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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Combining data and theory for derivable scientific discovery with AI-Descartes

Abstract Scientists aim to discover meaningful formulae that accurately describe experimental data. Mathematical models of natural phenomena can be manually created from domain knowledge and fitted to data, or, in contrast, created automatically from large datasets with machine-learning algorithms. The problem of incorporating prior knowledge expressed as constraints on the functional form of a learned model has been studied before, while finding models that are consistent with prior knowledge expressed via general logical axioms is an open problem. We develop a method to enable principled derivations of models of natural phenomena from axiomatic knowledge and experimental data by combining logical reasoning with symbolic regression. We demonstrate these concepts for Kepler’s third law of planetary motion, Einstein’s relativistic time-dilation law, and Langmuir’s theory of adsorption. We show we can discover governing laws from few data points when logical reasoning is used to distinguish between candidate formulae having similar error on the data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Understanding Calibration and Error Propagation in Longitudinal and Lateral Manganin Gauge Shock Experiments

Soda-lime glass remains elastic under shock pressures up to approximately 6.5 GPa. In this paper, soda lime glass shock experiments are used to understand the calibration and error propagation in longitudinal and lateral manganin gauge experiments. The errors in the calibration process for both longitudinal and lateral manganin gauge experiments are identified and discussed. Five soda-lime glass experiments up to 3 GPa are analyzed using this refined technique. The results show good agreement between the experimental data and the published calibration by Rosenberg and Moshel. Errors are propagated from the experimental data measurements and the assumptions that are made in the calibration, where the bulk of the error seems to come from uncertainty in the dynamic yield strength of manganin. Finally, the method presented in this paper allows for analysis of dynamic shock experiments with longitudinal and lateral manganin gauges including error propagation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Photonuclear production of 47 Ca for 47 Ca/ 47 Sc generator from natural CaCO 3 targets

Here this work investigated the indirect production of 47 Sc from natural Ca targets via 48 Ca(γ,n) 47 Ca → 47 Sc +β - +$\bar{\nu}_e$ with incident electron energies of 30, 35, and 40 MeV. The 47 Ca production yields were simulated using the PHITS Monte Carlo simulation code and compared to experimental data. The simulated production rates for all three irradiations are in good agreement with experimental data within uncertainties. As a demonstration of the 47 Ca/ 47 Sc generator system, one of the irradiated CaCO 3 targets was dissolved in nitric acid, and 47 Sc was isolated from the target material using commercially available Eichrom DGA resin. The 47 Sc was allowed to grow in, and the purification process was repeated with promising 47 Sc and Ca recovery yields.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2025

Design Overview of a High-Pressure Helium Flow Visualization Apparatus for Blanket Cooling Studies

Cooling of the fusion blanket first wall remains a significant challenge given the adverse conditions of heat and particle flux encountered near the plasma. Helium emerges as an attractive cooling candidate because of its chemical and neutronic inertness and separability from hydrogenic species (e.g. tritium). Because of the low thermal mass of helium, optimization of these coolant channels is warranted to provide high heat transfer performance at low pumping costs. Increasingly, computational fluid dynamics (CFD) simulations are employed to model and optimize these flow channels, and accompanying experimental data are needed to validate the predictions of these models. To provide the aforementioned experimental data, a high-pressure helium flow visualization upgrade has been designed for the Helium Flow Loop Experiment facility. This apparatus was built to American Society of Mechanical Engineers boiler and pressure vessel standards to withstand operating pressure of 4 MPa and mated to high-pressure glass windows. Seedless flow visualization is performed via high-speed background oriented schlieren (BOS), with image correlation used for time-resolved two-dimensional velocimetry at frequencies in excess of 60 kHz. Rectangular flow channel test articles are additively manufactured via laser powder bed fusion and installed into this visualization apparatus, with one-sided heating supplied by resistive heaters. In conclusion, the chosen test geometries were informed by prior CFD simulations, and the helium flow structures observed via BOS (detachment, recirculation, etc.) will be used for the validation of these accompanying models, in support of the design and optimization of blanket cooling channel configurations.

Helium flow↗
DOE OSTI2025

Data-driven analysis of dipole strength functions using artificial neural networks

Here, we present a data-driven analysis of dipole strength functions across the nuclear chart, employing an artificial neural network to model nuclear dipole responses. We train the network on a dataset of experimentally measured dipole strength functions for 216 different nuclei. To assess its predictive capability, we test the trained model on an additional set of 10 new nuclei, where experimental data exist. We demonstrate that the artificial neural network not only accurately reproduces known data but also identifies potential inconsistencies in experimental datasets, indicating which results may warrant further review or possible rejection. For nuclei where experimental data are sparse or unavailable, the network confirms theoretical calculations, reinforcing its utility as a predictive tool in nuclear physics. Finally, utilizing the predicted electric dipole polarizability, we extract the value of the symmetry energy at saturation density and find it consistent with results from the literature.

artificial neural networks↗
DOE OSTI2021

GeoMicro3D: A novel numerical model for simulating the reaction process and microstructure formation of alkali-activated slag

Highlights: • The GeoMicro3D model was innovatively developed for simulating the reaction process and microstructure formation of AAS. • In GeoMicro3D, the dissolution of slag and reactions of aqueous ions are fundamentally described in the local lattice cell. • A novel approach is proposed to speed up the nucleation simulations. • GeoMicro3D was implemented and verified with the relevant experimental data and thermodynamic calculation results. For the first time, this study developed a novel model, named GeoMicro3D, to simulate the reaction process and microstructure formation of alkali-activated slag. The GeoMicro3D model consists of four modules that are designed to simulate, respectively: (i) the initial spatial distribution of real-shape slag particles in alkaline activator, (ii) the dissolution of slag and diffusion of ions via the transition state theory and lattice Boltzmann method, respectively, (iii) the spatial distribution of reaction products using a nucleation probability theory, and (iv) the chemical reactions with thermodynamic modelling. Afterwards the GeoMicro3D model was implemented and verified. The simulation results were discussed and compared with the relevant experimental data and thermodynamic calculation results using GEMS. A good agreement was found in the comparisons, showing the strong simulation capability of GeoMicro3D.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Specific features of fluorescence transfer in multiply scattering randomly inhomogeneous layers under intense laser pumping

Based on the analysis of experimental data on the effect of the pulsed laser pump intensity on the spectral properties and the size of the fluorescent response zone in randomly inhomogeneous fluorescent layers, we found that the amplification of spontaneous and stimulated emission significantly affects the statistical properties of the propagation lengths of the fluorescent field partial components in the layers. The experiments are performed with layers of SiO{sub 2} and TiO{sub 2} nanoparticles saturated with rhodamine 6G, pumped by 532-nm laser radiation in the intensity range corresponding to the transient regime from excitation of spontaneous fluorescence to random lasing in the layer. The experimental data are compared with the results of statistical modelling of fluorescence transfer. It is shown that, even at a pump intensity below the random lasing threshold, the spontaneous emission amplification in a layer leads to a significant increase in the contributions to the fluorescence response from partial components with propagation lengths much larger than the layer thickness. This can be interpreted as a manifestation of the quasi-waveguide effect, in which the probability of propagation of diffuse fluorescence components along the layer over distances many times greater than its thickness and the size of the pumped region increases significantly with a decrease in the characteristic radiation amplification length in the layer. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

High-precision shock equation of state measurements for metallic fluid carbon between 15 and 20 Mbar

Diamond is an efficient ablator material to convert the energy of high-power giant lasers into ablation pressure with applications for High-Energy-Density (HED) science, planetary science, and Inertial Confinement Fusion (ICF) research at the National Ignition Facility (NIF). Unfortunately, current theoretical equation of state models cannot reproduce all the observed experimental data in the multi-megabar regime particularly relevant for HED and ICF research. New experimental data on the behavior of carbon at extreme pressures and temperatures are, therefore, essential to improve our predictive capability to design and analyze dynamic compression experiments for HED or ICF research and build improved equation of state models in the future. In this paper, we report high-precision laser-driven shock compression measurements on diamond single crystals at the Omega Laser Facility. Using ultrafast Doppler optical Velocimetry Interferometer System for Any Reflector (VISAR) to track the leading shock front and a quartz plate as an in situ reference, we obtain relative pressure-density shock equation-of-state measurements between 15 and 20 Mbar with an impedance-matching procedure. We also report shock-and-release measurements in a spherical geometry at the NIF. The new data provide tight constraints on the compressibility of warm dense carbon along the Hugoniot of full density diamond, allowing us to discriminate between existing theoretical equation-of-state models. We find that both LLNL LEOS 9061 and LANL Sesame 7835 models capture well the shock compressibility in the explored range. LANL Sesame 7835 also reproduces well the observed shock-and-release behavior of diamond near 10–20 Mbar.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Ground-state properties of light 4 n self-conjugate nuclei in ab initio no-core Monte Carlo shell model calculations with nonlocal N N interactions

We report J π = 0 + ground-state energies and point-proton radii of 4 He, 8 Be, 12 C, 16 O, and 20 Ne nuclei calculated by the ab initio no-core Monte Carlo shell model with the JISP16 and Daejeon16 nonlocal NN interactions. Ground-state energies are obtained in the basis spaces up to seven oscillator shells (N shell =7) with several oscillator energies (ℏω) around the optimal oscillator energy for the convergence of ground-state energies. These energy eigenvalues are extrapolated to obtain estimates of converged ground-state energies in each basis space using energy variances of computed energy eigenvalues. We further extrapolate these energy-variance-extrapolated energies obtained in the finite basis spaces to infinite basis-space results with an empirical exponential form. This form features a dependence on the basis-space size but is independent of the value of ℏω used for the harmonic-oscillator basis functions. Point-proton radii for these states of atomic nuclei are also calculated following techniques employed for the energies. From these results, it is found that the Daejeon16 NN interaction provides good agreement with experimental data up to approximately 16 O, while the JISP16 NN interaction provides good agreement with experimental data up to approximately 12 C. Beyond these nuclei, the interactions produce overbinding accompanied by radii that are too small. These findings suggest and encourage further revisions of nonlocal NN interactions towards the investigation of nuclear structure in heavier-mass regions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Nucleon axial-vector form factor and radius from radiatively corrected antineutrino scattering data

The nucleon axial-vector form factor, 𝐺 𝐴 , is critical to determine the electroweak interactions of leptons with nucleons. Important examples of processes influenced by 𝐺 𝐴 are elastic (anti)neutrino-nucleon scattering and muon capture by the proton. Sparse experimental data results in a large uncertainty on the momentum dependence of 𝐺 𝐴 and has motivated the consideration of new experimental probes and first-principles lattice quantum chromodynamics (QCD) evaluations. The comparison of new and precise theoretical predictions for 𝐺 𝐴 with future experimental data necessitates the application of radiative corrections to experimentally observable processes. We apply these corrections in the extraction of 𝐺 𝐴 and the associated axial-vector radius from the recent MINERvA antineutrino-hydrogen data, compare the effects from radiative corrections to other uncertainties in neutrino scattering experiments, and discuss the comparison of lattice QCD evaluations to experimental measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Integrated Capture and Conversion of CO 2 to Methanol (ICCCM) Process Technology - CRADA 449 (Final Report)

The goal of this project is to develop a prototype system that integrates the capture and catalytic hydrogenation of CO 2 into methanol in the same solvent. Ultimately, this integrated approach could provide a technology with projected reductions to capital and operating costs by at least 20% relative to a benchmark methanol synthesis via gas-phase CO 2 hydrogenation. There were five primary objectives for the project: 1. Optimize the selections of both the catalysts and the CO 2 capture solvents to achieve high conversion (>80%) and high selectivity (>90%) toward methanol in the targeted processing ranges (100-180°C, 1-60 bar). 2. Design a reactor system that provides a fixed catalyst surface area and high-efficiency heat exchange to assure compact modular processing. 3. Build and test a reactor system and demonstrate in a bench scale continuous flow system, and use the operating data to refine the comparison to existing conversion technologies. 4. Refine techno economic (TEA) and Tech-to-Market (TTM) analyses using the experimental data obtained from the bench-scale system. 5. Use the experimental data and TEA/TTM projections to develop a conceptual design for a pre-commercial system that targets a specific market opportunity.

09 BIOMASS FUELS↗
DOE OSTI2021

Prediction of softening kinetics and recrystallization texture in non-isothermally annealed bulged tubes using CPFEM and CA models

A hierarchically coupled cellular automata (CA) model, crystal plasticity finite element method (CPFEM), and thermal finite element (FE) model is developed to predict the softening kinetics of the bulged steel tube during non-isothermal annealing. Through the developed model, the kinetics of softening mechanisms including static recovery (SRV) and static recrystallization (SRX), as well as the recrystallization texture are predicted. Later, the Johnson-Mehl-Avrami-Kohnogorov (JMAK) model based on the predicted SRX data is developed to interpret the recrystallization behavior of the material. To perform this study, diverse experimental tests including tube hydroforming (THF), annealing, uniaxial tensile test, hardness test, as well as microstructure observations through optical microscopy and Electron Backscatter Diffraction (EBSD) tests on steel tube are performed. The obtained experimental data are utilized to calibrate and verify the implemented CPFEM model for simulation of THF process, thermal FE model for prediction of the local temperature over annealing time, and CA algorithm for modeling of the softening kinetics and texture evolution throughout the annealing process. The study shows that the predicted deformation characteristics, softening kinetics, recrystallization texture and temperature profile during non-isothermal annealing are in good agreement with experimental data. During the annealing process, a total of four stages for the kinetics of softening mechanisms is observed: No softening; SRV only; SRV dominant; and SRX dominant. During the progress of SRX, the behavior of recrystallization is abruptly changed, confirming that two different mechanisms are controlling the kinetics of transformation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Benchmarking GEANT4 and PHITS for 14.8-MeV neutron transport in polyethylene and graphite materials

The feasibility of GEANT4 and PHITS with ENDF/B-VIII.0, JEFF-3.3 and JENDL-4.0 evaluated nuclear data libraries in 14.8-MeV neutron transport simulation are verified by comparing with the MCNP calculations and the experimental data. Here the measured data are from neutron integral experiments including graphite and polyethylene samples. For 6 cm-thick polyethylene and 20 cm-thick graphite samples, the results from GEANT4 and PHITS with three evaluated nuclear data libraries agree well with the MCNP calculations. For a 2 cm-thick graphite sample, the simulated results from GEANT4 and PHITS agree with the MCNP calculations, and they all underestimate the experiment data in below 3 MeV and overestimate them in the energy range of 5–7 MeV. The difference between the simulation results and the experimental data depends on the evaluated nuclear data libraries. In overall, GEANT4 and PHITS are performing reasonable jobs for 14.8-MeV neutron transport simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

A Data-Driven Method for Modeling Creep-Fatigue Stress- Strain Behavior Using Neural ODEs

In this paper, we introduce a data-driven machine learning approach for modeling one-dimensional stress–strain behavior under cyclic loading, utilizing experimental data from the nickel-based Alloy 617. The study employs uniaxial creep–fatigue test data acquired under various loading histories and compares two distinct neural network-based ODE models. The first model, known as the black-box model, comprehensively describes the strain–stress relationship using a Neural ODE equation. To interpret this black-box model, we apply the Sparse Identification of Nonlinear Dynamical Systems (SINDy) technique, transforming the black-box model into an equation-based model using symbolic regression. The second model, the Neural flow rule model, incorporates Hooke’s Law for the linear elastic component, with the nonlinear part characterized by a Neural ODE. Both models are trained with experimental data to accurately reflect the observed stress–strain behavior. We conduct a detailed comparison with the standard Chaboche model, which includes three back stresses. Our results demonstrate that the neural network-based ODE models precisely capture the experimental creep–fatigue mechanical behavior, exceeding the standard Chaboche model’s accuracy. Furthermore, an interpretable model derived from the black-box neural ODE model through symbolic regression achieves accuracy comparable to the Chaboche model, enhancing its interpretability. The results highlight the potential of neural network-based ODE models to depict complex creep–fatigue behavior, eliminating the necessity for experts to define a specific, material-focused model form.

creep-fatigue↗
DOE OSTI2024

Autonomous hybrid optimization of a SiO 2 plasma etching mechanism

Computational modeling of plasma etching processes at the feature scale relevant to the fabrication of nanometer semiconductor devices is critically dependent on the reaction mechanism representing the physical processes occurring between plasma produced reactant fluxes and the surface, reaction probabilities, yields, rate coefficients, and threshold energies that characterize these processes. The increasing complexity of the structures being fabricated, new materials, and novel gas mixtures increase the complexity of the reaction mechanism used in feature scale models and increase the difficulty in developing the fundamental data required for the mechanism. This challenge is further exacerbated by the fact that acquiring these fundamental data through more complex computational models or experiments is often limited by cost, technical complexity, or inadequate models. In this paper, we discuss a method to automate the selection of fundamental data in a reduced reaction mechanism for feature scale plasma etching of SiO 2 using a fluorocarbon gas mixture by matching predictions of etch profiles to experimental data using a gradient descent (GD)/Nelder–Mead (NM) method hybrid optimization scheme. These methods produce a reaction mechanism that replicates the experimental training data as well as experimental data using related but different etch processes.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Uncertainty-quantified phenomenological optical potentials for single-nucleon scattering

Optical-model potentials (OMPs) continue to play a key role in nuclear reaction calculations. However, the uncertainty of phenomenological OMPs in widespread use—inherent to any parametric model trained on data—has not been fully characterized, and its impact on downstream users of OMPs remains unclear. Here we assign well-calibrated uncertainties for two representative global OMPs, those of Koning-Delaroche and Chapel Hill '89, using Markov-chain Monte Carlo for parameter inference. By comparing the canonical versions of these OMPs against the experimental data originally used to constrain them, we show how a lack of outlier rejection and a systematic underestimation of experimental uncertainties contributes to bias of, and overconfidence in, best-fit parameter values. Our updated, uncertainty-quantified versions of these OMPs address these issues and yield complete covariance information for potential parameters. Scattering predictions generated from our ensembles show improved performance both against the original training corpora of experimental data and against a new “test” corpus comprising many of the experimental single-nucleon scattering data collected over the last twenty years. Finally, we apply our uncertainty-quantified OMPs to two case studies of application-relevant cross sections. We conclude that, for many common applications of OMPs, including OMP uncertainty should become standard practice. Furthermore, to facilitate their immediate use, digital versions of our updated OMPs and related tools for forward uncertainty propagation are included as Supplemental Material.

150 ≤ A ≤ 189↗
DOE OSTI2021

Using a modified double deep image prior for crosstalk mitigation in multislice ptychography

Multislice ptychography is a high-resolution microscopy technique used to image multiple separate axial planes using a single illumination direction. However, multislice ptychography reconstructions are often degraded by crosstalk, where some features on one plane erroneously contribute to the reconstructed image of another plane. Here, the use of a modified `double deep image prior' (DDIP) architecture is demonstrated in mitigating crosstalk artifacts in multislice ptychography. Utilizing the tendency of generative neural networks to produce natural images, a modified DDIP method yielded good results on experimental data. For one of the datasets, it is shown that using DDIP could remove the need of using additional experimental data, such as from X-ray fluorescence, to suppress the crosstalk. This method may help X-ray multislice ptychography work for more general experimental scenarios.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Hybrid Domain Overlapping Method for Coupling System Thermal Hydraulics and CFD Codes

A hybrid multiscale coupling methodology based on a domain overlapping approach has been developed for coupling System Thermal Hydraulics (STH) and Computational Fluid Dynamics (CFD) codes. The method has been implemented between the modern STH code SAM and the CFD code NekRS, using the coupling tool Cardinal. The coupling aims to extend the STH code's applicability to scenarios where local momentum and energy transfers are important yet difficult for STH codes to capture, such as three-dimensional mixing. Two coupling strategies are implemented and compared: a hybrid domain overlapping method and the conventional domain decomposition method. Here, the strategies are applied to two closed-loop applications, and the present method shows superior stability behavior when compared to the domain decomposition method. Then, the present coupling method is validated against experimental data from a double T-junction experiment. The present STH/CFD coupling shows improved agreement with experimental data when compared to STH standalone simulations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗