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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Microstructural Evolution and Toughness of the Various HAZs in 1300-MPa-Grade Ultrahigh-Strength Structural Steel

The effect of heat input on the microstructure and toughness of simulated subregions was investigated by welding thermal simulations and Charpy impact tests. The results indicate that the microstructures of the simulated coarse and fine grain heat affected zone (CGHAZ and FGHAZ) gradually changed from lath martensite to a mixture of lath martensite/lath bainite and finally to granular bainite with the increase in heat input. The microstructure of the simulated intercritical heat affected zone (ICHAZ) was mainly composed of granular bainite and blocky martensite regardless of heat input. When the heat input increased, the toughness of the simulated CGHAZ and ICHAZ continuously decreased. Nevertheless, the simulated FGHAZ still displayed good toughness (53.16 J) due to its fine structure. The occurrence of martensite-austenite (M-A) constituents was the main reason for the decrease in crack initiation energy of the simulated CGHAZ and ICHAZ at high values of heat input, and the toughness deteriorated as the size of M-A constituents increased. It should be noted that high-misorientation packet and block boundaries can effectively deviate or arrest the propagation of microcracks. When the heat input was in the approximate range of 8.63-14.95 kJ cm{sup −1}, all of the simulated subregions exhibited good toughness.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Direct numerical simulation of mechanical response in synthetic additively manufactured microstructures

Additive manufacturing (AM) processes for metals can yield as-built microstructures that vary significantly from their cast or wrought counterparts. These microstructural variations can in turn, have profound effects on the properties of a component. Here, a modeling methodology is presented to investigate microstructurally-influenced mechanical response in additively manufactured structures via direct numeral simulation. Three-dimensional, synthetic voxelized microstructures are generated by kinetic Monte Carlo (kMC) additive manufacturing process simulations performed at four scan speeds to create a thin-wall cylindrical geometry notionally constructed using a concentric-pathed directed energy deposition AM process. The kMC simulations utilize a steady-state molten pool geometry that is held constant throughout the study. Resultant microstructures are mapped onto a highly-refined conformal finite-element mesh of a part geometry. A grain-scale anisotropic crystal elasticity model is then used to represent the constitutive response of each grain. Here, the response of the structure subjected to relatively simple load conditions is studied in order to provide understanding of both the influence of AM processing on microstructure as well as the microstructure's influence on the macroscale mechanical response.

42 ENGINEERING↗
NASA NTRS1996

Computer Simulation of Spatial Arrangement and Connectivity of Particles in Three-Dimensional Microstructure: Application to Model Electrical Conductivity of Polymer Matrix Composite

Computer simulation is a powerful tool for analyzing the geometry of three-dimensional microstructure. A computer simulation model is developed to represent the three-dimensional microstructure of a two-phase particulate composite where particles may be in contact with one another but do not overlap significantly. The model is used to quantify the "connectedness" of the particulate phase of a polymer matrix composite containing hollow carbon particles in a dielectric polymer resin matrix. The simulations are utilized to estimate the morphological percolation volume fraction for electrical conduction, and the effective volume fraction of the particles that actually take part in the electrical conduction. The calculated values of the effective volume fraction are used as an input for a self-consistent physical model for electrical conductivity. The predicted values of electrical conductivity are in very good agreement with the corresponding experimental data on a series of specimens having different particulate volume fraction.

Louis, P.↗
DOE OSTI2025

GrainPaint: A multi-scale diffusion-based generative model for microstructure reconstruction of large-scale objects

Simulation-based approaches to microstructure generation can suffer from a variety of limitations, such as high memory usage, long computational times, and difficulties in generating complex geometries. Generative machine learning models present a way around these issues, but they have previously been limited by the fixed size of their generation area. Here, we present a new microstructure generation methodology leveraging advances in inpainting using denoising diffusion models to overcome this generation area limitation. We show that microstructures generated with the presented methodology are statistically similar to grain structures generated with a kinetic Monte Carlo simulator, SPPARKS.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High-Resolution Comonomer Sequencing of Blocky Brominated Syndiotactic Polystyrene Copolymers Using 13C NMR Spectroscopy and Computer Simulations

This work demonstrates the first high-resolution comonomer sequencing of Blocky brominated syndiotactic polystyrene (sPS-co-sPS-Br) copolymers based on pentad assign- ments of the quaternary carbon region of the nuclear magnetic resonance spectrum. Copolymers containing p-bromostyrene (Br-Sty) units were prepared in matched sets using postpolymerization bromination methods carried out in the heterogeneous gel state (Blocky) and homogeneous solution state (Random). Quantitative information from the quaternary carbon spectra, heteronuclear multiple bond correlation spectroscopy, electronic structure calculations, and simulated statistically random copolymers was correlated to confirm the carbon resonance assignments for all 20 possible pentad comonomer sequences. Using the experimental pentad sequence prevalences, a computer code was developed to simulate chains with microstructures typical of each sample as a means to visually represent the copolymer blockiness with quantitative precision. Based on the microstructure and distribution of run lengths in these chains, the simulations revealed that the Blocky copolymers contain a high degree of blockiness. By comparing the run lengths in the simulated chains to the average number of styrene units in a crystalline segment of sPS (found by small-angle X-ray scattering), copolymer crystallizability was predicted. For the simulated Blocky B-21% (21 mol % Br-Sty) chain, the probability of randomly selecting a styrene unit in a crystallizable block was 25.8%, while that in the simulated Random R-18% was zero, in excellent agreement with the experimental crystallization behavior measured by differential scanning calorimetry. Additionally, these predictions confirmed that the simulated chains accurately represent the ensemble of chains in their respective copolymer samples. Furthermore, each simulated Blocky chain contained one or more long sPS blocks that paralleled the measured 38-40 styrene units spanning a crystalline segment within the sPS/CCl4 gel. This finding affirmed that the long sPS segments originated from the precise lamellar structure within the heterogeneous gel morphology (i.e., block length is correlated with lamellar thickness). Overall, the ability to tailor the copolymer microstructure through control of the semicrystalline gel morphology opens the door to synthesizing ordered copolymers by postpolymerization functionalization processes with unprecedented levels of compositional control.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Multi deep learning-based stochastic microstructure reconstruction and high-fidelity micromechanics simulation of time-dependent ceramic matrix composite response

A multi deep learning-based framework is developed for efficient, automated microstructure reconstruction and generation of stochastic representative volume elements (SRVEs) with periodic boundary conditions (PBCs) for accurate modeling of ceramic matrix composite (CMC) response. The methodology comprises a convolutional neural network coupled with regression layers to act as a vanilla regression network for semantic segmentation of the microstructure, allowing accurate characterization of the phases and their distributions at the microscale. Scanning electron microscope and confocal microscope are used to obtain C/SiNC and SiC/SiNC CMCs micrographs for vanilla regression testing. Microstructure variability in terms of fiber volume fraction and porosity are quantified through the output regression layer, ensuring accurate representation of material variability in SRVE construction. Generative adversarial network (GAN) and its variants are designed to produce high-fidelity SRVE, spanning CMCs microstructure variability space. A circular padding algorithm is developed to generate SRVEs with PBCs during training of GANs. The accuracy of the generated SRVEs is established through micromechanics simulations, where an efficient formulation of the high-fidelity generalized methods of cells (HFGMC) approach is used to compute the effective mechanical properties. Furthermore, an iterative algorithm is implemented in the HFGMC solver to simulate time-dependent deformation of SiC/SiNC subjected to creep loading conditions.

36 MATERIALS SCIENCE↗
NASA NTRS2014

Multiscale Analysis of Structurally-Graded Microstructures Using Molecular Dynamics, Discrete Dislocation Dynamics and Continuum Crystal Plasticity

A multiscale modeling methodology is developed for structurally-graded material microstructures. Molecular dynamic (MD) simulations are performed at the nanoscale to determine fundamental failure mechanisms and quantify material constitutive parameters. These parameters are used to calibrate material processes at the mesoscale using discrete dislocation dynamics (DD). Different grain boundary interactions with dislocations are analyzed using DD to predict grain-size dependent stress-strain behavior. These relationships are mapped into crystal plasticity (CP) parameters to develop a computationally efficient finite element-based DD/CP model for continuum-level simulations and complete the multiscale analysis by predicting the behavior of macroscopic physical specimens. The present analysis is focused on simulating the behavior of a graded microstructure in which grain sizes are on the order of nanometers in the exterior region and transition to larger, multi-micron size in the interior domain. This microstructural configuration has been shown to offer improved mechanical properties over homogeneous coarse-grained materials by increasing yield stress while maintaining ductility. Various mesoscopic polycrystal models of structurally-graded microstructures are generated, analyzed and used as a benchmark for comparison between multiscale DD/CP model and DD predictions. A final series of simulations utilize the DD/CP analysis method exclusively to study macroscopic models that cannot be analyzed by MD or DD methods alone due to the model size.

Saether, Erik↗
DOE OSTI2026

Microstructure, Transport, and Mechanics of Compacted Clay Simulated at the 0.1 μm Scale (1400 Smectite Clay Particles) Using a Coarse-Grained Model with Explicit Counterions

Clay-rich geomaterials play a critical role in many subsurface systems. The macroscale properties of these materials (low permeability, high ionic conductivity, high swelling pressure, etc.) are sensitive to molecular-level adsorption and hydration interactions at clay−water interfaces. Efforts to develop multiscale simulation approaches to predict these properties reveal a scale gap between atomistic simulations (typically limited to systems smaller than 10 nm) and continuum-scale models (which use computational grid elements with dimensions ≳ 10 μm). In this study, we present a coarse-grained (CG) framework that partly bridges this gap by simulating compacted smectite clay assemblages with dimensions of 0.1 μm containing 1,400 clay particles across a range of dry densities (1,050 to 1,850 kg·m −3 ) and Na/Ca counterion compositions (Na fraction ranging from 0.2 to 1). The simulated systems, along with their reconstructed binary three-dimensional pore networks, are used to evaluate the microstructure, pore size distribution, tortuosity, ion diffusivity, and swelling pressure of compacted smectite clay. Results show that our approach captures important features of the mesoscale heterogeneity of compacted clays, including tactoid formation, hierarchical porosity, and anisotropic pore networks. Results also reveal how compaction and counterion composition govern emergent behaviors, including dominant pore sizes, directional transport, and electrochemical response. This work highlights the potential of CG simulations to bridge molecular and continuum scales and to advance geotechnical and environmental applications involving clay-rich materials as well as related nanoporous media such as geopolymers and calcium-silicate-hydrate. However, the results also suggest that accurate prediction of certain microstructural and mechanical properties (e.g., swelling pressure) may require even larger-scale systems on the order of 1 μm.

02 PETROLEUM↗
DOE OSTI2025

Additive Manufactured Composite Phase-Change Material for Thermal Energy Storage Applications

Phase-change materials play a critical role in industrial energy storage applications to drive efficiency improvements, thermal energy management, and carbon emissions reductions. Recently, it has been shown that rapid solidification of alloys with metastable immiscibility in the liquid phase has the potential to form unique microstructures in which a low-melting phase is uniformly distributed in a high-melting matrix. This feature can be exploited using additive manufacturing to produce components with complex geometries containing such unique phase-change microstructures. Phase-field simulations utilizing high-performance computing were used to provide a detailed description of the evolution of the active phase during service in terms of their morphology and composition in different polycrystalline matrix grain morphologies that are typically produced during additive manufacturing. Phase field simulations were performed using, MEUMAPPS-SL (Microstructure Evolution Using Massively Parallel Phase-field Simulations – Solid Liquid) code that was developed in-house by the Oak Ridge National Laboratory. The simulations utilized the capabilities of the Kestrel supercomputer at the National Renewable Energy Laboratory. The simulation results were compared with experimental results generated at Siemens Energy, Inc. The results indicate that the kinetics of liquid spreading along grain boundaries is largely determined by the mobility of the triple line along the intersection of the grain boundary liquid and the grain boundary plane.

25 ENERGY STORAGE↗
DOE OSTI2018

Mechanical Properties, Microstructural Evolution, and the Effect of Friction on the Plastic Flow of the AISI 321 Austenitic Stainless Steel Tube During Cold Pilgering: An Experimental and Simulation Analysis

The mechanical properties, microstructural evolution, and the effect of friction on the plastic flow of the AISI 321 austenitic stainless steel (ASS) tube were investigated during the cold pilger process. The elastic–plastic behavior of as-received tube was simulated by the Johnson-cook model. The model parameters were obtained by the compression and tensile tests. The mechanical properties of the material were examined by the tensile and microhardness tests. Based on the ring compression test results, three different situations for friction conditions were considered. The stress and strain states at these conditions were examined for the outer and inner surfaces of the tube. Numerical evaluation of plastic shearing due to the cold pilgering of the AISI321 tube was performed. The X-ray diffraction, ferrite scope tests, and optical microscope were also used for the microstructure evaluation and verification of the simulation results, respectively. The Latham-Cockcraft damage was calculated for different conditions by introducing the new subroutine, showing that it was strongly dependent on the friction conditions and the shear strain, ε{sub zr}, respectively. It was shown that the friction coefficient of 0.3 resulted in the minimum damage of the tube and the different friction conditions between the two surfaces of the tube enhanced the damage function. Also, the strain induced ά-martensite increased the work-hardening capacity and affected the ductility of the tube.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Crack Initiation Behavior of Cold-Worked Alloy 690 in Simulated PWR Primary Water - Role of Starting Microstructure, Applied Stress and Cold Work on Precursor Damage Evolution

Long-term stress corrosion crack (SCC) initiation behavior in Alloy 690 is being evaluated by constant load tensile testing in simulated pressurized water reactor primary water. Seven commercial Alloy 690 heats with different starting microstructures and cold-work levels are being tested at either 90% or 100% of the material yield stress. Previous studies have revealed grain boundary (GB) cavity formation after 7,110 to 9,220 hours of exposure in certain thermally treated (TT) Alloy 690 heats in highly cold-worked (CW) conditions, serving as precursors to intergranular cracks. This paper summarizes the new characterization results for the evolution of GB cavities in four Alloy 690TT heats in 21% and 31%CW conditions loaded at yield stress after 18,400 hours of exposure. Link-up of GB cavities has led to formation of long internal creep cracks, resulting in crack initiation detected by direct current potential drop in a highly CW Alloy 690TT heat with uniform, semi-continuous distribution of small GB carbides. In comparison, highly CW materials featuring larger and more widely spaced GB carbides did not show a significant increase in GB cavity density or size. Quantitative assessments were performed on GB cavity evolution in highly CW specimens for two Alloy 690TT heats demonstrating the strong dependence of GB cavity evolution on applied stress and starting GB microstructure.

Zhai, Ziqing↗
DOE OSTI2022

Discovering mechanisms for materials microstructure optimization via reinforcement learning of a generative model

Abstract The design of materials structure for optimizing functional properties and potentially, the discovery of novel behaviors is a keystone problem in materials science. In many cases microstructural models underpinning materials functionality are available and well understood. However, optimization of average properties via microstructural engineering often leads to combinatorically intractable problems. Here, we explore the use of the reinforcement learning (RL) for microstructure optimization targeting the discovery of the physical mechanisms behind enhanced functionalities. We illustrate that RL can provide insights into the mechanisms driving properties of interest in a 2D discrete Landau ferroelectrics simulator. Intriguingly, we find that non-trivial phenomena emerge if the rewards are assigned to favor physically impossible tasks, which we illustrate through rewarding RL agents to rotate polarization vectors to energetically unfavorable positions. We further find that strategies to induce polarization curl can be non-intuitive, based on analysis of learned agent policies. This study suggests that RL is a promising machine learning method for material design optimization tasks, and for better understanding the dynamics of microstructural simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Direct Ab Initio Simulation of the Synthesis of BaZrO 3 and the Microstructure Impacts on Proton Transport

Controlling and predicting the processing-structure-performance relationship in functional materials is a grand challenge in materials science, with important implications for a wide range of emerging applications; a high fidelity understanding of the performance impact of microstructures formed under synthesis conditions is required to develop advanced materials, such as solid-state fuel cells and electrolyzers. Using the ceramic BaZrO 3 as a case study, we directly simulate the synthesis and investigate how proton transport is dictated by microstructures. We develop a framework that couples density functional theory (DFT), machine-learning interatomic potential (MLIP) driven molecular dynamics, and grand canonical Monte Carlo to perform large-scale, microstructure-resolved, atomistic simulations of proton transport in experimentally representative polycrystalline structures. Our fully ab initio approach, using a MLIP as a proxy for DFT, allows us to quantify the competition between two distinct diffusion mechanisms: one associated with grain-boundary regions and another within grains. When the impacts of grain boundaries are taken into account, proton transport exhibits substantial deviation from the bulk oxide limit. This addresses long-standing discrepancies between theory and experiments. Our integrated approach provides atomistic insight into microstructure-dependent proton pathways in BaZrO 3 and establishes a general protocol for predicting processing-structure-performance relationships.

organic↗
DOE OSTI2019

The Effect of Annealing Time on Microstructure and AC Corrosion Behavior of X80 Steel in Simulated Solution of Alkaline Soil

The alternating current (AC) corrosion behavior of X80 steels annealed for different times was investigated in an alkaline soil simulation solution by electrochemical measurement, immersion test and surface analysis technology. The results show that with or without AC interference, the steels annealed for various times have different corrosion resistance. The anticorrosion resistance of steel improves with an increase in annealing time. AC interference results in the evolution of the main cathodic reaction, and facilitates the corrosion of the steels. The steel annealed for 20 min presents a more severe corrosion degree with distinct pits. The corrosion behavior of the steels annealed for different times with AC application is closely related to the microstructure. A decrease in pearlite reduces the number of galvanic corrosion cells, decreasing the corrosion rate of steel. And the grain increase is beneficial for improving the corrosion resistance of the annealed steel.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Particle-Based Fiber Models of Woven Materials for Earth Entry Thermal Protection

Applications requiring materials with layer-to-layer strength, from basketry to thermal protection systems, use interlaced, three-dimensional woven materials. NASA is developing and deploying woven material heat shields for missions, including Artemis I (3D-MAT for compression pads) and potentially Mars Sample Return - Earth Entry System. These materials are complex, hierarchical and must protect from extreme environments and phenomena, such as deformation, impact and high-enthalpy heating. Woven material performance depends on microstructure, damage and weave geometry. Therefore, fiber-specific models are needed to simulate fiber contacts within the weave hierarchical geometry (fiber to tow to yarn to weave) and the inherent directionality of fibers. Explicit fiber models can simulate how weave microstructure evolution affects thermal and mechanical properties. We parameterize a discrete element bonded particle models (DEM-BPM) of fibers to capture thermal and mechanical behavior within and between fibers, with bonded and contact forces, respectively. We study the proportion of heat transfer and stress via the contact network, fiber bonds and the weave geometry, for example, with respect to yarn warp-weft identity (whether it interlaces weave layers). Our results demonstrate the importance of explicit fiber modeling for connecting microstructure with thermal and mechanical properties.

woven material↗