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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Extend an innovative HPC-Compatible Multiple Temporal-spatial Resolution Concurrent Finite Element Modeling Approach to Guide Laser Powder Bed Fusion Additive

Laser power bed fusing (PBF) additive manufacturing is a key enabling technology to manufacture highly complex and integrated automotive structures. However, the geometric complexity of PBF-AM technique also leads to highly non-uniform heating and cooling rate in the manufactured part, which may cause flaw formation and produce excessive and nonuniform residual stresses, which increase quality uncertainties and manufacture issues, leading to increases in cost and energy consumption in the form of rejected parts. In this research project, we developed an innovative Multi-Spatial-Temporal-Resolution Finite Element (MUST-FE) method and completed the corresponding high performance computation (HPC) platform-based in-house code, which enables high accuracy prediction of temperature and residual stress fields for component-scale PBF-AM manufacture in efficient computation time. The MUST-FE model is calibrated and validated with a “2D pad” AlSi10Mg experiments by matching the melt pool shape and dimension, and with a “XY-cross” AlSi10Mg experiment by matching the thermal distortion and residual stress. The innovative multi-resolution and concurrent modeling approach adopted in this code ensures accuracy and computational efficiency, which will enable energy-efficient and high-yield, low-cost manufacturing of optimized, qualifiable automotive structures and contribute towards reaching technical targets outlined in AMO’s Program Plan to develop additive manufacturing systems that deliver consistently reliable parts with predictable properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Energy Materials Chemistry Integrating Theory, Experiment and Data Science (Final Report)

The Energy Materials Chemistry Integrating Theory, Experiment and Data Science (EM-CITED) project is a multidisciplinary research effort focused on accelerating discovery of scientific knowledge via incorporation of data science and artificial intelligence in materials chemistry research. The project aims to advance materials chemistry-aware data science to unify theory and experiment knowledge streams. The work resulted in foundational AI frameworks for materials chemistry – Deep Reasoning Networks (DRNets), Hierarchical Correlation Learning for Multi-property Prediction (H-CLMP), and Material-to-Spectrum (Mat2Spec) prediction – as well as a host of strategies for accelerated scientific discoveries through principled incorporation of data science in computational and experimental research.

36 MATERIALS SCIENCE↗
DOE OSTI2025

In-Situ Process Monitoring Evaluation and Demonstration using Advanced Characterization with Laser Powder Bed Systems

Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) worked with EOS Group to evaluate the current in-situ sensor capabilities of an EOS M290 Laser Powder Bed Fusion machine. The M290 was fitted with a 1 Mega-Pixel (MP) grayscale visible-light camera and a 5 MP temporally integrated (TI) near-infrared (NIR) camera. One print from stainless steel (SS) 316 and two from Inconel 625 (IN625) were performed where data including in-situ imaging and a machine log file were captured. These data were subsequently analyzed using a Dynamic Multi-Scale Segmentation Convolutional Neural Network (DMSCNN) trained on user defined classes and correlated to as-printed flaws, in the form of porosity, discovered in X-Ray Computed Tomography (XCT). In Phase I, two indications were detected in-situ and spatially correlated to stochastic lack-of-fusion flaws discovered using XCT. In Phase II, using these links from in-situ signatures to XCT flaw populations, a second neural network (NN) was trained to create a Voxelized Property Prediction Model (VPPM) to predict porosity percentages within the part using only features garnered from the in-situ data from two IN625 complex geometries. The VPPM was able to accurately predict porosity values for IN625 parts with an R 2 value of 0.764.

36 MATERIALS SCIENCE↗
DOE OSTI2025

In-Situ Process Monitoring Evaluation and Demonstration using Advanced Characterization with Laser Powder Bed Systems

Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) worked with EOS Group to evaluate the current in-situ sensor capabilities of an EOS M290 Laser Powder Bed Fusion machine. The M290 was fitted with a 1 Mega-Pixel (MP) grayscale visible-light camera and a 5 MP temporally integrated (TI) near-infrared (NIR) camera. One print from stainless steel (SS) 316 and two from Inconel 625 (IN625) were performed where data including in-situ imaging and a machine log file were captured. These data were subsequently analyzed using a Dynamic Multi-Scale Segmentation Convolutional Neural Network (DMSCNN) trained on user defined classes and correlated to as-printed flaws, in the form of porosity, discovered in X-Ray Computed Tomography (XCT). In Phase I, two indications were detected in-situ and spatially correlated to stochastic lack-of-fusion flaws discovered using XCT. In Phase II, using these links from in-situ signatures to XCT flaw populations, a second neural network (NN) was trained to create a Voxelized Property Prediction Model (VPPM) to predict porosity percentages within the part using only features garnered from the in-situ data from two IN625 complex geometries. The VPPM was able to accurately predict porosity values for IN625 parts with an R 2 value of 0.764.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Canister Centerline Cooling Experiments for DPF5-336 Reference Material Made with ERV3b Salt Simulant

This report provides experimental details and results on the elemental distributions (compositions), crystalline/amorphous phase distribution, and microstructures for DPF5-336 reference materials made with ERV3b salt that were subjected to the canister centerline cooling (CCC) heat treatment process. To fabricate these materials, ammonium dihydrogen phosphate was mixed with ERV3b salt simulant and a dechlorination procedure was run in the generation-2 dechlorinator at the Pacific Northwest National Laboratory up to 600°C in an alumina crucible. After the dechlorination process, the product was removed from the crucible, lightly crushed, loaded into a new alumina crucible, Fe 2 O 3 was added, and this was vitrified at 1100°C for 1 hour and quenched. The quenched material was mostly amorphous but showed some small diffraction peaks attributed to Li 3 Fe 2 (PO 4 ) 3 . This quenched material was ground to a fine particle size in a milling chamber, and this was subjected to the CCC cooling profile in duplicate within alumina and fused quartz crucibles. The CCC experiment is designed to simulate the slowest cooling profile (the vertical centerline) of a 0.61-m diameter canister where the slower cooling profile often results in the production of a variety of different crystalline phases upon formation of which result in a residual glass of unknown composition and properties. The information gleaned from these types of experiments will lead to improved composition-property predictions for materials with similar compositions. The results of the alumina and fused quartz experiments show different microstructures but similar diffraction patterns providing evidence of similar crystalline phases being present in each sample. Both samples had monazite [i.e., (Ce,Nd)PO 4 ] and mixtures of phases containing P, Fe, and alkali metal elements. This report completes the milestone M4FT-23PN030104042 with details provided in Appendix B.

36 MATERIALS SCIENCE↗
DOE OSTI2025

NNL.Fe.qSNAP-ZBL.2024.1: A Fe Spectral Neighbor Analysis Potential for Radiation Damage Simulations

The NNL.Fe.qSNAP-ZBL.2024.1 machine-learned potential (MLP) has been generated to support the development of an elemental body-centered cubic (BCC) Fe athermal recombination corrected neutron damage model and simulations of primary recoil atom (PRA) cascades in BCC Fe. This MLP is a quadratic spectral neighbor analysis potential (qSNAP) hybridized with the universal Ziegler-Beirsack-Littmark (ZBL) potential at short-range and is named according to Naval Nuclear Laboratory MLP naming conventions (NNL.material-system.MLP-type.year.version). Training set calculations for Fe are presented along with the subsequent MLP fitting procedure. A key criterion of the fitting procedure is that ZBL describes the short-range interaction with minimal impact on the MLP. The MLP is compared to density functional theory (DFT) predicted properties relevant to radiation damage simulation, including threshold displacement energies, for validation. The NNL.Fe.qSNAP-ZBL.2024.1 potential is considered suitable for molecular dynamics (MD) simulations of radiation defects up to 800 K and PRA cascades in BCC Fe up to around 10 keV. The potential can additionally be used on a limited basis for recoils of 10–20 keV, within which range the emergence of structures outside the training set in cascade simulations may cause system instabilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Comparative study of machine learning techniques for post-combustion carbon capture systems

Computational analysis of countercurrent flows in packed absorption columns, often used in solvent-based post-combustion carbon capture systems (CCSs), is challenging. Typically, computational fluid dynamics (CFD) approaches are used to simulate the interactions between a solvent, gas, and column's packing geometry while accounting for the thermodynamics, kinetics, heat, and mass transfer effects of the absorption process. These simulations can then be used explain a column's hydrodynamic characteristics and evaluate its CO 2 -capture efficiency. However, these approaches are computationally expensive, making it difficult to evaluate numerous designs and operating conditions to improve efficiency at industrial scales. In this work, we comprehensively explore the application of statistical ML methods, convolutional neural networks (CNNs), and graph neural networks (GNNs) to aid and accelerate the scale-up and design optimization of solvent-based post-combustion CCSs. We apply these methods to CFD datasets of countercurrent flows in absorption columns with structured packings characterized by several geometric parameters. We train models to use these parameters, inlet velocity conditions, and other model-specific representations of the column to estimate key determinants of CO 2 -capture efficiency without having to simulate additional CFD datasets. We also evaluate the impact of different input types on the accuracy and generalizability of each model. We discuss the strengths and limitations of each approach to further elucidate the role of CNNs, GNNs, and other machine learning approaches for CO 2 -capture property prediction and design optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Engineering-Scale Integrated Energy System Data Projection Demonstration via the Dynamic Energy Transport and Integration Laboratory

The objective of this study is to demonstrate and validate the Dynamic Energy Transport and Integration Laboratory (DETAIL) preliminary scaling analysis using Modelica language system-code Dymola. The DETAIL preliminary scaling analysis includes a multisystem integral scaling package between thermal-storage and hydrogen-electrolysis systems. To construct the system of scaled equations, dynamical system scaling (DSS) was applied to all governing laws and closure relations associated with the selected integral system. The existing Dymola thermal-energy distribution system (TEDS) facility and high-temperature steam electrolysis (HTSE) facility models in the Idaho National Laboratory HYBRID repository were used to simulate a test case and a corresponding scaled case for integrated system HYBRID demonstration and validation. The DSS projected data based on the test-case simulations and determined scaling ratios were generated and compared with scaled case simulations. The preliminary scaling analysis performance was evaluated, and scaling distortions were investigated based on data magnitude, sequence, and similarity. The results indicated a necessity to change the normalization method for thermal storage generating optimal operating conditions of 261 kW power and mass flow rate of 6.42 kg/s and the possibility of reselecting governing laws for hydrogen electrolysis to improve scaling predictive properties. To enhance system-scaling similarity for TEDS and HTSE, the requirement for scaling validation via physical-facility demonstration was identified.

08 HYDROGEN↗
NASA NTRS1972

Calculative techniques for transonic flows about certain classes of wing body combinations

Procedures based on the method of local linearization and transonic equivalence rule were developed for predicting properties of transonic flows about certain classes of wing-body combinations. The procedures are applicable to transonic flows with free stream Mach number in the ranges near one, below the lower critical and above the upper critical. Theoretical results are presented for surface and flow field pressure distributions for both lifting and nonlifting situations.

Stahara, S. S.↗
NASA NTRS1972

Calculative techniques for transonic flows about certain classes of wing-body combinations, phase 2

Theoretical analysis and associated computer programs were developed for predicting properties of transonic flows about certain classes of wing-body combinations. The procedures used are based on the transonic equivalence rule and employ either an arbitrarily-specified solution or the local linerization method for determining the nonlifting transonic flow about the equivalent body. The class of wind planform shapes include wings having sweptback trailing edges and finite tip chord. Theoretical results are presented for surface and flow-field pressure distributions for both nonlifting and lifting situations at Mach number one.

Stahara, S. S.↗
NASA NTRS1973

A quantum model for bending vibrations and thermodynamic properties of C3.

The investigation reported was conducted to clarify the thermodynamic properties of C3 by further developing the limit to the partition function suggested by Strauss and Thiele (1967). A quantum solution for the energy levels of a quadratically perturbed square well potential is presented and the consistency of this limit with observed energy levels is established. In the process a more complete physical picture of the bending C3 molecules emerges. The values of entropy deduced from various measurements of graphite pressure are compared with this limit, and the thermodynamic properties predicted for the limiting case are evaluated.

Hansen, C. F.↗
NASA NTRS1974

Parametric study of relaminarization of turbulent boundary layers on nozzle walls

By means of comparisons between theoretical predictions and experimental data, the accuracy of a boundary procedure to predict the effect of large streamwise accelerations upon initially turbulent boundary layers is assessed. The boundary layer procedure is based upon simultaneous solution of the boundary layer partial differential equations and the integral turbulence kinetic energy equation. The results of the present investigation show the ability of the procedure to accurately predict properties of boundary layers subjected to large streamwise accelerations. The procedure is used to conduct a parametric study of the effect of free stream turbulence, heat transfer, Reynolds number, acceleration, and Mach number on boundary layers in supersonic nozzles to assist in the design of a quiet tunnel. Results of the investigation show that, even in the presence of moderate free-stream turbulence levels, the boundary layer in the approach section of the quiet tunnel nozzle relaminarizes and becomes thin enough to be removed by a small slot in the nozzle wall. Furthermore, the calculations indicate that it should be possible to maintain a laminar boundary layer for the entire length of the supersonic portion of the quiet tunnel nozzle.

Kreskovsky, J. P.↗
NASA NTRS1976

Atmospheric flow over two-dimensional bluff surface obstructions

The phenomenon of atmospheric flow over a two-dimensional surface obstruction, such as a building (modeled as a rectangular block, a fence or a forward-facing step), is analyzed by three methods: (1) an inviscid free streamline approach, (2) a turbulent boundary layer approach using an eddy viscosity turbulence model and a horizontal pressure gradient determined by the inviscid model, and (3) an approach using the full Navier-Stokes equations with three turbulence models; i.e., an eddy viscosity model, a turbulence kinetic-energy model and a two-equation model with an additional transport equation for the turbulence length scale. A comparison of the performance of the different turbulence models is given, indicating that only the two-equation model adequately accounts for the convective character of turbulence. Turbulence flow property predictions obtained from the turbulence kinetic-energy model with prescribed length scale are only insignificantly better than those obtained from the eddy viscosity model. A parametric study includes the effects of the variation of the characteristics parameters of the assumed logarithmic approach velocity profile. For the case of the forward-facing step, it is shown that in the downstream flow region an increase of the surface roughness gives rise to higher turbulence levels in the shear layer originating from the step corner.

Bitte, J.↗
NASA NTRS1977

Elastic properties and fracture strength of quasi-isotropic graphite/epoxy composites

The layups of the studied laminates are (0, + or - 60) sub s, (0, + or - 45, 90) sub s, (0, + or - 30, + or - 60, 90) sub s (0, + or - 22 1/2, + or - 45, + or - 67 1/2, 90) sub s. The properties determined were tensile modulus, Poisson's ratio, bending stiffness, fracture strength and fracture strain. Measured properties and properties predicted using laminate theory were found to be in reasonable agreement. Reasons for data scatter were determined.

Sullivan, T. L.↗
NASA NTRS1976

The solar wind and its influence on the atmospheres of moon, Mercury and Venus

The solar wind is expected to have an important influence on the atmospheres of the moon, Mercury and Venus and therefore a brief outline of solar wind theory is presented along with the predicted properties of the wind at the orbits of these planets. Since the atmospheres of the moon and possibly Mercury are formed primarily by solar wind accretion, we present the latest accretion models for these bodies. The expected role the solar wind plays on both the ionization and termination of the ionosphere of Venus is discussed.

Hartle, R. E.↗
NASA NTRS1979

On the angle between the average interplanetary magnetic field and the propagation direction of plane large amplitude Alfven waves

The paper shows that the experimentally observed close alignment of magnetic field minimum variance direction with the average magnetic field for Alfven waves in the solar wind is consistent with theoretically predicted properties of plane large amplitude Alfven waves in the MHD approximation. The theoretical properties of these Alfven waves constrain the time averaged magnetic field to cluster around the direction of minimum variance, which is aligned with the wave normal. Thus, spacecraft magnetometer observations in the solar wind of minimum variance directions strongly peaked about the average magnetic field direction are consistent with plane large amplitude Alfven waves which have wave normals aligned with the directions of minimum variance. This does not imply that geometrical hydromagnetic calculations for Alfven wave propagation direction in the solar wind are incorrect, but there is a discrepancy between geometrical hydromagnetics theory and observations that IMF minimum variance directions tend to be aligned with the ideal Parker spiral instead of the radial direction.

Lichtenstein, B. R.↗
NASA NTRS1980

Progress in turbulence modeling for complex flow fields including effects of compressibility

Two second-order-closure turbulence models were devised that are suitable for predicting properties of complex turbulent flow fields in both incompressible and compressible fluids. One model is of the "two-equation" variety in which closure is accomplished by introducing an eddy viscosity which depends on both a turbulent mixing energy and a dissipation rate per unit energy, that is, a specific dissipation rate. The other model is a "Reynolds stress equation" (RSE) formulation in which all components of the Reynolds stress tensor and turbulent heat-flux vector are computed directly and are scaled by the specific dissipation rate. Computations based on these models are compared with measurements for the following flow fields: (a) low speed, high Reynolds number channel flows with plane strain or uniform shear; (b) equilibrium turbulent boundary layers with and without pressure gradients or effects of compressibility; and (c) flow over a convex surface with and without a pressure gradient.

Wilcox, D. C.↗