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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Method for Rapid Modeling of Distortion in Laser Powder Bed Fusion Metal Additive Manufacturing Parts

The simulation and modeling of part-level distortion and residual stress in diverse metal additive manufacturing (AM) geometries has great potential to enable the rapid adoption of this technology in engineering design. Moreover, the use of additive manufacturing component libraries (CLs) offer a computationally efficient means of quantifying these part-level defects resultant from AM processing. We report on how the individual simulations of simple shapes, potential entries in a CL, can be superimposed to provide an indication of distortion and residual stresses in complex geometries. Laser powder bed fusion AM was used to construct test geometries of varied shapes and their combinations in the form of CLs in an effort to characterize location-dependent and feature-dependent distortion distributions. Blue light scanning was used to experimentally measure 3D distortions in order to investigate the interaction between the component shapes and local boundary conditions. Overall, part-level distortions were highly dependent on test component geometry, local boundary conditions, and shape combination. Commercial finite element software was used to verify experimental trends and to make predictions of distortion. The use of CLs resulted in over 20 times savings in computational cost while reproducing overall trends in distortion for test geometry assemblies. Therefore, it is anticipated that the use of CLs for L-PBF AM geometries has demonstrated potential to facilitate efficient simulations of full component AM assemblies, thereby reducing the need for costly trial-and-error-type experimental analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Microstructural Simulation of Ion-Irradiated Natural Rocks and Minerals

This report details the contribution of Oak Ridge National Laboratory to the Nuclear Energy University Program (NEUP) project, "Rapid Characterization of Concrete Mineralogy using Multi-Scale Tools" led by the University of Illinois at Urbana-Champaign. To support the subsequent license renewal (SLR) of the US nuclear power plants (NPPs) fleet, the performance of concrete-forming aggregates against neutron irradiation needs to be assessed. Ion irradiation is proposed as a rapid, cost-effective surrogate method to full neutron irradiation testing. To complement the characterization of ion-irradiated rock specimens, ORNL has run finite-elements and fast-Fourier transform (FFT-based) simulations using the codes MARS and Microstructure-Oriented Scientific Analysis of Irradiated Concrete (MOSAIC). The main conclusion of this analysis is that the apparent post–ion-irradiation step-height underestimates the accumulated free radiation-induced volumetric expansion (RIVE) in the ion-implanted depth by about 15% at full amorphization and about 25% toward the beginning of the ion irradiation experiment. The discrepancy is explained by the fact that the step height is proportional to the sum of the RIVE (i.e., one third of the RIVE) and the irradiation-assisted plastic strains in the vertical direction (lower than two thirds of the RIVE). Because of the large lateral compressive stresses caused by the restraining effect of the unirradiated substrate, the stress field in the mineral grains and at the grain boundary (GB) in the ion-implanted layer is much different than the comparable stress field occurring during neutron irradiation. Hence, the mismatch RIVE causing cracks in the rock-forming minerals leads to different cracking patterns. Ion irradiation continues to be used as a rapid technique to assess the RIVE potential of rocks.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

TEM Approaches for Microstructure-Informed Prediction of Mechanical Properties in Structural Alloys

Predicting the mechanical performance of structural alloys from their evolving microstructure remains a major challenge in materials science, particularly for nuclear structural materials, where irradiation-induced defects span multiple types and length scales and interact through complex mechanisms. The dispersed barrier hardening (DBH) [1] and Friedel–Kroupa–Hirsch (FKH) [2,3] models have been widely used to evaluate the hardening contributions of individual obstacles and to estimate tensile strength from quantified microstructures; however, when multiple size-dependent obstacles coexist and evolve, predicting temperature-dependent tensile strength becomes significantly more complex, and a fully consistent hardening model is still lacking. Transmission electron microscopy (TEM) plays a central role in refining hardening models and enabling predictive assessments of tensile strength evolution by providing quantitative characterization of dislocations, irradiation-induced defects (e.g., dislocation loops and cavities), precipitates, and grain structure (Fig. 1.). These experimentally measured defect densities are incorporated into physically based hardening models with size- and shape- dependent obstacle strengths [4], using root-sum-square superposition for obstacles of comparable strength and linear superposition for dissimilar ones [5]. In addition, recent advances in TEM [6-8], including high-resolution imaging, 4D-STEM strain mapping, EDS/EELS elemental analysis, and flash-polishing-based TEM specimen preparation and extraction-replica methods (Fig. 2), further improve the accuracy of microstructural quantification. By comparison with prior studies as well as our own results, we show that when TEM-derived microstructural information is carefully integrated with physically grounded hardening models, yield strength (or irradiation-induced hardening) measured at room temperature can be predicted with good quantitative agreement across multiple alloy classes. In-situ TEM combined with high-temperature mechanical testing represents an important next step for refining hardening models by directly probing dislocation–obstacle interactions across varying irradiation doses and temperatures [9]. Because the barrier strength factor (α) depends on both temperature and obstacle size, it should not be treated as a constant fitting parameter; rather, it must be explicitly evaluated to achieve physically meaningful predictions of mechanical behaviour at operating temperatures. This presentation therefore discusses why all strengthening contributions (e.g., Peierls stress, solid-solution strengthening, voids, bubbles, dislocation loops, dislocation lines, and grain boundaries) must be considered collectively, why appropriate superposition methods are essential when obstacles possess different barrier strength factors, how hardness measurements can be meaningfully related to tensile properties, and how TEM-derived microstructural information can be systematically incorporated into hardening models. More broadly, it outlines a pathway toward microstructure-informed prediction of mechanical properties and supports the goal of establishing science-based tools for evaluating structural materials in extreme environments [10].

Lin, Yan-Ru [ORNL] (ORCID:0000000339991473)↗
DOE OSTI2020

Estimating posterior quantity of interest expectations in a multilevel scalable framework

Scalable approaches for uncertainty quantification are necessary for characterizing prediction confidence in large-scale subsurface flow simulations with uncertain permeability. To this end we explore a multilevel Monte Carlo approach for estimating posterior moments of a particular quantity of interest, where we employ an element-agglomerated algebraic multigrid (AMG) technique to generate the hierarchy of coarse spaces with guaranteed approximation properties for both the generation of spatially correlated random fields and the forward simulation of Darcy's law to model subsurface flow. In both these components (sampling and forward solves), we exploit solvers that rely on state-of-the-art scalable AMG. To illustrate the applicability of this approach, numerical tests are performed on two 3D examples-a unit cube and an egg-shaped domain with an irregular boundary-where the scalability of each simulation as well as the scalability of the overall algorithm are demonstrated.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Production of hydrogen peroxide in an intra-meander hyporheic zone at East River, Colorado.

The traditionally held assumption that photo-dependent processes are the predominant source of H 2 O 2 in natural waters has been recently questioned by an increasing body of evidence showing the ubiquitiousness of H 2 O 2 in dark water bodies and in groundwater. In this study, we conducted field measurement of H 2 O 2 in an intra-meander hyporheic zone and in surface water at East River, CO. On-site detection using a sensitive chemiluminescence method suggests H 2 O 2 concentrations in groundwater ranging from 6 nM (at the most reduced region) to ~ 80 nM (in a locally oxygen-rich area) along the intra-meander transect with a maxima of 186 nM detected in the surface water in an early afternoon, lagging the maximum solar irradiance by ~1.5 h. Our results suggest that the dark profile of H 2 O 2 in the hyporheic zone is closely correlated to local redox gradients, indicating that interactions between various redox sensitive elements could play an essential role. Due to its transient nature, the widespread presence of H 2 O 2 in the hyporheic zone indicates the existence of a sustained balance between H 2 O 2 production and consumption, which potentially involves a relatively rapid succession of various biogeochemically important processes (such as organic matter turnover, metal cycling and contaminant mobilization). More importantly, this study confirmed the occurrence of reactive oxygen species at a subsurface redox transition zone and further support our understanding of redox boundaries on reactive oxygen species generation and as key locations of biogeochemical activity.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2020

Understanding the deformation mechanisms in Ni-based superalloys with using crystal plasticity finite element method

Nl-based superalloy is considered as a good candidate due to its excellent resistance to elevated temperature deformation for long term period application. Understanding the deformation and failure mechanisms of Ni-Based superalloys is very helpful for providing design guidelines for processing Ni-based superalloys. Experimental characterization indicates that the deformation mechanisms of Ni based superalloy is strongly microstructure dependent. Besides, damage transform from the void nucleation to the macro cracks by voids growth leading to the failure of the Ni-based superalloys are also showing strong microstructure sensitivity. Therefore, this work focuses on the prediction and comprehension of the deformation and void growth behavior in Ni based superalloy at different working conditions via crystal plasticity finite element modeling and simulation. Physically based crystal plasticity frameworks were developed for newly Ni- based superalloy Haynes 282. It was found that dislocation shearing through the precipitates were acting as the main contributor to the strength of Haynes 282 at room temperature and 815°C. Our analysis of the creeping behavior of Haynes 282 exhibited that resistance of general climb replaced by the resistance induced by the deposited climb dislocation density. In addition, in the study of void growth behavior, our simulation results demonstrated that as the main loading axis perpendicular to the grain boundary (GB), voids grow more slowly on tilt GBs in bicrystals than those in single and bicrystals with twist GBs. And tilt GBs would promote the void grow into irregular shape.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A generalizable machine learning-assisted fast Fourier transform algorithm to simulate the large strain phenomena in polycrystalline materials

Machine learning methods have shown initial promise in constitutive modeling for single crystals or homogenized polycrystals, delivering notable computational efficiency. However, existing machine learning-based constitutive models often lack generalizability, limiting their application across diverse boundary value problems. This study introduces a thermodynamics-informed artificial neural network model to accelerate rate-tangent crystal plasticity fast Fourier transform simulations for cross-scale deformation behaviors of polycrystals under complex loading. Our model integrates microstructural variability and local interactions effectively. To address local effects in each grain, we employ K-means clustering to group Gauss points within the microstructure into clusters assumed to be in similar mechanical states. This approach, based on self-clustering analysis, extends model scope from macroscopic stress response to the granular level, capturing mechanical responses and orientation evolution across grains. This reduces the number of nonlinear problems to solve, with cluster responses propagated throughout each group. The thermodynamics-based artificial neural network-extracted features are further processed using local material state clusters to account for history-dependent deformation and evolving microstructures. Additionally, representative volume element simulations with rate-tangent crystal plasticity fast Fourier transform provide reliable datasets for model training. The proposed model demonstrates high efficiency, accuracy, self-consistency, and enhanced generalizability in predicting strain–stress responses and orientation evolution at both individual grain and aggregate scales under complex loading conditions, such as biaxial tension and arbitrary loading scenarios.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Mesoscopic structure of mixed type domain walls in multiaxial ferroelectrics

The structure of a 180° uncharged rotational domain wall in a multiaxial ferroelectric film is studied in the framework of an analytical Landau-Ginzburg-Devonshire (LGD) approach. Finite element modeling (FEM) is used to solve numerically the system of the coupled nonlinear Euler-Lagrange (EL) second-order differential equations for two components of polarization. We show that the structure of the domain wall and corresponding metastable or stable phase of the film are controlled by a single parameter—the dimensionless ferroelectric anisotropy factor μ. We fitted the static profile of a solitary domain wall, calculated by FEM, with kinklike functions for polarization components, and extracted the five μ-dependent parameters from the fitting to FEM curves. The surprisingly high accuracy of the fitting results for two polarization components in the entire μ range allows us to conclude that the analytical functions, which are trial functions in the direct variational method, can be treated as a high-accuracy variational solution of the static EL equations. We further derive exact two-component analytical solutions of the static EL equations for a polydomain 180° domain structure in a multiaxial ferroelectric film. Using these, we derive analytical expressions for the system free energy and analyze its dependence on the film thickness and boundary conditions at the film surfaces. The single-domain state is ground for zero polarization derivative at the surfaces, while the polydomain states minimize the system energy for zero polarization at the surfaces. Counterintuitively, the energy of the polydomain states split into two levels, “0” and “1,” for zero polarization at the surfaces, and each of the levels contains a large number of close-energy sublevels, whose structure is characterized by a different number and type of domain walls. The analytical solutions can become a useful tool for Bayesian analysis of high-resolution scanning transmission electron microscopy images in ferroelectric films.

36 MATERIALS SCIENCE↗
DOE OSTI2023

An adjoint-based optimization method for jointly inverting heterogeneous material properties and fault slip from earthquake surface deformation data

SUMMARY Analysis of tectonic and earthquake-cycle associated deformation of the crust can provide valuable insights into the underlying deformation processes including fault slip. How those processes are expressed at the surface depends on the lateral and depth variations of rock properties. The effect of such variations is often tested by forward models based on a priori geological or geophysical information. Here, we first develop a novel technique based on an open-source finite-element computational framework to invert geodetic constraints directly for heterogeneous media properties. We focus on the elastic, coseismic problem and seek to constrain variations in shear modulus and Poisson’s ratio, proxies for the effects of lithology and/or temperature and porous flow, respectively. The corresponding nonlinear inversion is implemented using adjoint-based optimization that efficiently reduces the cost function that includes the misfit between the calculated and observed displacements and a penalty term. We then extend our theoretical and numerical framework to simultaneously infer both heterogeneous Earth’s structure and fault slip from surface deformation. Based on a range of 2-D synthetic cases, we find that both model parameters can be satisfactorily estimated for the megathrust setting-inspired test problems considered. Within limits, this is the case even in the presence of noise and if the fault geometry is not perfectly known. Our method lays the foundation for a future reassessment of the information contained in increasingly data-rich settings, for example, geodetic GNSS constraints for large earthquakes such as the 2011 Tohoku-oki M9 event, or distributed deformation along plate boundaries as constrained from InSAR.

Geochemistry & Geophysics↗
DOE OSTI2023

Simulation and Analysis on Reactor Pressure Vessel (RPV) subjected to Pressurized Thermal Shock (PTS) under SBLOCA scenario by using Cardinal to support the fracture mechanics analyses

The structural components that comprise nuclear reactors and their supporting structures are subjected to harsh operating environments that can challenge their integrity, especially after exposure for extended durations or under accident condition. As one of the most significant components of a Reactor, the Reactor Pressure Vessel (RPV) is exposed to an aggressive environment during the operation time (e.g. more than 40 years). Ageing degradation mechanisms (e.g. thermos-fatigue) could grow initial defects up to a critical size, increasing the susceptibility to failure in the RPV. The conventional methods are mostly based on simple crack and structure geometries. Very limited studies consider the real conditions of the RPV subjected to a thermal shock due to a Loss of Coolant Accident (LOCA). During a LOCA event, the most severe conditions take place when the emergency core cooling (ECC) water is injected inside the cold legs filled initially with hotter water and/or steam. The rapid cooling of the down-comer and the internal RPV surface followed probably by re-pressurization of the RPV causes large temperature gradients and variation of pressure which induces thermal-mechanical stresses. In order to develop the model for integrity assessment of a reactor pressure vessel (RPV) subjected to pressurized thermal shock (PTS), a multi-physics simulation, which includes the thermo-hydraulic, thermo-mechanical and fracture mechanics analyses is necessary. The multi-physics simulations are performed using Cardinal, a wrapping of the GPU-oriented spectral element Computational Fluid Dynamics (CFD) code NekRS and other multi-physics sub-modules within the MOOSE framework. Cardinal now fully supports MOOSE stochastic perturbations of NekRS models with varying boundary conditions, initial conditions, material properties, and any other quantity which is defined by a kernel (such as coefficients in a momentum source model). The implementation is designed in a flexible manner so that scalar values are sent from MOOSE into a user scratch space in NekRS, which can then be applied for any purpose within the NekRS case files (both on the host and device). When modeling PTS, several factors can impact the results significantly. In this report, the impacts of the geometry of the model, Reynolds number and buoyancy effect are investigated. Two geometry, i.e., a simplified model and a realistic RPV model, with both laminar and turbulent flow condition are adopted for the PTS simulation with and without buoyancy effect. The purpose of the investigation is to understand the impact of these factors on the prediction of temperature history of RPV. The accurate prediction on the temperature evolution, which will be exported to Grizzly code for further analyses on the progression of aging mechanisms and their effects on the integrity of RPV structures, is very crucial. Based on the understanding of these factors, a more sophisticated model is built to analysis the PTS under SBLOCA scenario. A literature survey is conducted to pick the SBLOCA scenario for the multi-physics simulation. The analysis helps to explain the form and the transformation of the cold plum when the ECC is activated under SBLOCA. This model can be can be applied to study the PTS effect for different RPV configurations. The results can help to assess structural component degradation for advanced reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

CFD/FEA Co-Simulation Framework for Analysis of the Thermal Barrier Coating Design and Its Impact on the HD Diesel Engine Performance

Thermal barrier coatings (TBCs) have been investigated both experimentally and through simulation for mixing controlled combustion (MCC) concepts as a method for reducing heat transfer losses and increasing cycle efficiency, but it is still a very active research area. Early studies were inconclusive, with different groups discovering obstacles to realizing the theoretical potential. Nuanced papers have shown that coating material properties, thickness, microstructure, and surface morphology/roughness all can impact the efficacy of the thermal barrier coating and must be accounted for. Adding to the complexities, a strong spatial and temporal heat flux inhomogeneity exists for mixing controlled combustion (diesel) imposed onto the surfaces from the impinging flame jets. In support of the United States Department of Energy SuperTruck II program goal to achieve 55% brake thermal efficiency on a heavy-duty diesel engines, this study sought to develop a deeper insight into the inhomogeneous heat flux from mixing controlled combustion on thermal barrier coatings and to infer concrete guidance for designing coatings. To that end, a co-simulation approach was developed that couples high-fidelity computational fluid dynamics (CFD) modeling of in-cylinder processes and combustion, and finite element analysis (FEA) modeling of the thermal barrier-coated and metal engine components to resolve spatial and temporal thermal boundary conditions. The models interface at the surface of the combustion chamber; FEA modeling predicts the spatially resolved surface temperature profile, while CFD develops insights into the effect of the thermal barrier coating on the combustion process and the boundary conditions on the gas side. The paper demonstrates the capability of the framework to estimate cycle impacts of the temperature swing at the surface, as well as identify critical locations on the piston/thermal barrier coating that exhibit the highest charge temperature and highest heat fluxes. In addition, the FEA results include predictions of thermal stresses, thus enabling insight into factors affecting coating durability. An example of the capability of the framework is provided to illustrate its use for investigating novel coatings and provide deeper insights to guide future coating design.

42 ENGINEERING↗
DOE OSTI2025

Gas and dust dynamics in γ Cephei-type disks

Context. Giant planets are observed orbiting the primary stars of close binary systems. Such planets may have formed in compact circumprimary disks, which once surrounded these stars, under conditions much different than those encountered around single stars. Aims. In order to quantify the effects of the strong gravitational perturbations exerted on circumprimary disk material, the three-dimensional (3D) dynamics of gas and dust in orbit around the primary star of a compact and eccentric binary system was modeled by applying the stellar and orbital parameters of γ Cephei, a well-known system that can be representative of a class of close binaries. Methods. Circumprimary gas was approximated as an Eulerian viscous and compressible fluid and modeled by means of 3D hydrodynamical simulations, assuming locally isothermal conditions in the medium around the primary star. Dust grains were modeled as Lagrangean particles, subjected to gravity and aerodynamic drag forces. Models that include a giant planet were also considered. Results. Models indicate that spiral density waves excited around pericenter passage propagate toward the inner boundary of the disk, through at least a few pressure scale-heights from the mid-plane, inducing radial and vertical mixing in the gas. However, perturbations imparted to gas, both in terms of eccentricity and precession, are far weaker than previously estimated by two-dimensional (2D) simulations. Models predict small eccentricities, ≲0.03, and slow retrograde precession. The addition of a giant planet does not change the low eccentricity state of the disk. The parameters applied to the disk would lead to the formation of a massive planet, many times the mass of Jupiter, in agreement with some observations. Micron to mm-size dust grains are well coupled to the gas, resulting in similar dynamics and statistically similar distributions of orbital elements. The planet only affects the dust distributions locally. In agreement with outcomes of recent 2D models, the lifetime of an isolated circumprimary disk would be brief, ~10 5 years, because of its compact nature, requiring a long-term external supply of mass to allow for the in situ formation of a giant planet.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Complex motion of steerable vesicular robots filled with active colloidal rods

Abstract While the collective motion of active particles has been studied extensively, effective strategies to navigate particle swarms without external guidance remain elusive. We introduce a method to control the trajectories of two-dimensional swarms of active rod-like particles by confining the particles to rigid bounding membranes (vesicles) with non-uniform curvature. We show that the propelling agents spontaneously form clusters at the membrane wall and collectively propel the vesicle, turning it into an active superstructure. To further guide the motion of the superstructure, we add discontinuous features to the rigid membrane boundary in the form of a kinked tip, which acts as a steering component to direct the motion of the vesicle. We report that the system’s geometrical and material properties, such as the aspect ratio and Péclet number of the active rods as well as the kink angle and flexibility of the membrane, determine the stacking of active particles close to the kinked confinement and induce a diverse set of dynamical behaviors of the superstructure, including linear and circular motion both in the direction of, and opposite to, the kink. From a systematic study of these various behaviors, we design vesicles with switchable and reversible locomotions by tuning the confinement parameters. The observed phenomena suggest a promising mechanism for particle transportation and could be used as a basic element to navigate active matter through complex and tortuous environments.

42 ENGINEERING↗
DOE OSTI2022

A PDE Model of Breast Tumor Progression in MMTV-PyMT Mice

The evolution of breast tumors greatly depends on the interaction network among different cell types, including immune cells and cancer cells in the tumor. This study takes advantage of newly collected rich spatio-temporal mouse data to develop a data-driven mathematical model of breast tumors that considers cells’ location and key interactions in the tumor. The results show that cancer cells have a minor presence in the area with the most overall immune cells, and the number of activated immune cells in the tumor is depleted over time when there is no influx of immune cells. Interestingly, in the case of the influx of immune cells, the highest concentrations of both T cells and cancer cells are in the boundary of the tumor, as we use the Robin boundary condition to model the influx of immune cells. In other words, the influx of immune cells causes a dominant outward advection for cancer cells. We also investigate the effect of cells’ diffusion and immune cells’ influx rates in the dynamics of cells in the tumor micro-environment. Sensitivity analyses indicate that cancer cells and adipocytes’ diffusion rates are the most sensitive parameters, followed by influx and diffusion rates of cytotoxic T cells, implying that targeting them is a possible treatment strategy for breast cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Airfoil Computational Fluid Dynamics - 2k shapes, 25 AoA's, 3 Re numbers

This dataset contains aerodynamic quantities - including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and momentum) - for 1,830 airfoil shapes computed using the HAM2D CFD (computational fluid dynamics) model. The airfoil shapes were designed using the separable shape tensor parameterization that encodes two-dimensional shapes as elements of the Grassmann manifold. This data-driven approach learns two independent spaces of parameter from a collection of sample airfoils. The first captures large-scale, linear perturbations, and the second defines small-scale, higher-order perturbations. For this dataset, we used the G2Aero database of over 19,000 airfoil shapes to learn a parameter space that captured a wide array of shape characteristics. We sampled airfoil designs over both parameter spaces to explore the full range of possible shape variations. The aerodynamic quantities for the generated airfoil were obtained using the HAM2D code, which is a finite-volume Reynolds-averaged Navier-Stokes (RANS) flow solver. We employ a fifth-order WENO scheme for spatial reconstruction with Roe's flux difference scheme for inviscid flux and second-order central differencing for viscous flux. A preconditioned GMRES method is applied for implicit integration. The Spalart-Allmaras 1-eq turbulence model is used for the turbulence closure, and the Medida-Baeder 2-eq transition model is applied to account for the effects of laminar turbulent transition. The airfoil grid is generated with a total of 400 points on the airfoil surface, the initial wall-normal spacing of y+ = 1, and an outer boundary located at 300 chord lengths away from the wall. The CFD simulations are performed at a freestream Mach number of 0.1, for or three different Reynolds' numbers (3M, 6M, and 9M), and for 25 angles of attack from -4 deg. to 20 deg. with 1 degree increments. Across all these various parameters, this dataset includes the results from over 250,000 CFD simulations. The simulations were performed using the Bridges-2 system at the Pittsburgh Supercomputing Center in February 2023 as part of the INTEGRATE project funded by the Advanced Research Projects Agency - Energy, in the U.S. Department of Energy. The data was collected, reformatted, and preprocessed for this OEDI submission in July 2023 under the Foundational AI for Wind Energy project funded by the U.S. Department of Energy Wind Energy Technologies Office. This dataset is intended to serve as a benchmark against which new artificial intelligence (AI) or machine learning (ML) tools may be tested. Baseline AI/ML methods for analyzing this dataset have been implemented, and a link to their repository containing those models has been provided. The .h5 data file structure can be found in the GitHub Repository resource under explore_airfoil_2k_data.ipynb.

2k↗
DOE OSTI2023

Analysis of phase stability and chemical segregation in the Mo-V alloys using a generalized embedded atom method potential

A new interatomic potential for the Mo-V system is introduced to facilitate the study of phase stability and mechanical properties at lower temperatures. This potential is based on a generalization of the embedded atom method and includes contributions from embedding energy, explicit two- and three-body interactions and nonlocal many-body interaction terms. The parameters of the potential are optimized by using data from ab initio density functional theory (DFT) calculations. The potential is rigorously validated across a range of physical properties, such as elastic constants, equation of states, phonon dispersion curves, point defect properties and melting temperatures for different compositions. Even though our potential is trained on a small dataset, its accuracy is comparable to available machine learning potentials for Mo and V. Furthermore, our results show that an ordered B2 phase is stable at low temperatures in alloys containing 50% V, but the solid solution phase is stable above 800 K. However, such long-range ordering is not observed in V-rich or Mo-rich alloys. In addition, our results show that V segregates to dislocation cores and grain boundaries.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Influence of Powder Characteristics and Processing Methods on Creep Performance of Powder Metallurgy Hot Isostatic Pressed SS316

The U.S. nuclear energy expansion goals are driving the demand for manufacturing routes that can rapidly produce large, complex, near net shape components. Powder metallurgy hot isostatic pressing (PM HIP) is an advanced manufacturing technique that can be economically scaled-up, while alleviating the supply chain challenges that forging and casting face in terms of cost and lead time constraints. This makes PM-HIP a viable technology to aid and accelerate large-scale part manufacturing for nuclear applications. However, large-scale qualification and deployment of this technology require a thorough understanding of the influence of powder feedstock quality, powder handling history, hot isostatic pressing (HIP) parameters, and subsequent heat treatment on microstructural evolution and elevated temperature mechanical performance. The present work focusses on 316 austenitic stainless steel (SS316) which is most commonly used in high temperature environments for nuclear applications Results from this study show that PM HIPed SS316 meets ASME tensile requirements at room temperature and at elevated temperature. However, creep performance of PM-HIPed SS316 remains inferior to its wrought counterpart, demonstrating that tensile performance alone is not a reliable metric for long duration high temperature integrity. Further, this report delineates powder derived microstructural features that govern creep damage, with key evidences pointing to “microstructural inheritance” from gas atomized powder feedstocks. Commercial SS316 powders of varying chemical compositions and recycling histories were studies, and the results showed large differences in elemental segregation, oxide surface layers and secondary phase distributions. Multi-scale characterization revealed segregation of chromium, molybdenum, manganese and silicon at the boundaries and the precipitation of manganese-, silicon-, and molybdenum-oxides. During HIP consolidation, these surface oxides transform into decorated prior particle boundaries (PPBs) and grain boundary inclusions that persist through conventional post-HIP solution annealing treatment. The retained oxides in post-HIP microstructures were found to influence grain growth, precipitation behavior, and ultimately creep cavitation and fracture. Such post-HIP heat treatments are therefore limited by a complex trade-off between grain growth, and oxide coarsening which aggravate creep damage by acting as nucleation sites for cavities. The objective of this work is to establish an integrated processing–structure–property framework for PM-HIP 316 stainless steel by investigating the influence of powder feedstock characteristics in pre- and post-HIP processing as well as to understand the significance of post-HIP heat treatment on microstructural evolution and creep properties. The results from this report emphasize the significance of powder feedstock integrity in improving creep performance of PM-HIPed SS316, by highlight the effect of rapid solidification, elemental segregation, oxide formation and powder recycling on microstructural defect inheritance following HIP consolidation. Rather than considering HIP processing, solution annealing, and mechanical performance independently, this report treats powder production, HIP consolidation, post-HIP thermal processing, and creep deformation as interconnected stages within a continuous metallurgical process. The resulting framework will provide a scientific basis for developing feedstock engineering strategies capable of improving long-term reliability of PM-HIP stainless steels and accelerating their qualification for advanced nuclear applications.

Ajjarapu, Pavan [Oak Ridge National Laboratory (OR↗
DOE OSTI2022

Melting and phase relations of Fe-Ni-Si determined by a multi-technique approach

Many studies have suggested silicon as a candidate light element for the cores of Earth and Mercury. However, the effect of silicon on the melting temperatures of core materials and thermal profiles of cores is poorly understood, due to disagreements among melt detection techniques, uncertainties in sample pressure evolution during heating, and sparsity of studies investigating the combined effects of nickel and silicon on the phase diagram of iron. Here, in this study we develop a multi-technique approach for measuring the high-pressure melting and solid phase relations of iron alloys and apply it to Fe 0.8 Ni 0.1 Si 0.1 (Fe-11wt%Ni-5.3wt%Si), a composition compatible with recent estimates for the cores of Earth and Mercury. This approach combines results (20-83 GPa) from two atomic-level techniques: synchrotron Mossbauer spectroscopy (SMS) and synchrotron x-ray diffraction (XRD). Melting is independently detected by the loss of the Mossbauer signal, produced exclusively by solid-bound iron nuclei, and the onset of a liquid diffuse x-ray scattering signal. The use of a burst heating and background updating method for quantifying changes in the reference background during heating facilitates the determination of liquid diffuse signal onsets and leads to strong reproducibility and excellent agreement in melting temperatures determined separately by the two techniques. XRD measurements additionally constrain the hcp-fcc phase boundary and in-situ pressure evolution of the samples during heating. We apply our updated thermal pressure model to published SMS melting data on fcc-Fe and fcc-Fe 0.9 Ni 0.1 to precisely evaluate the effect of silicon on melting temperatures. We find that the addition of 10 mol% Si to Fe 0.9 Ni 0.1 reduces melting temperatures by ~250 K at low pressures (<60 GPa) and flattens the hcp-fcc phase boundary. Extrapolating our results, we constrain the location of the hcp-fcc-liquid quasi-triple point at 147±14 GPa and 3140±90 K, which implies a melting temperature reduction of 500 K compared with Fe 0.9 Ni 0.1 . The results demonstrate the advantages of combining complementary experimental techniques in investigations of melting under extreme conditions.

36 MATERIALS SCIENCE↗