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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Microstructure-based prediction of thermal aging strength reduction factors for grade 91 ferritic-martensitic steel

This study aimed to develop a microstructure-based mechanistic approach to address the long-term thermal aging effect on yield stress and ultimate tensile strength and to provide a physical basis for developing thermal aging factors for G91 for a design life of 60 years. Several heats of G91 steel were examined. Controlled aging experiments were conducted on two heats at temperatures of 550, 600, and 650 °C for times up to ~64,000 h. Specimens were also taken from archived creep-tested specimens of G91 and from a tube removed from the Kingston coal-fired power plant to obtain data that cover a wide range of temperatures and for aging times up to 155,000 h. Thermal aging caused significant subgrain recovery, coarsening of M 23 C 6 carbides at subgrain boundaries and MX carbonitrides within subgrains. The intermetallic Laves phase forms during aging and grows rapidly. The growth rate of the subgrain width and MX mean size during thermal aging were described by kinetic models. Thermal aging results in the reductions in the yield stress and the ultimate tensile strength of G91. The effects of thermal aging on the reductions in yield stress and ultimate tensile strength were well described by the microstructure-strength model that considers three superimposed strengthening mechanisms, namely, sub-boundary strengthening, MX precipitation hardening, and Mo solid solution strengthening. Furthermore, the model was independently validated by the ASME Code values and is being used by the ASME to develop the aging-induced strength reduction factors for G91 steel for a design life of 60 years.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Microstructure evolution during binder jet additive manufacturing of H13 tool steel

H13 is one of the most used tool steels for both hot and cold work tooling applications. Binder jet additive manufacturing offers the potential to deposit complex tools at scale due to larger powder bed sizes and faster deposition rates. However, to date there is no published literature on the sintering of H13 to full densification. Here, we discuss the pressureless sintering of binder jet AM H13 steel to full densification via supersolidus liquid phase sintering (SLPS) while presenting appropriate process windows (1360 °C – 1380 °C) for densification without distortion. The process windows have been rationalized based on thermodynamic calculations of liquid volume fractions with temperature. We show that higher binder saturation results in higher carbon retention and subsequently early liquid formation that can initiate the sintering process at lower temperatures. We report abnormal grain growth during sintering and found that the solidification phase transformations play a critical role on microstructural evolution and must be considered to accurately model the kinetics of SLPS.

36 MATERIALS SCIENCE↗
NASA NTRS2004

Stress Distribution During Deformation of Polycrystalline Aluminum by Molecular-Dynamics and Finite-Element Modeling

In this paper, a multiscale modelling strategy is used to study the effect of grain-boundary sliding on stress localization in a polycrystalline microstructure with an uneven distribution of grain size. The development of the molecular dynamics (MD) analysis used to interrogate idealized grain microstructures with various types of grain boundaries and the multiscale modelling strategies for modelling large systems of grains is discussed. Both molecular-dynamics and finite-element (FE) simulations for idealized polycrystalline models of identical geometry are presented with the purpose of demonstrating the effectiveness of the adapted finite-element method using cohesive zone models to reproduce grain-boundary sliding and its effect on the stress distribution in a polycrystalline metal. The yield properties of the grain-boundary interface, used in the FE simulations, are extracted from a MD simulation on a bicrystal. The models allow for the study of the load transfer between adjacent grains of very different size through grain-boundary sliding during deformation. A large-scale FE simulation of 100 grains of a typical microstructure is then presented to reveal that the stress distribution due to grain-boundary sliding during uniform tensile strain can lead to stress localization of two to three times the background stress, thus suggesting a significant effect on the failure properties of the metal.

Yamakov, V.↗
DOE OSTI2024

Strengthening mechanisms for microstructures containing unimodal and bimodal γ' precipitates in ATI 718Plus

Here, the influence of γ' precipitate size distribution on the deformation mechanisms under tensile loading in ATI 718Plus was studied. A set of aging treatments within the temperature range of 720 °C–900 °C was performed on solution-treated samples to obtain various γ' precipitate size distributions. Unimodal and bimodal γ' precipitate size distributions were achieved through single-step and two-step aging sequences, respectively, and such microstructures were tensile tested to failure to assess their yield strength, ultimate tensile strength, and elongation-to-failure. Some of the tensile samples were interrupted after achieving 3–4 % plastic strain, and the deformed microstructures were examined using transmission electron microscopy to investigate the γ' precipitate-dislocation interactions. For the unimodal γ' precipitate size distribution samples with the smaller γ' precipitates (radius ~ 7 nm), dislocations sheared through the precipitates. Both dislocation loops and paired dislocations were observed for the microstructures containing larger γ' precipitates (radius ~ 24 nm). The microstructure containing a bimodal γ' precipitate size distribution, which included average γ' precipitate radii of ~6 nm and ~28 nm, exhibited shearing as the dominant deformation mechanism, and this microstructure exhibited the highest strength values. The experimental observations were rationalized based on the theoretically-calculated critical resolved shear stress values for shearing and looping and a modified model for predicting the yield strength for bimodal microstructures was introduced.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Prediction of Probabilistic Detonation Threshold via Millimeter-Scale Microstructure-Explicit and Void-Explicit Simulations

We present an approach and relevant models for predicting the probabilistic shoc-to-detonation transition (SDT) behavior and Pop plot (PP) of heterogeneous energetic materials (HEM) via mesoscopic microstructure-explicit (ME) and void explicit (VE) simulations at the millimeter (mm) sample size scale. Although the framework here is general, the particular material considered in this paper is pressed Octahydro-1,3,5,7-tetranitro-1,2,3,5-tetrazocine (HMX). To systematically delineate the effects of material heterogeneities, four material cases are considered. These cases are homogeneous material, material with granular microstructure but no voids, homogeneous material with voids, and material with both granular microstructure and voids. Statistically equivalent microstructure sample sets (SEMSS) are generated and used. Eulerian hydrocode simulations explicitly resolve the material heterogeneities, voids, and the coupled mechanical-thermal-chemical processes. In particular, it is found that both microstructure and voids strongly influence the SDT behavior and PP. The effects of different combinations of microstructure heterogeneity and voids on the SDT process and PP are quantified and rank-ordered. The overall framework uses the Mie–Grüneisen equation of state and a history variable reactive burn model (HVRB). A novel probabilistic representation for quantifying the PP is developed, allowing the calculation of (1) the probability of observing SDT at a given combination of shock pressure and run distance, (2) the run-distance to detonation under a given combination of shock pressure and prescribed probability, and (3) the shock pressure required for achieving SDT at a given run distance with a prescribed probability. The results are in agreement with general trends in experimental data in the literature.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Understanding Microstructure Variability in Vapor-Deposited Energetic Materials by Using Phase-Field Methods

Critical components, such as detonators, in Sandia's stockpile contain heterogeneous materials whose performance and reliability depend on accurate, predictive models of coupled, complex phenomena to predict their synthesis, processing, and operation. Ongoing research in energetic materials has shown that microstructural properties, such as density, pore-size, morphology, and specific surface area are correlated to their initiation threshold and detonation behavior. However, experiments to study these specific characteristics of energetic materials are challenging and time consuming. Therefore, in this work, we turn to mesoscale modeling methods that may be capable of reproducing some observed phenomena to refine and predict outcomes beforehand. Even so, we have no physics-based modeling capability to predict how the microstructure of an energetic material will evolve over near- and long-term time scales. Thus, the goal of this work is to (i) identify any knowledge gaps in how the underlying microstructure forms and evolves during the synthesis process, and (ii) develop and test a mesoscale phase-field model for vapor deposition to capture critical mechanisms of microstructure formation, evolution, and variability in vapor-deposited energetic materials, such as processing conditions, material properties, and substrate interactions. Based on this work, the phase-field method is shown to be a valuable tool for developing the necessary models containing coupled, complex phenomena to investigate and understand the synthesis and processing of energetic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Phase-field simulations to inform nuclear fuel performance modeling

Software tools to simulate nuclear fuel performance at the engineering scale, such as Idaho National Laboratory (INL)’s BISON code, are increasingly relied upon in regulatory and economic decision-making. However, accurate results from these tools depends on the availability of materials parameters that are used as input. In recent years, atomistic and mesoscale simulation methods have emerged as a cost-effective, expedient means to obtain such input parameters. Phase-field simulations using INL’s Marmot application have been used to obtain microstructure-level parameters and to improve material models for fuel performance modeling using BISON. In this talk, recent examples of this process are given, including applications in UO2, U3Si2, and UZr fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Gas-mediated defect engineering in earth-abundant Mn-rich layered oxides for non-aqueous sodium-based batteries

Gases are often by-products of battery materials during cell formation and degradation, affecting the cycle life and safety of rechargeable batteries. However, understanding gas-mediated (electro)-chemical reactions and nanoscale structural transformations during the synthesis of battery electrode materials remains challenging because of the lack of suitable characterization routes and the complexity of the interplay between thermodynamics and kinetics. Here, in this study, we use operando synchrotron X-ray diffraction, in situ transmission X-ray microscopy and multiscale modelling to elucidate the reaction pathways and microstructural defect development of earth-abundant Mn-rich layered oxides as positive electrode materials for sodium-based batteries. In particular, we demonstrate the dominant role of CO 2 over O 2 and H 2 O (g) in modulating the competition between entropy and enthalpy during solid-state synthesis. Using Ni 0.25 Mn 0.75 CO 3 as a model precursor, we reveal that CO 2 generation favours the formation of entropy-driven metastable intermediates, suppresses closed pore/nanovoids formation and decreases chemical heterogeneity and residual lattice strain of Mn-rich layered oxides during the synthesis. This result motivates a fast-sintering strategy to promote CO 2 release, which ultimately leads to improved chemo-mechanical and electrochemical stability of the Mn-rich positive electrodes when tested in non-aqueous Na metal coin cells.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Phase-field modeling of radiation-induced segregation for multicomponent alloys

Structural alloys under irradiation are known to undergo radiation-induced solute redistribution (RIS) at grain boundaries, leading to detrimental effects such as intergranular corrosion and stress-assisted cracking. To better understand the phenomenon, improved models of RIS applicable to concentrated, multicomponent alloys, and mesoscale microstructures are needed. In this talk, we present a novel grand-potential-based phase-field model to account for the complete set of multicomponent kinetic and thermodynamic couplings between atoms and point defects in the Onsager transport equations. We demonstrate multiscale modeling capability by deriving the Onsager coefficient matrix from atomistic-based Kinetic Monte Carlo simulations. Model predictions and validations of RIS and the effect of defect production, grain boundary sink strength and density are demonstrated for a model FCC FeCrNi system. We also demonstrate the novel capability to describe RIS in the presence of equilibrium segregation described using a density-based CALPHAD thermodynamic framework. This modeling approach overcomes certain limitations in conventional RIS models and provides a step closer towards multiscale modeling.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2004

Lunar and Planetary Science XXXV: Undergraduate Education and Research Programs, Facilities, and Information Access

The titles in this section include: 1) GRIDVIEW: Recent Improvements in Research and Education Software for Exploring Mars Topography; 2) Software and Hardware Upgrades for the University of North Dakota Asteroid and Comet Internet Telescope (ACIT); 3) Web-based Program for Calculating Effects of an Earth Impact; 4) On-Line Education, Web- and Virtual-Classes in an Urban University: A Preliminary Overview; 5) Modelling Planetary Material's Structures: From Quasicrystalline Microstructure to Crystallographic Materials by Use of Mathematica; 6) How We Used NASA Lunar Set in Planetary and Material Science Studies: Textural and Cooling Sequences in Sections of Lava Column from a Thin and a Thick Lava-Flow, from the Moon and Mars with Terrestrial Analogue and Chondrule Textural Comparisons; 7) Classroom Teaching of Space Technology and Simulations by the Husar Rover Model; 8) New Experiments (In Meteorology, Aerosols, Soil Moisture and Ice) on the New Hunveyor Educational Planetary Landers of Universities and Colleges in Hungary; 9) Teaching Planetary GIS by Constructing Its Model for the Test Terrain of the Hunveyor and Husar; 10) Undergraduate Students: An Untapped Resource for Planetary Researchers; 11) Analog Sites in Field Work of Petrology: Rock Assembly Delivered to a Plain by Floods on Earth and Mars; 12) RELAB (Reflectance Experiment Laboratory): A NASA Multiuser Spectroscopy Facility; 13) Full Text Searching and Customization in the NASA ADS Abstract Service.

Source record↗
DOE OSTI2021

Multimodal Analysis of Spatially Heterogeneous Microstructural Refinement and Softening Mechanisms in Three-Pass Friction Stir Processed Al4Si Alloy

Multiple thermally and thermomechanically induced microstructural refinement mechanisms can be activated in metallic alloys when subjected to solid phase processing methods such as friction stir processing (FSP). In this work, we provide detailed descriptions of the relationship between region-specific microstructural refinement mechanisms and the variation in microhardness, through a systematic and multimodal microstructural characterization of an FSP-processed 75% cold-rolled Al-4 at.% Si model binary alloy. Spatially resolved high-energy synchrotron X-ray diffraction, electron backscattered diffraction, and scanning transmission electron microscopy were used to understand the spatially heterogeneous microstructural evolution due to FSP. Results provide insights into how mechanisms such as static recovery, static recrystallization, dynamic recovery and recrystallization, geometric and continuous dynamic recrystallization, and particle-stimulated static or dynamic grain nucleation may occur heterogeneously in the microstructure as a function of the distance from the stir zone in processed alloys, directly influencing the degree of softening. The systematic analysis of microstructures and hardness in the FSP-processed model binary alloy given in this work highlights the rich microstructural domains that can be uniquely harnessed through solid phase processing of metallic alloys.

Al4Si, Friction Stir Processing, Geometric Dynamic↗
DOE OSTI2026

Documentation, assessment, and improvements of fission gas modeling capabilities in BISON

Fission gas behavior critically affects nuclear fuel performance, influencing thermal conductivity, microstructure, swelling, and fuel-cladding interactions. The Simple Integrated Fission Gas Release and Swelling (Sifgrs) model, implemented within the BISON fuel performance code, provides advanced capabilities for modeling these phenomena. This manuscript reviews and assesses Sifgrs’ modular structure and submodels describing intragranular, intergranular, and release mechanisms. The modular implementation enables rapid improvements as our understanding advances and new fuel forms emerge. After an overview of capabilities, we present a comprehensive validation suite, comparing predictions to experimental data from tests under normal and transient conditions, including reproduction of the Vitanza curve. Results demonstrate Sifgrs’ accuracy, robustness, and applicability. Current limitations and ongoing efforts are discussed, including mechanistic, multiscale modeling, uncertainty quantification, and validation within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, supporting the safe and efficient use of nuclear fuels.

BISON↗
DOE OSTI2020

Multiscale Approach to Fast ModSim for Laser Processing of Metals for Future Nuclear Deterrence Environments

Predicting performance of parts produced using laser-metal processing remains an out- standing challenge. While many computational models exist, they are generally too computationally expensive to simulate the build of an engineering-scale part. This work develops a reduced order thermal model of a laser-metal system using analytical Green's function solutions to the linear heat equation, representing a step towards achieving a full part performance prediction in an "overnight" time frame. The developed model is able to calculate a thermal history for an example problem 72 times faster than a traditional FEM method. The model parameters are calibrated using a non-linear solution and microstructures and residual stresses calculated and compared to a non-linear case. The calibrated model shows promising agreement with a non-linear solution.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Automated Probabilistic Finite Element Model Calibration Tool Based on Uncertainty Quantification and Machine Learning

Qualification and certification of safety critical parts is a hurdle to the adoption of metallic additively manufactured components for aerospace vehicle applications. Challenges include variability in part properties due to inconsistent defect distribution and microstructure. Understanding of the process through finite element modeling (FEM), and process control through in-situ monitoring, may result in significant improvements; however, solutions useful to manufacturers will require large volumes of data and automated data utilization. Toward this end, a generalizable automated FEM calibration paradigm is developed. This paradigm leverages existing and novel tools from machine learning and uncertainty quantification to enable the automatic calibration of FEMs without requiring prior knowledge of the model performance across input parameter space, including meshing and solver settings, which can require time consuming manual model probing or cause noisy and inconsistent predictions. The result is a probabilistic distribution of calibrated and validated FEM input parameters targeting measured data.

Additive manufacturing model calibration finite el↗
DOE OSTI2025

Multiscale Modeling Framework for Lithium Nucleation in 3D Porous Carbon Anodes

Porous carbon scaffolds offer a promising route for mitigating non-uniform lithium (Li) plating to enhance the safety and longevity of Li metal batteries. However, the influence of microstructural morphology on Li nucleation is not well understood. Here, we present a multiscale modeling framework to investigate how the porous microstructure of carbon materials affects Li nucleation behavior. Ab initio molecular dynamics simulations quantify the nucleation energy barriers of Li on graphene as a function of Li content, surface curvature, and applied potential, providing key parameters for a classical nucleation theory (CNT) model. From macroscale half-cell simulations, we obtained Li concentration and electrical potential profiles to define boundary conditions for mesoscopic simulations. At the mesoscale, three distinct synthetic 3D microstructures with different porosities and characteristic feature sizes are generated to resolve local distributions of Li flux, current density, and mechanical stress. These outputs are integrated into the CNT model to map spatial variation in nucleation rates. Our findings reveal trade-offs between suppressing nucleation rates and achieving spatial uniformity, offering design guidelines for optimizing porous carbon anodes to balance nucleation control and mechanical integrity.

Materials science↗
DOE OSTI2023

Neural Network-Enhanced Reproducing Kernel Particle Method for Image-Based Multiphysics Damage Modeling of Energy Storage Materials

Energy storage materials undergo significant stresses during charge/discharge cycling, which makes understanding their reliability and durability fundamental in predicting performance and service life. Strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking, largely along material interfaces and grain boundaries. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), image-based modeling techniques are used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electrochemical-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in capturing crack propagation due to mesh dependency. Additionally, commonly used damage models, such as the continuous damage model and the cohesive zone model, often have steep tradeoffs between discontinuous field accuracy and computational expense. In this work, a neural network-enhanced reproducing kernel particle method (NN-RKPM) [1] is leveraged to accurately capture damage and crack propagation throughout the material by learning the location, orientation, and sharpness of discontinuity while allowing for a coarser nodal distribution than that necessary for capturing sharp solution transitions using traditional mesh-based methods. NN-RKPM is 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.

damage modeling↗
DOE OSTI2023

GnarlyX: Eulerian multi-material hydrodynamics coupled to equation of state and hyperelastic, plastic constitutive models

GnarlyX is a new hydrocode for direct numerical simulations of the microstructural behavior of high explosives at the mesoscale. We summarize the computational framework for multidimensional, Eulerian multi-material hydrodynamics coupled to EOS and hyperelastic, plastic constitutive models. We present 1D verification tests of multi-material only and combined multimaterial and strength capabilities with comparisons to exact solutions of shock states resulting from an incident shock impacting the material interface of PBX9502 and aluminum. We show that GnarlyX performs well in capturing the resulting shock waves in examining numerical convergence with exact solutions. In later work, we will summarize the thermomechanics and multi-dimensional, parallel computing capabilities in GnarlyX with multi-dimensional verification tests.

42 ENGINEERING↗