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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Interplay of strain and phase evolution of laser powder bed fusion Ti–6Al–4V

While additive manufacturing (AM) provides a method of producing geometrically complex and highly detailed structures, the generation of residual strain in AM processes like laser powder bed fusion (L-PBF) can negatively impact performance-enabling properties. In applications such as orthopedic implants, specific performance windows require optimized microstructures in order to obtain desirable properties from multi-phase alloys like Ti–6Al–4V. This research aims to quantify the microscale origins of strain in L-PBF manufactured Ti–6Al–4V by understanding how strain is distributed at the grain and sub-grain scale, the interplay between phase evolution and strain, and examining post-processing strain relief strategies to control these features. Model spinal cage implants were manufactured from Ti–6Al–4V powder via L-PBF and then subjected to strain relieving heat treatment cycles above and below the Ti–6Al–4V β transus as a function of time and cooling rate. Residual strain was then studied via high resolution electron backscatter diffraction (HR-EBSD), and 2D strain maps with sub-micron resolution were generated for each post-processing state. It was found that macroscale thermal strains decreased with heat treatment time, but additional contributions from phase stabilizing residual strains retained primarily in the α' grains as lattice distortive strain remained. Additionally, the retention of β phase significantly changed the strain and dislocation distribution while reducing overall residual strain. In conclusion, these results were validated and reinforced with 3D mesoscopic micromechanical modeling of strain behavior across simulated microstructures, confirming that the local lattice dilation of α’ martensite is a primary contributor of microscale strain generation and retention in L-PBF Ti–6Al–4V.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modeling the thermodynamics of the FeTi hydrogenation under para-equilibrium: An ab-initio and experimental study

We report FeTi-based hydrides have recently re-attracted attention as stationary hydrogen storage materials due to favorable reversibility, good sorption kinetics and relatively low costs compared to alternative intermetallic hydrides. Employing the OpenCalphad software, the thermodynamics of the (FeTi) 1-x H x (0 ≤ x ≤ 1) system were assessed as a key basis for modeling hydrogenation of FeTi-based alloys. New thermodynamic data were acquired from our experimental pressure-composition-isotherm (PCI) curves, as well as first-principles calculations utilizing density functional theory (DFT). The thermodynamic phase models were carefully selected based on critical analysis of literature information and ab-initio investigations. Key thermodynamic properties such as dissociation pressure, formation enthalpies and phase diagrams were calculated in good agreement to our performed experiments and literature-reported data. This work provides an initial perspective, which can be extended to account for higher-order thermodynamic assessments and subsequently enables the design of novel FeTi-based hydrides. In addition, the assessed thermodynamic data can serve as key inputs for kinetic models and hydride microstructure simulations.

08 HYDROGEN↗
DOE OSTI2021

Metamaterial-like aerogels for broadband vibration mitigation

We present metamaterial-like aerogels that provide broadband low-frequency vibration mitigation through their self-assembled locally resonant microstructures. Simulations confirm the presence of a negative dynamic stiffness for the aerogels.

Malakooti, Sadeq↗
DOE OSTI2023

Fierro Version 2.x

FIERRO is a parallel C++ code designed to simulate fluid mechanics, heat transfer, and solid mechanics in two- and three-dimensional space. FIERRO is written to run on homogeneous (CPU) and heterogeneous (CPU+GPU) high performance computing machines. Fierro can aid a) modeling and design efforts that have historically relied on commercial implicit and explicit finite element codes, b) numerical methods research, c) manufacturing research, and d) computer science research. The code contains diverse numerical methods to solve the governing physics equations for both quasi-static and dynamic problems. Mathematical optimization solvers are coupled to the numerical methods to research topology and shape optimization that has application to additive manufacturing, and to create novel numerical approaches. Phase-field methods with micromechanical solvers are provided to simulate microstructure formation and evolution in manufacturing processes. The micromechanical solvers can also help research efforts create continuum-scale constitutive models for solids, as a function of the microstructure, in situ in a calculation or in a stand-alone manner. No physical data exists within the code.

Morgan, Nathaniel↗
DOE OSTI2023

Fierro

FIERRO is a parallel C++ code designed to simulate fluid mechanics, heat transfer, and solid mechanics in two- and three dimensional space. FIERRO is written to run on homogeneous (CPU) and heterogeneous (CPU+GPU) high performance computing machines. Fierro can aid a) modeling and design efforts that have historically relied on commercial implicit and explicit finite element codes, b) numerical methods research, c) manufacturing research, and d) computer science research. The code contains diverse numerical methods to solve the governing physics equations for both quasi-static and dynamic problems. Mathematical optimization solvers are coupled to the numerical methods to research topology and shape optimization that has application to additive manufacturing, and to create novel numerical approaches. Phase-field methods with micromechanical solvers are provided to simulate microstructure formation and evolution in manufacturing processes. The micromechanical solvers can also help research efforts create continuum-scale constitutive models for solids, as a function of the microstructure, in situ in a calculation or in a stand-alone manner. No physical data exists within the code.

Morgan, Nathaniel↗
NASA NTRS1998

Elevated Temperature Crack Growth Behavior in HSCT Structural Materials

Structures in super-sonic aircraft are subjected to conditions of high temperature and cyclic and sustained loading for extended periods of time. The durability of structures fabricated from aluminum and certain titanium alloys in such demanding conditions is of primary concern to the designers and manufacturers of futuristic transport aircraft. Accordingly, the major goal of this project was to evaluate the performance and durability of high temperature aluminum and titanium alloys for use in high speed civil transport (HSCT) structures. Additional goals were to develop time-dependent fracture mechanics methodology and test methods for characterizing and predicting elevated temperature crack growth behavior in creep-brittle materials such as ones being considered for use in HSCT structures and to explore accelerated methods of simulating microstructural degradation during service and measuring degraded properties in these materials.

Saxena, Ashok↗
DOE OSTI2023

A data-driven framework for permeability prediction of natural porous rocks via microstructural characterization and pore-scale simulation

Understanding the microstructure–property relationships of porous media is of great practical significance, based on which macroscopic physical properties can be directly derived from measurable microstructural informatics. However, establishing reliable microstructure–property mappings in an explicit manner is difficult, due to the intricacy, stochasticity, and heterogeneity of porous microstructures. In this paper, a data-driven computational framework is presented to investigate the inherent microstructure–permeability linkage for natural porous rocks, where multiple techniques are integrated together, including microscopy imaging, stochastic reconstruction, microstructural characterization, pore-scale simulation, feature selection, and data-driven modeling. A large number of 3D digital rocks with a wide porosity range are acquired from microscopy imaging and stochastic reconstruction techniques. A broad variety of morphological descriptors are used to quantitatively characterize pore microstructures from different perspectives, and they compose the raw feature pool for feature selection. Here high-fidelity lattice Boltzmann simulations are conducted to resolve fluid flow passing through porous media, from which reliable permeability references are obtained. The optimal feature set that best represents permeability is identified through a performance-oriented feature selection process, upon which a cost-effective surrogate model is rapidly fitted to approximate the microstructure-permeability mapping via data-driven modeling. This surrogate model exhibits great advantages over empirical/analytical formulas in terms of prediction accuracy and generalization capacity, which can predict reliable permeability values spanning four orders of magnitude. Besides, feature selection also greatly enhances the interpretability of the data-driven prediction model, from which new insights into the mechanism of how microstructural characteristics determine intrinsic permeability are obtained.

58 GEOSCIENCES↗
DOE OSTI2022

A Novel Approach to Simulate Realistic Concrete Microstructures under Irradiation

The concrete biological shield of light water reactors is exposed to high neutron and gamma irradiation doses in the long term. Irradiation deteriorates the physical and mechanical properties of concrete. Such effects need to be investigated to predict the concrete’s performance in the event of a lifetime extension of a nuclear power plant. This work combines high-resolution characterization techniques with fast-Fourier transform (FFT)-based 2-D simulations to evaluate the radiation-induced volumetric expansion (RIVE) and damage in concrete microstructures under neutron irradiation. Two concrete microstructures from samples provided by the Japan Concrete Aging Management Program (JCAMP) were characterized using micro x-ray fluorescence (mXRF) to obtain elemental intensity maps, and energy-dispersive x-ray spectroscopy to complement mXRF with local elemental information for Na. Minerals and cement paste are then identified based on the elemental composition to produce high-resolution phase maps, resulting in a more accurate representation of the microstructures compared to previous work. Simulations of radiation-induced volumetric expansion (RIVE), creep, and damage in JCAMP concrete use the fast Fourier transform (FFT)-based code Microstructure Oriented Scientific Analysis of Irradiated Concrete (MOSAIC) combined with the irradiated minerals, aggregates, and concrete (IMAC) database, which contains mineral-specific RIVE models. Overall, the simulation results are in fair agreement with experimental data.

Cheniour, Amani↗
DOE OSTI2019

Microstructural Characterization and Simulation of High Temperature Inelastic Deformation and Fracture of Al-Li 2070

A combined experimental and simulation investigation is carried out to characterize the high temperature deformation behavior of a recently developed Al-Li alloy, AA2070, over a temperature range including typical forging temperatures. Focus is placed on providing explanations for the temperature-dependent plastic and fracture behavior observed for this material using macroscale tensile tests, microscale imaging and analysis, and physics-based micromechanical modeling. It is shown that AA2070 experiences non-monotonic elongation to failure with a rise in temperature. Detailed fractography and microstructural analysis, including dynamic recrystallization analysis, provide insight into this interesting and practically useful behavior. In addition, a validated crystal plasticity model is called upon to explain the unique texture observed in the necked region of the ductile tensile specimen. The insights provided by this investigation will allow improved design of high temperature forming operations for AA2070 and similar alloys which can extend the application of third generation Al-Li alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Phase-field modeling of stored-energy-driven grain growth with intra-granular variation in dislocation density

Abstract We present a phase-field (PF) model to simulate the microstructure evolution occurring in polycrystalline materials with a variation in the intra-granular dislocation density. The model accounts for two mechanisms that lead to the grain boundary migration: the driving force due to capillarity and that due to the stored energy arising from a spatially varying dislocation density. In addition to the order parameters that distinguish regions occupied by different grains, we introduce dislocation density fields that describe spatial variation of the dislocation density. We assume that the dislocation density decays as a function of the distance the grain boundary has migrated. To demonstrate and parameterize the model, we simulate microstructure evolution in two dimensions, for which the initial microstructure is based on real-time experimental data. Additionally, we applied the model to study the effect of a cyclic heat treatment (CHT) on the microstructure evolution. Specifically, we simulated stored-energy-driven grain growth during three thermal cycles, as well as grain growth without stored energy that serves as a baseline for comparison. We showed that the microstructure evolution proceeded much faster when the stored energy was considered. A non-self-similar evolution was observed in this case, while a nearly self-similar evolution was found when the microstructure evolution is driven solely by capillarity. These results suggest a possible mechanism for the initiation of abnormal grain growth during CHT. Finally, we demonstrate an integrated experimental-computational workflow that utilizes the experimental measurements to inform the PF model and its parameterization, which provides a foundation for the development of future simulation tools capable of quantitative prediction of microstructure evolution during non-isothermal heat treatment.

Materials Science↗
DOE OSTI2020

Mesoscale simulations of High Burnup Fuel Fragmentation: Applying phase-field modeling to understand high burnup fuel fragmentation during loss of coolant accident conditions

During a loss-of-coolant accident (LOCA) in a nuclear power plant, a rapid increase in temperature is experienced in the fuel. In commercial light water reactors (LWRs), the high burnup structure (HBS) forms in regions of the UO 2 fuel where local burnup is high, characterized by smaller grain sizes and large, overpressurized bubbles. During a LOCA transient, fuel in the HBS region is susceptible to fine fragmentation, where the fuel breaks up into micron-size fragments (sometimes referred to as pulverization). To better understand the mechanisms behind this phenomenon, mesoscale computational modeling using the Idaho National Laboratory code Marmot has been employed to simulate the process of HBS formation and response to a LOCA transient. The process of complete and partial HBS formation was demonstrated in prototypical LWR conditions. The simulated HBS microstructures from these simulations were passed to a phase-field model of fracture. To provide a more direct comparison with experiments, a set of experiments conducted by Studsvik on fine fragmentation/pulverization during LOCA conditions was simulated using the BISON fuel performance code. The temperature profiles from the BISON simulations were passed to a phase-field model to determine the gas bubble pressure as a function of time. These pressure histories were used in a phase-field model of fracture to determine under what conditions and in which types of bubbles fine fragmentation was likely to occur.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Experimental verification of a crystal plasticity-based simulation framework for predicting microstructure and geometric shape changes: Application to bending and Taylor impact testing of Zr

This paper is concerned with experimental verification of a recently developed multi-scale simulation framework for plastic deformation of metallic materials from quasi-static to impact deformation conditions. The framework is a visco-plastic self-consistent (VPSC) polycrystalline model embedded in an implicit finite element method (FE-VPSC) to provide a microstructure-sensitive constitutive response at each material point. Each material point of the FEM model is a polycrystalline aggregate with crystallographic deformation mechanisms operating at the single crystal scale with their evolving activity based on a dislocation density-based hardening law and texture. Four beams and three cylinders machined in different orientations from a textured plate of high-purity zirconium are tested quasi-statically in 4-point bending and at speeds of 100 m/s, 170 m/s and 243 m/s during Taylor impact tests, respectively. The variation in dimensional changes resulting from different sample orientations in the plate with respect to loading directions is measured for each sample. Moreover, texture and twinning characterization is performed using electron backscattered diffraction (EBSD). The deformation processes and underlying evolution of microstructure are successfully simulated using the FE-VPSC framework. In doing so, the model parameters are optimized and validated across a broad range of strain rates and temperatures. Simulation results in terms of geometrical changes and microstructural evolution are compared with the experimental measurements. The model predicts anisotropic material flow resulting from the hard-to-deform crystallographic directions, the development of gradients in texture and twinning through the geometries, tension–compression asymmetry, as well as the extent of plasticity under impact.

42 ENGINEERING↗
DOE OSTI2024

Multiscale simulation of spatially correlated microstructure via a latent space representation

When deformation gradients act on the scale of the microstructure of a part due to geometry and loading, spatial correlations and finite-size effects in simulation cells cannot be neglected. We propose a multiscale method that accounts for these effects using a variational autoencoder to encode the structure–property map of the stochastic volume elements making up the statistical description of the part. In this paradigm the autoencoder can be used to directly encode the microstructure or, alternatively, its latent space can be sampled to provide likely realizations. Furthermore, we demonstrate the method on three examples using the common additively manufactured material AlSi10Mg in: (a) a comparison with direct numerical simulation of the part microstructure, (b) a push forward of microstructural uncertainty to performance quantities of interest, and (c) a simulation of functional gradation of a part with stochastic microstructure.

Elastoplasticity↗
DOE OSTI2025

PyCMG-based Simulation of Volumetric Concrete Microstructure

Concrete is a complex, heterogeneous material with a microstructure composed of aggregates, cement paste, and pores spanning multiple length scales. Understanding this microstructure is critical for advancing the performance, durability, and modeling of concrete-based systems. While experimental imaging such as X-ray computed tomography (XCT) provides valuable insights, generating large datasets with detailed ground truth annotations is both costly and labor-intensive due to challenges in segmenting similar phases, such as aggregates and cement paste, that often share similar attenuation properties. To address this, we developed a pipeline to simulate realistic 3D concrete microstructures using the open-source Python package PyCMG. This simulation effort focuses on generating high-fidelity, annotated microstructures that can serve as training or benchmarking datasets for image analysis, segmentation algorithms, and machine learning models, particularly in scenarios where experimental data is scarce.

Ziabari, Amir [Oak Ridge National Laboratory; ORNL↗