properties of two complex alloy systems of Ni-based Superalloys, namely Haynes 282 and Inconel 740. The overall strategies employed systematically in different scales of modeling are based on the common structural framework of the multi phases that made up the Ni-based Superalloys, namely the matrix phase of the Gamma ($\gamma$) phase which is embedded with ordered Gamma prime ($\gamma$’) precipitates and decorated with the dispersions of mostly carbide precipitates. With this in mind, we had set up the modeling platforms to incorporate a wide range of scales, starting from electronic structures to the continuum level via the crystal plasticity model.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Characterization and Modeling of Deformation Induced Damage in Titanium Alloys

Over the lifetime of their DOE support, and specifically during the past funding cycle, the PIs have primarily focused on ambient temperature studies of the mechanisms of heterogeneous deformation and shear transfer at GBs. The PIs have developed and applied a broad array of experimental approaches complemented by advanced computational methods and simulations to enable new understanding of GB shear transfer, and a new approach for modeling this behavior at the mechanistic level has been established. The PIs have examined how slip behavior differs on the surface and interior of polycrystals using a variety of approaches. Some of the associated data has been used to generate 3-D models of experimentally-characterized microstructures that both support interpretation of deformation mechanisms as well as reveal where modeling needs to be improved to more closely agree with what is experimentally observed. The PIs progress in constitutive modeling of crystal plasticity has introduced explicit GB resistance to shear that depends on the mutual geometry of active slip systems. This past work places the PIs in a good position to take on the challenges associated with mechanistically understanding the interplay between GBS and slip interactions.

42 ENGINEERING↗
DOE OSTI2022

High Throughput Computational Framework of Materials Properties for Extreme Environments

This project aims to establish a framework capable of efficiently predicting the properties of structural materials for service in harsh environments over a wide range of temperatures and over long periods of time. The approach is to develop and integrate high throughput first-principles calculations in combination with machine learning (ML) methods, perform high throughput CALPHAD (calculations of phase diagrams) modeling, and carry out finite element method (FEM) simulations. Relevant to high temperature service in fossil power system, nickel-based superalloys such as Inconel 740 and Haynes 282 as well as the associated (Ni-Cr-Co)-Al-C-Fe-Mn-Mo-Nb-Si-Ti system, were investigated. The present framework was built on the concept of phase-based property data, in which properties of individual phases are modeled as a function of internal and external independent variables. This project established an open-source infrastructure with the following capabilities: (1) High throughput implementation of first-principles calculations at finite temperatures and variable compositions using both accurate phonon calculations and the efficient Debye model for thermodynamic properties, elastic constants, diffusion coefficients, vacancy formation, stacking and twin faults, and dislocation mobility; i.e., using the developed code DFTTK; (2) Machine learning capabilities to predict the above properties so that the number of first-principles calculations can be significantly reduced; e.g., using the developed code SIPFENN; (3) High throughput CALPHAD modeling of the above properties as a function of temperature and composition using our unique capability based on ESPEI and PyCalphad; (4) New capabilities to predict the stress-strain behavior of individual phases; and (5) New models for tensile strength prediction in common FEM software with the crystal plasticity finite element simulations (CPFEM).

, Ni-based superalloys↗
DOE OSTI2023

A mechanistic model for creep and thermal aging in Alloy 709

This report describes a physics-based model for creep and thermal aging in Alloy 709. Alloy 709 is an advanced austenitic alloy, targeted for use in future Sodium Fast Reactors (SFRs) and other advanced reactors. The material has superior high temperature properties compared to currently qualified 316 and 304 stainless steels. However, the available creep and thermal aging test database for Alloy 709 is significantly more limited compared to the historical materials. The physics-based model developed here is one way to accelerate the qualification of the material by providing more accurate long-term predictions for creep properties and thermal aging, compared to current empirical time-extrapolate techniques. The crystal plasticity finite element model is used to predict the deformation and failure of alloy 709. The same setup for the CPFE model is used in both the baseline model calibration process and the simulation campaigns for parameter inference. Specific constitutive choices are made for Alloy 709 to capture the primary deformation mechanisms. The dislocation creep formulation developed by Hu and Cocks is extended to account for coupled precipitation formation and the grain boundary cavitation model developed by Sham, Needleman, et al. is used to model grain boundary cavitation-induced failure. A novel update algorithm is proposed to render the semi-discrete constitutive update for the Sham-Needleman model unconditionally stable. A progressive calibration approach is adopted based on the observations that several types of material responses can be effectively decoupled. A surrogate model is trained based on full-fledged CPFE simulations to accelerate the forward model evaluations, and stochastic variational inference (SVI) is used to calibrate the unknown microstructural model parameters. The calibrated mechanistic model is used to predict the long-term creep life of Alloy 709, and the predictions are compared against classical empirical approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Irradiation creep model for α-Fe: Dislocation climb in the presence of stress fields (Final Report)

Irradiation creep is known to be an important process for structural materials in nuclear environments, potentially leading to creep failure at temperatures where thermal creep is generally negligible. While there is a great deal of data for irradiation creep in steels and zirconium alloys in light water reactor conditions, much less is known for first wall materials under fusion energy conditions. Lacking suitable fusion neutron sources for detailed experimentation, modeling, and simulation can help bridge the dose-rate and spectral-effects gap and produce quantifiable expectations for creep deformation of first wall materials under standard fusion conditions. In this work, we present a comprehensive model for irradiation creep created from merging a crystal plasticity representation of the dislocation microstructure and a defect evolution simulator that accounts for the entire cluster dimensionality space. Both approaches are linked by way of a climb velocity that captures dislocation-biased defect absorption and a dislocation strengthening term that reflects the accumulation of defect clusters in the system. We carry out our study in Fe under first wall fusion reactor conditions, characterized by a fusion neutron spectrum at temperatures between 300 and 800°K.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Predicting Failure Using Deep Learning SAND Report

Accurate prediction of ductile failure is critical to Sandia’s NW mission, but the models are computationally heavy. The costs of including high-fidelity physics and mechanics that are germane to the failure mechanisms are often too burdensome for analysts either because of the person-hours it requires to input them or because of the additional computational time, or both. In an effort to deliver analysts a tool for representing these phenomena with minimal impact to their existing workflow, our project sought to develop modern data-driven methods that would add microstructural information to business-as-usual calculations and expedite failure predictions. The goal is a tool that receives as input a structural model with stress and strain fields, as well as a machine-learned model, and output predictions of structural response in time, including failure. As such, our project spent substantial time performing high-fidelity, three-dimensional experiments to elucidate materials mechanisms of void nucleation and evolution. We developed crystal-plasticity finite-element models from the experimental observations to enrich the findings with fields not readily measured. We developed engineering length-scale simulations of replicated test specimens to understand how the engineering fields evolve in the presence of fine-scale defects. Finally, we developed deep learning convolutional neural networks, and graph-based neural networks to encode the findings of the experiments and simulations and make forward predictions in time for structural performance. This project demonstrated the power of data-driven methods for model development, which have the potential to vastly increase both the accuracy and speed of failure predictions. These benefits and the methods necessary to develop them are highlighted in this report. However, many challenges remain to implementing these in real applications, and these are discussed along with potential methods for overcoming them.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Simulating the effect of grain structure and porosity on creep for powder bed fusion 316H

This report details results from modeling studies focused on identifying the potential factors influencing creep performance of 316H stainless steel manufactured using Laser Powder Bed Fusion (LPBF), with a focus on experimentally-observed and predicted differences between the response of the AM material and conventionally manufactured wrought 316H. The studies presented here systematically look at the role of grain structure, porosity and texture in the anisotropic creep behavior of the material under conditions expected in high temperature advanced nuclear reactors. A physics-based Crystal Plasticity Finite Element modeling approach has allowed us to look at these factors in isolation and study their role in the material's long-term deformation behavior. An update to the precipitation model used in the constitutive framework for 316H is also presented here, with the aim of improving the accuracy of our results from this modeling effort. This work is a step in the direction of gaining mechanistic understanding of the long-term deformation behavior of LPBF 316H, helping us model its long term performance and reducing the qualification time for the material.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Uncertainty Quantification of Fatigue Behavior of Rough AM Surfaces and Microstructures to Enable Hydrogen Gas Turbine Combustion

Modification of fossil-fueled industrial gas turbines to accept no/low carbon fuels (Hydrogen, H2/natural gas blends) is a significant undertaking. Successful deployment of this technology sits at the intersection of three design criteria (1) new functional fuel injectors that can burn these fuels, (2) manufacturability to meet cost and time-to-market targets, and (3) durability in the harsh environment of an operating turbine. Additive manufacturing (AM) provides accelerated product development. However, uncertainty remains around the durability of parts with rough AM surfaces. A fully experimental approach towards quantifying fatigue performance of rough AM microstructures is costly and laborious. Instead, Solar Turbines Incorporated (Solar) proposes the use of a crystal plasticity finite element (CPFE) model to quantify the factors that drive AM surface fatigue behavior. Solar will use the CPFE results, along with targeted experimental data, to train a computationally efficient surrogate model that can be incorporated into existing turbine part lifing methods.

08 HYDROGEN↗
DOE OSTI2025

Simulation of Creep Deformation and Failure in Graded AM Microstructures

This report describes modeling tools and techniques developed to simulate the long-term material performance of 316H stainless steel manufactured using Laser Powder Bed Fusion (LPBF). A physics-based Crystal Plasticity Finite Element model is used to simulate creep in microstructures and to study the roles of grain morphology, porosity, and texture. We describe our modeling methodology, including an orientation-mapping technique to capture the spatially varying crystallographic orientation that results from the build conditions. Our study of microstructural features shows that AM microstructures produced by LPBF tend to creep faster in the build direction, while texture and grain boundaries strengthen the transverse directions. However, when grain-boundary porosity and the consequent cavity growth are included in the model, the transverse directions begin to creep faster. In examining texture, the results indicate that spatially varying orientation arising from the build conditions increases anisotropy in the material, making it critical to account for orientation gradients in the material to accurately model its mechanical behavior. We also describe a material-model calibration campaign in which we calibrated the constitutive model specifically for LPBF 316H stainless steel at 725℃ for both solution-annealed and as-built conditions. Finally, these tools and techniques are used to model creep in microstructures representing different regions of an LPBF material with graded microstructure, owing to intentional variation in processing conditions. The creep simulation results show good agreement with experimental data across all three microstructures, with future work planned to study rupture in the material.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Surrogate Model Integration with MOOSE XFEM for Creep Crack Growth

Ferritic-martensitic steels are key structural materials for advanced reactors but experience time-dependent deformation and damage under prolonged high temperature and irradiation, leading to creep-driven crack initiation and growth. High-fidelity models—crystal plasticity with irradiation mechanisms, phase-field for microstructural evolution, and continuum-damage viscoplasticity—capture the underlying physics but are too computationally intensive for broad design-space exploration and uncertainty quantification. This milestone advances a scalable alternative by integrating a microstructure-sensitive surrogate creep model into the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework and extending it to fracture via the extended finite element method (XFEM). The surrogate model, developed with collaborators at Sandia and Los Alamos National Laboratories, maps relevant microstructural descriptors to the viscoplastic response of HT9. We embed this surrogate within a coupled deformation-damage workflow in MOOSE/XFEM to simulate creep-driven crack initiation and propagation. Implementation enhancements include updates to the material interface, a plastic correction phase involving microstructure evolution, and fracture criteria to ensure numerical robustness and compatibility with the surrogate structure. Demonstrations on canonical creep benchmarks spanning uniaxial and multiaxial states show that the surrogate reproduces key trends of high-fidelity models while substantially reducing computational cost. The resulting capability bridges physics fidelity and performance, providing a practical path to a predictive, microstructure-aware assessment of creep and fracture in reactor materials.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

LAROMance Grade 91 Model Integration in NEML2

New reactor designs are targeting higher operating temperatures for increased thermal efficiency when compared to the current fleet of light water reactors. Designing structural components for these high temperature environments with reliable long-term operations requires material models that can accurately capture the deformation mechanisms active in these environments. The LAROMance surrogate material models are based on a database of mechanistic crystal plasticity simulations for high-temperature conditions. Inputs to the LAROMance models reflect the microstructural pedigree of the material, like dislocation densities and precipitate contents. Based on the evolution of these microstructural features, the LAROMance model provides the engineering scale constitutive model response. The LAROMance model was recently parameterized for Grade 91, a high temperature alloy. In the present work, the Grade 91 LAROMance model is implemented in the New Material Model Library, version 2 (NEML2). NEML2 provides a modular way to build material models from smaller blocks and was developed to vectorize the material update to efficiently run on modern computational architectures with graphics processing unit accelerators. NEML2 constitutive models can be used in simulations based on the multiphysics object-oriented simulation environment (MOOSE). This report provides details on the implementation of the Grade 91 LAROMance model in NEML2 and its verification of engineering scale finite element simulations in MOOSE.

42 - ENGINEERING↗
DOE OSTI2025

SEM/EBSD Characterization of Baffle-Former Bolts Designated for High Energy X-ray Microscopy Studies at the Advanced Photon Source

This report documents the microstructural and surface characterization of two high-fluence baffle-former bolts (BFBs) harvested from a commercial pressurized water reactor (PWR) after nearly four decades of service. These bolts experienced extreme conditions including high neutron fluence, elevated temperatures, corrosive primary water, and sustained mechanical loads, all of which contribute to degradation mechanisms such as irradiation-assisted stress corrosion cracking (IASCC). Using scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD), the study assessed bulk and near-surface microstructures, grain boundary characteristics, and in-service oxide layers. The results revealed significant differences between bolts exposed to 41 dpa and 29 dpa, including differences in recrystallization extent, deformation structures, and oxidation morphology. These findings establish critical baseline data for integration with advanced synchrotron-based high-energy X-ray microscopy (HEXM) and computational crystal plasticity models. Ultimately, the work supports improved mechanistic understanding and predictive capability regarding the long-term performance of reactor core internal components.

Lach, Tim [Oak Ridge National Laboratory (ORNL), O↗
DOE OSTI2026

Non-conformal interface-cohesive modeling with the shifted boundary method

The accurate simulation of boundary- and interface-dominated problems on complex geometries remains challenging when boundary- or interface-fitted meshes are difficult to generate, particularly for curved boundaries, polycrystalline microstructures, and dense interface networks. The Shifted Boundary Method (SBM) alleviates this meshing burden by shifting the enforcement of boundary conditions from the true boundary to a nearby surrogate boundary and recovering the effect of the true boundary through geometric correction terms, thereby enabling standard finite element spaces on non-boundary-fitted meshes. In this report, we develop a general shiftedboundary and shifted-interface framework within the open-source MOOSE framework. We first present a general SBM implementation for complex geometries on non-boundary-fitted meshes. We then adopt the Shifted Interface Method (SIM) for internal interfaces and develop a unified shifted-interface treatment in which the interface law is enforced on a surrogate interface and the effect of the true interface is recovered through shifted jumps, fluxes, and tractions. This perspective brings scalar thermal-contact and vector-valued cohesive-zone mechanics into a single framework, the latter realized as the Shifted Cohesive Zone Method (SCZM) and coupled with history-dependent constitutive models from NEML2. We further extend the MOOSE mesh infrastructure to support cohesive-zone calculations on distributed meshes. The framework is verified and demonstrated through three progressive studies: Poisson’s equation on a smoothed starshaped domain, a manufactured thermal-contact problem on a non-interface-fitted mesh, and a two-dimensional polycrystalline representative volume element combining crystal plasticity with cohesive grain-boundary interfaces. Across these studies, the shifted formulations reproduce boundary- and interface-fitted reference solutions with high fidelity, indicating that the proposed framework provides an accurate and efficient route to boundary- and interface-dominated simulations on arbitrary geometries without requiring fitted meshes.

Yang, Cheng-Hau↗
DOE OSTI2024

Nanoindentation Stress Relaxation to Quantify Dislocation Velocity–Stress Exponent

This work reports a new methodology using indentation stress relaxation to characterize the dislocation velocity–stress exponent. Through the indentation stress relaxation process, the dislocation structure builds up at the rate governed by dislocation velocity, which is a function of the externally applied stress. The relationship between the dislocation velocity and stress can thus be derived from the indentation stress relaxation data of the stress as a function of time. In this study, instrumented nanoindentation stress relaxation experiments were performed on pure aluminum samples, following three different initial displacement rates of 100, 400, and 800 nm/s. Based on the scaling properties of dislocation kinetics, the data were interpreted to derive a dislocation velocity–stress exponent of 2.5 ± 0.5 for room-temperature aluminum. Crystal plasticity finite-element simulations were performed to illustrate the sensitivity of the proposed nanoindentation stress relaxation methodology to the dislocation velocity–stress exponent value.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Sensitivity Study of Multiscale and Phenomenological Elasto-Viscoplastic Grade 91 Material Models for Component-Scale Response

Many advanced nuclear reactor concepts currently being developed are targeting higher operating temperatures relative to the current fleet of light water nuclear reactors, for efficiency gains and other operational considerations. The design of high temperature structural components with reliable long-term operational performance will depend on material models that accurately capture the inelastic deformation mechanisms active in these environments. In this work, we perform a detailed parameter sensitivity analysis of two unified elasto-viscoplastic Grade 91 material models capable of capturing long term high temperature creep deformation. The first model is a phenomelogical material model from the Nuclear Engineering Material Library (NEML) developed at Argonne National Lab. The NEML model parameters and their uncertainty were fit to a range of Grade 91 experimental data using Bayesian Markov Chain Monte Carlo analysis. The second model is a LAROMance data-driven surrogate material model developed at Los Alamos National Lab. The LAROMance model is fit to a large database of responses produced by a mechanistic crystal plasticity based polycrystal model. Parameters for the LAROMance surrogate material model reflect the pedigree of the Grade 91 microstructure. Both material models have been integrated into the Grizzly code, based on the open-source MOOSE multiphysics simulation framework, to simulate both the progression of aging mechanisms and the effects of that aging on nuclear power plant structures. Grizzly is used analyze a three-dimensional Grade 91 piping system to compare the long-term inelastic response predicted by these two fundamentally different models and assess the sensitivity of the material model input parameters on this quantity of interest.

42 ENGINEERING↗
DOE OSTI2024

Femto-second Laser’s Enabling New Length Scale Fabrications for Rapid Post Irradiation Examination of Materials: Concluding LDRD Project Poster

Mechanical testing campaigns are required to qualify materials for advanced reactor conditions, yet economical and safety limitations restrict the number of standardized mechanical tests that can be performed. Reducing the size of the sample is one approach to addressing these challenges and to accelerating testing. Previous research has shown that smaller mechanical test samples produce higher yield and ultimate stress values compared to values measured from standard sample sizes: the “smaller is stronger” effect. Specimens used in accelerated material testing campaigns must reflect bulk material performance to enable engineering scale material property measurement. The objective of this research project was to determine if engineering scale mechanical behavior—the yield stress—could be measured with micro-tensile test samples smaller than traditional standard testing geometries. The relationship between yield stress and sample size was explored with two different nuclear-relevant structural materials: Zircaloy-4 and tungsten. Mechanical testing of both metals demonstrated decreasing yield stress values with increasing sample gauge size across three different sizes. Yield stress values from the largest gauge size, fabricated with a femto-second laser ablation system, approach bulk material yield stress values reported in published literature. Preliminary analysis of the tungsten samples indicates the yield stress value depends on the grain characteristics within the gauge section, in addition to the gauge size. Accompanying modeling efforts, including response surface generation and crystal plasticity approaches, further demonstrated that the size of the sample gauge section alone cannot explain the change in yield stress values.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Coupling Microstructural Evolution Simulations to Material Property Degradation Predictions for Plasma-Facing Materials

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500 C to 1500 C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 D/m^2-s. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗