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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Development and testing of coarse-grained models for ultrasonic simulations of cast austenitic stainless steel

Ultrasonic inspection of cast austenitic stainless steel (CASS) in the nuclear industry is particularly challenging because of sound field scatter and attenuation caused by the coarse-grained microstructure. Modeling and simulation are important tools in ultrasonic testing, as they can be used to help address key aspects of inspections, such as developing new probe designs, predicting inspection reliability, and testing phased-array focal laws. However, developing a useful and reliable CASS model is challenging due to the many grain interfaces and crystalline orientations that must be captured. We demonstrate a method of creating a realistic CASS model that is usable in CIVA, a commercially available modeling and simulation software platform. Using polished and chemically etched sections, we generate models of a coarse-grained equiaxed specimen and a columnar specimen. We also test an alternative method of generating a coarse-grained model using Voronoi regions. We qualitatively compare sound field scatter and quantitatively compare sound field attenuation and beam partitioning in simulated sound fields to those of laboratory-measured sound fields. Results show that the Voronoi models perform as well as or better than the models based on actual grain morphology. Here we also show that model-to-model randomness in Voronoi grain structure can impact the magnitude of a simulated echo response by a factor of two or more. Although CASS models are potentially a good depiction of reality for a given scenario, they should not be considered representative since CASS morphology can change significantly from specimen to specimen or within the same specimen.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Enhanced strength and ductility of a tungsten-doped CoCrNi medium-entropy alloy

Developing metallic materials with a good combination of strength and ductility has been an unending pursuit of materials scientists. The emergence of high/medium-entropy alloys (HEA/MEA) provided a novel strategy to achieve this. In this work, we also strengthened a strong-and-ductile MEA using a traditional solid solution strengthening theory. The selection of solute elements was assisted by mechanical property and microstructure predictive models. Extensive microstructural characterizations and mechanical tests were performed to verify the models and to understand the mechanical behavior and deformation mechanisms of the designated CoCrNi–3W alloy. Our results show good experiment-model agreement. The incorporation of 3 at.% W into the ternary CoCrNi matrix increased its intrinsic strength by ~20%. External strengthening through microstructural refinement led to a yield strength nearly double that of the parent alloy, CoCrNi. The increase in strength is obtained with still good ductility when tested down to 77 K. Nanoscale twin boundaries are observed in the post-fracture microstructure under 77 K. Finally, the combination of strength and ductility after W additions deviate from the traditional strength-ductility-trade-off contour.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multi-objective surrogate-assisted calibration of CPFEM models using macroscopic response and in situ EBSD measurements of grain reorientation trajectories

Crystal plasticity finite element method (CPFEM) models are widely used to simulate the deformation behaviour of polycrystalline materials, but their calibration is often limited by their high computational cost and the non-convexity of the optimisation landscape. Here, this study develops a multi-objective surrogate-assisted calibration workflow that couples a multi-objective genetic algorithm (MOGA) with an adaptively trained deep neural network (DNN) surrogate model to efficiently identify CPFEM parameters from experimental data. The workflow is demonstrated on three crystal plasticity (CP) formulations of increasing complexity — Voce hardening (VH), two-coefficient latent hardening (LH2), and six-coefficient latent hardening (LH6) — using in situ electron backscatter diffraction (EBSD) measurements of Alloy 617 under uniaxial tensile loading. The CPFEM models are calibrated against the experimentally observed stress–strain response and reorientation trajectories of eight grains, then validated against eight additional trajectories and overall texture evolution. Across the CP formulations, the macroscopic response was reproduced reliably, while differences emerged in the robustness and accuracy of the grain-scale predictions. Including grain reorientation trajectories in the multi-objective calibration improved texture evolution predictions and filtered out physically inconsistent parameter sets that can arise from calibrating against only the stress–strain data. The workflow also demonstrates good transferability of calibrated parameters from a low- to a high-fidelity microstructural model. These results provide practical guidance for integrating in situ microstructural data into CPFEM through efficient, repeatable, and physically meaningful multi-objective calibration.

Crystal plasticity finite element method↗
DOE OSTI2018

Materials Dynamics

The Materials Dynamics area of leadership focuses on understanding structure-properties-performance relationships for the extreme conditions of dynamic loading. This research encompasses controlled synthesis of materials to meet dynamic performance requirements and requires computational coupling across length and time scales for three-dimensional microstructure modeling. For this leadership area, we define dynamic loading as strain rates greater than 103/s. A key grand challenge of this area is to predict and measure the evolution of microstructural phases, defect structures, and electronic structure under dynamic conditions while also dynamically measuring local temperature to understand transition states. Solving this challenge will require agile, multidimensional data analysis and interpretation capability.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Materials Dynamics

The Materials Dynamics area of leadership focuses on understanding process-structure-properties-performance (PSPP) relationships for the extreme conditions of dynamic loading. This research encompasses controlled synthesis of materials to meet dynamic performance requirements and entails computational coupling across length and time scales for three-dimensional microstructure modeling. For this leadership area, we define dynamic loading as strain rates ≥ 10 3 /s and often, high pressures. A key grand challenge of this area is to predict and measure the evolution of microstructural phases, defect structures, and electronic structure under dynamic conditions while also measuring local temperature to understand transition states. Solving this challenge will require agile, multi-dimensional data analysis and interpretation capability.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Effect of Martensite Content on Failure Behavior of Laser Welded Dual-Phase Steel Joints During Deformation

Laser welding was applied to three types of dual-phase (DP) steel sheets (DP590, DP780, and DP980) with different martensite contents. The microstructure of laser welded joints was observed by optical microscope and scanning electron microscope, and the hardness of welded joints was measured by a microhardness tester. The tensile testing machine and the Erichsen test machine were employed to measure the tensile properties and forming properties of welded joints, respectively. The microstructure model showed that the welded joints of three different materials all contained a hardened zone (HZ) that was composed of a fusion zone, a coarse-grained heat-affected zone, and fine-grained heat-affected zone. The microstructure of the HZ contained mainly martensite such that the average martensite content of welded joints was increased by 1.9-9.8%, and the microhardness of the HZ was 1.2-1.9 times that of the base metal (BM). Moreover, the elongation of welded joints decreased with decreasing martensite content in the BM, and the effect was severe for the DP590 welded joint (21.8%) compared to the other two welded joints. During the Erichsen test, deformation failure varied among the welded joints with different martensite contents, and it was determined by the HZ and softened zone. The fracture occurred in the softened zone and ran parallel along the zone for DP980 welded joints, whereas the fracture occurred in the HZ and ran perpendicular to this zone for the other two welded joints. The Erichsen values of the DP590, DP780, and DP980 welded joints were 81.1, 91.7, and 85.0% of the BM, respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Microstructure and nanoindentation of the rostrum of Curculio longinasus Chittenden, 1927 (Coleoptera: Curculionidae)

The rostrum is an extension of the cuticle of the head of weevils (Coleoptera: Curculionidae) and is often used to bore holes for oviposition (the process of laying eggs) into host plant tissue where larval development occurs. In members of the genus Curculio Linnaeus, 1758, the rostrum is long, slender, and strongly curved, but is nevertheless used to excavate straight bore-holes in the fruit of various host plants, through significant deformation of this structure. In this study, scanning electron microscopy (SEM) was used to examine the rostrum of Curculio longinasus Chittenden, 1927, leading to a microstructural model that describes its deformation behavior. Specifically, we used the continuous stiffness measurement (CSM) technique in nanoindentation to measure the Young's modulus and hardness of rostrum. The values of Young's modulus and hardness for the endocuticle were measured to be 8.91 ± 0.93 GPa and 558 ± 60 MPa, respectively. These results are critical for generating accurate finite element models of the head's mechanical behavior while it undergoes deformation. - Highlights: •SEM was used to examine the rostrum of Curculio longinasus Chittenden, 1927. •Nanoindentation to measure the Young's modulus and hardness of rostrum. •Results are critical for finite element models of the head's mechanical behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Controlling microstructure in deposits fabricated using powder blown direct energy deposition technique

The overall goal of this collaboration is to develop technologies to control grain morphology and microstructures of Inconel 718 components additively manufactured through the Direct Energy Deposition (DED) process (Identical to the LENS (laser engineered net shaping) processes) and to achieve equiaxed or near equiaxed grain structures. The phase1 technical collaboration was used to fabricate Inconel 718 builds with different process parameters, pre heat and scan strategies. The results were then rationalized using computational heat transfer and solidification models. Microstructural characterization showed that the aspect ratio of the grains can be reduced to less than 1.5, and that control of the grain sizes to within 50-100 μm could be potentially obtained by using an external source to preheat the substrate to 400 ̊C. Heat transfer models coupled with solidification models were used to rationalize the results which show that preheating lowered the temperature gradient thereby resulting in moving towards the equiaxed region of the columnar to equiaxed transition (CET) curve. The results demonstrate that higher preheat temperatures could be potentially used to obtain a truly equiaxed structure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Microstructural-Level Fuel Performance Modeling of U-Mo Monolithic Fuel

As the physics that governs the microstructural evolution of nuclear fuel span various time and spatial scales, to fully understand the fuel behavior inevitably involves atomic to mesoscale resolution that can be difficult to determine experimentally. Microstructural-level modeling and simulations can be used to develop physics-based materials models that can provide physical understanding to inform fabrication process control, as well as a valuable feedback mechanism between post-irradiation examination (PIE) results and fabrication parameters. In accordance with the program schedule, the primary goals of the microstructure modeling effort are to: 1. Address critical microstructural questions and provide practical guidance to the fabricator via the fuel product specification; 2. Provide mechanistic inputs for the existing fuel performance code to improve its descriptive and predictive capability at the macroscopic scale. In fiscal year (FY)-21, the work scope consisted of six main facets: (1) the effect of carbides on fuel performance; (2) gas diffusivity in different phases; (3) integration of microstructural fuel performance modeling; (4) property degradation; (5) irradiation creep; and (6) historical analysis of microstructure data. Brief summaries of each are included below.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

DECA: Discrete Event inspired Cellular Automata for grain structure prediction in additive manufacturing

Microstructure largely dictates macroscopic material properties and is strongly affected by processing. Therefore, the simulation of microstructure evolution in response to thermal fields during processing is of significant interest within the computational materials science community. Additive manufacturing (AM) has emerged as a technique for producing complex geometries and unique microstructures. Yet, complex and rapid thermal cycles in AM pose computational challenges for existing microstructure models. This work proposes a discrete event inspired cellular automata (CA) approach, titled DECA, to accelerate simulation of grain structure evolution in AM. In contrast to conventional time-stepped CA models, this model directly solves the times capture events would take place allowing for stepping in events rather than time (a technique also found in the field of discrete-event simulation). In comparison to purely serial discrete-event models, DECA allows for temporary violation of the causality constraint, but detects and corrects these violations, leading to an emergent phenomenon dubbed causality rippling, in which previously calculated capture events are overwritten. The amount of repeated calculations, defined by the capture ratio, is taken as a measure of computational inefficiency, and the model parameters that affect this ratio are evaluated. The new DECA approach was found to be more computationally efficient than conventional time-stepped CA models while guaranteeing an accurate solution, which can only be achieved in the conventional models for vanishingly small time steps. Finally, opportunities for parallelization and scaling of the new approach are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Microstructure Characterization and Modeling for Improved Electrode Design

This presentation describes research work led by NREL with team members from Argonne National Laboratory and Texas A&M University in microstructure analysis, modeling and validation under DOE's Computer-Aided Engineering of Batteries (CAEBAT) program. The goal of the project is to close the gaps between CAEBAT models and materials research by creating predictive models that can be used for electrode design.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Intelligent Weld Manufacturing: Role of Integrated Computational Welding Engineering

A master welder uses his sensory perceptions to evaluate the process and connect them with his/her knowledge base to take the necessary corrective measures with his/her acquired skills to make a good weld. All these actions must take place in real time. Success depends on intuition and skills, and the procedure is labor-intensive and frequently unreliable. The solution is intelligent weld manufacturing. The ultimate goal of intelligent weld manufacturing would involve sensing and control of heat source position, weld temperature, weld penetration, defect formation and ultimately control of microstructure and properties. This involves a solution to a problem (welding) with many highly coupled and nonlinear variables. The trend is to use an emerging tool known as intelligent control. This approach enables the user to choose a desirable end factor such as properties, defect control, or productivity to derive the selection of process parameters such as current, voltage, or speed to provide for appropriate control of the process. Important elements of intelligent manufacturing are sensing and control theory and design, process modeling, and artificial intelligence. Significant progress has been made in all these areas. Integrated computational welding engineering (ICWE) is an emerging field that will aid in the realization of intelligent weld manufacturing. The paper will discuss the progress in process modeling, microstructure, properties, and process control and automation and the importance of ICWE. Also, control and automation strategies for friction stir welding will be discussed.

42 ENGINEERING↗
DOE OSTI2023

The Effects of Silicon and Niobium Concentration on the Solidification Behavior and Microstructure of Cast Monel Alloys

Cast Monel alloys are used in applications requiring a combination of good mechanical properties and excellent resistance to corrosion. Despite prevalent industrial use, relatively few studies have been conducted to investigate the relationships between composition, solidification behavior, and microstructure. Given that these alloys are used in the cast and welded conditions, these factors have a significant influence over the material properties. Here, in this work, microstructural characterization, electron probe microanalysis, X-ray diffraction, and differential scanning calorimetry were used to study how changes in Si and Nb concentrations affected the solidification path and microstructure of Monel alloys. It was found that increasing Nb concentration stabilized higher amounts of MC carbides and suppressed graphite formation during solidification. It was also found that the high nominal concentration and segregation of Si to the liquid led to the formation of Ni 31 Si 12 and other silicides via terminal eutectic reactions at the end of solidification. A pseudo-binary solidification diagram was constructed using experimental data and was applied to predict the mass fraction of solidified eutectic as a function of composition. The modeled microstructures were found to be in good agreement with experimentally measured phase fractions.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Microstructure and Mechanical Properties of Al-Mg-Sc-Zr Alloy Variable Polarity Plasma Arc Welding Joint

Al-Mg-Sc-Zr alloy plates were welded by variable polarity plasma arc welding (VPPAW) with Sc-containing filler wire. The microstructure and mechanical properties were investigated. Results show that the weld zone and heat-affected zone (HAZ) are narrow due to the high concentrated heat input of VPPAW. Primary Al{sub 3}(Sc,Zr) particles are nice nucleating sites for α-Al, which can significantly refine the grains of α-Al, helping the weld zone maintain an outstanding strength. The unmelted Al{sub 3}(Sc,Zr) precipitates of the base metal aggregated near the fusion boundary result in the formation of a fine equiaxed grains zone, which improves the bonding degree between the weld zone and the base metal. The Al{sub 3}(Sc,Zr) precipitates in the HAZ have excellent inhibition effect on recrystallization. According to the observed microhardness distribution and microstructure characteristics, the microstructure model of welded joint is obtained. The fractured position of welded joint locates in the weld zone. The tensile strength of the welded joint without reinforcing rib is 330 MPa. The welding coefficient reaches 74%.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Growth interactions between icosahedral quasicrystals

We investigate the solidification pathways of a population of icosahedral quasicrystals in a liquid through in situ synchrotron x-ray tomography. The wealth of three-dimensional space- and time-resolved data enables us to test the predictions of various models and theories of crystallization on a quasi-crystal-forming alloy. Remarkably, we find the general evolution equation—that accounts for the competing effects of growth, coalescence, and coarsening—fits well our experimental data on surface area concentration. Furthermore, we quantify the orientation selection, screening length, and coarsening rate of the dodecahedra, and compare these results to that of periodic crystals. The latter is a full order of magnitude smaller than that of elemental metal dendrites in the limit of zero volume fraction, a reflection of the low solid-liquid interfacial energy of the icosahedral phase. Furthermore, our paper provides the critical input data for microstructural models used for integrated computational materials engineering of complex intermetallics, including quasicrystals.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Development of grain-scale slip activity and lattice rotation fields in Inconel 718

Using a combination of in-situ high-resolution digital image correlation (HR-DIC), Heaviside-DIC method (H-DIC), and crystal plasticity finite element (CPFE), we investigate the evolution of intragranular lattice rotations and slip activity during monotonic and cyclic loading in a high performance, polycrystalline face centered cubic material. The CPFE employs a quasi-3D model microstructure, which is a highly resolved mirror representation of the experimental in-situ test sample. In agreement, the measurements and calculations reveal that most grains, regardless of their size and lattice orientation, develop intragranular lattice rotation gradients that span the grain. For a small cluster of grains on the deformed material, we perform HR-DIC analysis of slip lines to demonstrate agreement in the active slip systems and changes in this local slip activity across the individual grains. The combined analysis reveals that deforming grains are divided into sub-granular regions of uniform lattice rotation and these regions are most often associated with only one or two active slip systems. The gradient lines that divide them correspond to changes in the predominant slip system. The model is used to examine the evolution of intragranular lattice rotation in a single fully reversed tension-compression cycle. The calculations indicate that intragranular gradients intensify during the reverse loading path as nearest neighboring regions appear to shed lattice rotation, increasing the lattice rotation in some regions, while shutting down rotation in neighboring regions. So these findings provide insight into the irreversible changes that develop within deforming grains at the scale of the grain, particularly the heterogeneous development of intragranular lattice rotation in early stages of deformation, which could serve as precursors to localization.

36 MATERIALS SCIENCE↗
DOE OSTI2024

ExaCA grain structure predictions for laser powder bed fusion processing

This dataset contains simulated cross-sections of laser powder bed fusion grain structures produced using the microstructure model ExaCA, in turn using time-temperature history data produced using the heat transport model AdditiveFOAM. These predictions show the grain structure using various permutations of hatch spacing and nucleation density. Also contained in the dataset are the input files necessary to reproduce the results. AdditiveFOAM (https://github.com/ORNL/AdditiveFOAM) and ExaCA (https://github.com/LLNL/ExaCA), both open source software, are required to reproduce the results in this dataset using the given input files. This DOI was updated 12/09/2025.

36 MATERIALS SCIENCE↗