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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Comparison of fixed charge and polarizable models for predicting the structural, thermodynamic, and transport properties of molten alkali chlorides

Results from extensive molecular dynamics simulations of molten LiCl, NaCl, KCl, and RbCl over a wide range of temperatures are reported. Comparison is made between the “Polarizable Ion Model” (PIM) and the non-polarizable “Rigid Ion Model” (RIM). Densities, self-diffusivities, shear viscosities, ionic conductivities, and thermal conductivities are computed and compared with experimental data. In addition, radial distribution functions are computed from ab initio molecular dynamics simulations and compared with the two sets of classical simulations as well as experimental data. Here, the two classical models perform reasonably well at capturing structural and dynamic properties of the four molten alkali chlorides, both qualitatively and often quantitatively. With the singular exception of liquid density, for which the PIM is more accurate than the RIM, there are few clear trends to suggest that one model is more accurate than the other for the four alkali halide systems studied here.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Hawaii Wave Surge Energy Converter (HAWSEC) OSU O.H. Hinsdale Basin

The following information and metadata applies to both the Phase I (Hydrodynamics) and Phase II (Full System Power Take-Off) zip folders which contain testing data from the OSU (Oregon State University) O.H. Hinsdale Wave Research Laboratory, from both OSU and the University of Hawaii at Manoa (UH). See zip folders provided further below in the downloads section. For experimental data of the full system, including PTO, see Phase II dataset. There are two main directories in each Phases's zip folder: "OSU_data" and "UH_data". The "OSU_data" directory contains data collected from their DAQ (data acquisition system), which includes all wave gauge observations, as well as body motions derived from their Qualisys motion tracking system. The organization of the directory follows OSU's convention. Detailed information on the instrument setup can be found under "OSU_data/docs/setup/instm_locations". The experiments conducted are documented in the "OSU_data/docs/daq_logs", which provides the trial number to the corresponding data located under "OSU_data/data" in several formats (e.g., ".mat" and ".txt"). Inside the trial directory, data is provided for each of the instruments defined in "OSU_data/docs/setup/instm_locations". The "UH_data" directory contains data collected from their DAQ. The data is stored in a ".tdms" file format. There are free plug-ins for Microsoft Excel and MathWorks MATLAB to read the ".tdms" format. Below are a few links providing methods to read in the data, but a Google search should identify alternatives sources if these no longer exist (valid as of January 2024): Excel: http://www.ni.com/example/27944/en/ MATLAB: https://www.mathworks.com/matlabcentral/fileexchange/30023-tdms-reader The Excel plugin is recommend to get a quick overview of the data. The UH data is organized by directory name, in which the sub-directories for each experiment contains a directory whose name defines the wave height and period for the experimental data within. For example, a directory name "H02_T0275" corresponds to an experiment with wave height 0.1m and a period of 2.75s. For random wave data, the gamma value is also included in the directory name. For example, a directory name "H02_T0225_G18" corresponds to an experiment with a significant wave height of 0.2m, a peak period of 2.25s, and a gamma value of 1.8, with each spectra being a TMA spectrum. For the free decay experiments, the directory name is defined by the initial angular displacement. For example, a directory name "ang05_run01" corresponds to an experiment with an initial angular displacement of 5 degrees. There is a dataset in the UH data for each corresponding experiment defined in the OSU DAQ logs. The ".tdms" data is output from the DAQ at fixed intervals. Therefore, if multiple files are contained within the folder, the data will need to be stitched together. Within the UH dataset, there are two input channels from the OSU DAQ providing a random square wave signal for time synchronization ("ENV-WHT-0010") and a high/low signal ("ENV-WHT-0012") to identify when the wave maker is active (+5V). The UH data is logged as a collection of channel outputs. Channels not in use for the OSU testing (either Phase I or Phase II) are marked "nan" below. If the sensor is disconnected, it will record noise throughout the experiment. Below are the channel definitions in terms of what they measure: GPS Time = time CYL-POS-0001 = position between flap and fixed reference CYL-LCA-0001 = force between flap and hydraulic cylinder REC-LPT-0001 = nan REC-HPT-0001 = nan REC-HPT-0002 = nan REC-HPT-0003 = nan HHT-HPT-0001 = pressure at exhaust ("head" only) REC-FQC-0001 = nan REC-FQC-0002 = nan HHT-FQC-0001 = flow at exhaust ("head" only) ENV-WHT-0001 = nan ENV-WHT-0002 = nan ENV-WHT-0003 = nan ENV-WHT-0010 = random signal from OSU DAQ ENV-WHT-0012 = high/low signal from OSU DAQ Also included is a calibration curve to convert the string pot data to flap pi...

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Establishing a process-structure-property-performance framework for SLS additive manufacturing through integrated multiscale modeling

This study presents a comprehensive suite of high-fidelity computational models that integrate multiscale and multiphysics simulations to capture the full Selective Laser Sintering (SLS) additive manufacturing process—from initial melting and solidification to mechanical response under external loads. Process simulations are linked with mechanical analysis through Representative Volume Elements (RVEs), establishing a process-structure–property-performance framework. The interaction between laser light and polyamide 12 (PA12) powder is modeled, accounting for laser characteristics and the optical, thermal, and geometrical properties of the powder. The heat source is incorporated into a heat transfer model, coupled with crystallization kinetics and densification models to predict material density and crystallinity. The porosity distribution from the densification model and crystallinity interpolated from experimental data are used to construct the RVEs. A multi-mechanism constitutive model is then calibrated using mechanical tests to predict the stress–strain response. Simulation results show good agreement with experimental data in terms of porosity, crystallinity, and mechanical performance when sufficient laser power (62 W or higher) is used. This research supports the inverse design of 3D-printed structures by introducing a high-fidelity framework that combines multiscale and multiphysics modeling with experimental calibration for predictive and performance-driven additive manufacturing.

SLS↗
DOE OSTI2023

A dynamic kinetic model captures cell-free metabolism for improved butanol production

Cell-free systems are useful tools for prototyping metabolic pathways and optimizing the production of various bioproducts. Mechanistically-based kinetic models are uniquely suited to analyze dynamic experimental data collected from cell-free systems and provide vital qualitative insight. However, to date, dynamic kinetic models have not been applied with rigorous biological constraints or trained on adequate experimental data to the degree that they would give high confidence in predictions and broadly demonstrate the potential for widespread use of such kinetic models. In this work, we construct a large-scale dynamic model of cell-free metabolism with the goal of understanding and optimizing butanol production in a cell-free system. Using a combination of parameterization methods, the resultant model captures experimental metabolite measurements across two experimental conditions for nine metabolites at timepoints between 0 and 24 hours. Here, we present analysis of the model predictions, provide recommendations for butanol optimization, and identify the aldehyde/alcohol dehydrogenase as the primary bottleneck in butanol production. Sensitivity analysis further reveals the extent to which various parameters are constrained, and our approach for probing valid parameter ranges can be applied to other modeling efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Predictive modeling of NSTX discharges with the updated multi-mode anomalous transport module

Abstract The objective of this study is twofold: firstly, to demonstrate the consistency between the anomalous transport results produced by updated Multi-Mode Model (MMM) version 9.0.4 and those obtained through gyrokinetic simulations; and secondly, to showcase MMM’s ability to predict electron and ion temperature profiles in low aspect ratio, high beta NSTX discharges. MMM encompasses a range of transport mechanisms driven by electron and ion temperature gradients, trapped electrons, kinetic ballooning, peeling, microtearing, and drift resistive inertial ballooning modes. These modes within MMM are being verified through corresponding gyrokinetic results. The modes that potentially contribute to ion thermal transport are stable in MMM, aligning with both experimental data and findings from linear CGYRO simulations. The isotope effects on these modes are also studied and higher mass is found to be stabilizing, consistent with the experimental trend. The electron thermal power across the flux surface is computed within MMM and compared to experimental measurements and nonlinear CGYRO simulation results. Specifically, the electron temperature gradient modes (ETGM) within MMM account for 2.0 MW of thermal power, consistent with experimental findings. It is noteworthy that the ETGM model requires approximately 5.0 ms of computation time on a standard desktop, while nonlinear CGYRO simulations necessitate 8.0 h on 8 K cores. MMM proves to be highly computationally efficient, a crucial attribute for various applications, including real-time control, tokamak scenario optimization, and uncertainty quantification of experimental data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Appraising constrained second-order power corrections in HQET with Λ b →Λ c Ι⁢ν

We derive the Λ b →Λ c form factors for the Standard Model and beyond at second order in heavy quark effective theory, applying the recently proposed residual chiral expansion to reduce the set of unknown subsubleading hadronic functions to a single, highly constrained function, that is fully determined by hadron mass parameters at zero recoil. We fit a form factor parametrization based on these results to all available lattice QCD predictions and experimental data. We find that the constrained and predictive structure of the form factors under the residual chiral expansion is in excellent agreement with lattice QCD predictions and experimental data, as well as prior heavy-quark-effective-theory-based fits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Nuclear Data Sheets for A=69

Experimental data on ground- and excited-state properties for all known nuclei with mass number A=69 have been compiled and evaluated. States populated in radioactive decay, as well as in nuclear reactions, have been considered. For these nuclei, level and decay schemes, as well as tables of nuclear properties, are given in detail. In conclusion, this work supersedes the 2013 evaluation by C.D. Nesaraja (2014Ne01).

Nesaraja, Caroline D. [Oak Ridge National Laborato↗
DOE OSTI2026

Nuclear Structure and Decay Data for A=216 Isobars

Experimental data from reaction and decay studies on nuclei with A=216 have been reviewed. Elements included in this review span from mercury (Z=80) to uranium (Z=92). Based on the published data, level and decay schemes are presented for the evaluated nuclides. In conclusion, this work updates and supersedes the previous A=216 evaluation (2007Wu02).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Measurement of the Ne 18 ( α , p ) Na 21 reaction with the ANASEN active-target detector system at E c . m . = 2.5 – 4 MeV

The 18 Ne(α,p) 21 Na reaction plays a significant role in Type-I X-ray bursts. It is a major path in the breakout from the hot-CNO cycles to the synthesis of heavier elements in the αp- and rp-processes. An experiment to determine the cross section of this reaction was performed with the ANASEN active-target detector system, determining the cross section at energies between 2.5 and 4 MeV in the center-of-mass frame. The measured cross sections for reactions populating the ground state in 21 Na are consistent with results obtained from the time-inverse reaction, but significantly lower than the previously published experimental data of direct measurements. The total cross sections are also compared with those derived from indirect methods and statistical-model calculations. Furthermore, this experiment establishes a new experimental data set on the excitation function of the 18 Ne(α,p) 21 Na reaction, revealing the significance of the excited states' contributions to the total reaction cross section and allowing us to separate the contribution of the (α,2p) reaction. The impact of the measured cross section on thermal reaction rates is discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Models to Incorporate Reaction Mechanisms into DG-OSPREY: Fixed-Bed Simulations for Organic Iodides Capture Using Ag 0 Z

As one of the most potent radioisotopes released during spent nuclear fuel reprocessing, 129 I is strictly regulated and must be removed before discharge. Organic iodides (primarily alkyl iodides with different chain lengths, i.e., CH 3 I, C 4 H 9 I, and C 12 H 25 I) comprise ~2% of the total iodine in the reprocessing off-gases and are primarily present in vessel off-gas (VOG). Reduced silver mordenite (Ag 0 Z) is predominantly considered for the removal of radioiodine; however, its capture performance and underlying interaction processes with long-chain organic iodides are not fully understood. Two major tasks were accomplished in this study. First, to improve upon the previous experimental studies where Ag 0 Z was used to capture CH 3 I, C 4 H 9 I, and C 12 H 25 I at different concentrations, we comprehensively investigated the corresponding capture mechanisms by characterizing fully loaded Ag 0 Z samples. Second, computational codes were implemented to perform fixed-bed simulations that account for transport and reaction mechanisms. Scanning electron microscopy with energy dispersive X-ray analysis (SEM-EDX), powder X-ray diffraction (PXRD), UV-visible diffuse reflectance spectroscopy (UV-vis DRS), and thermogravimetric analysis (TGA) were conducted on Ag 0 Z samples that are saturated with I 2 , CH 3 I, C 4 H 9 I, and C 12 H 25 I), respectively. Results indicate that AgI is the predominant adsorption product regardless of the adsorbed iodine species, yet alkyl iodides with different carbon chain lengths may have different compositions of α- and γ-AgI. Synchrotron pair distribution function (PDF) measurements and TGA coupled with a Fourier transformed infrared detector (TGA FTIR) have been performed, and experimental data are currently analyzed. Results are expected to provide further insights into the adsorption mechanisms. The fixed-bed capture performance for CH 3 I was successfully simulated by solving mathematical equations that describe the underlying transport processes and adsorption reactions. The computational framework, Catalytic After Treatment System (CATS), that was originated in our research group, was used to solve the governing equations. Kinetic parameters, including the pore diffusivity and reaction rate constant were obtained by optimization techniques using data from thin-bed experiments performed at Oak Ridge National Laboratory. The performance of a deep bed predicted using the optimized parameters showed promising agreement with the experimental data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

A Novel Approach for Real-Time Quality Monitoring in Machining of Aerospace Alloy through Acoustic Emission Signal Transformation for DNN

Gamma titanium aluminide (γ-TiAl) is considered a high-performance, low-density replacement for nickel-based superalloys in the aerospace industry due to its high specific strength, which is retained at temperatures above 800 °C. However, low damage tolerance, i.e., brittle material behavior with a propensity to rapid crack propagation, has limited the application of γ-TiAl. Any cracks introduced during manufacturing would dramatically lower the useful (fatigue) life of γ-TiAl components, making the workpiece surface’s quality from finish machining a critical component to product quality and performance. To address this issue and enable more widespread use of γ-TiAl, this research aims to develop a real-time non-destructive evaluation (NDE) quality monitoring technique based on acoustic emission (AE) signals, wavelet transform, and deep neural networks (DNN). Previous efforts have opted for traditional approaches to AE signal analysis, using statistical feature extraction and classification, which face challenges such as the extraction of good/relevant features and low classification accuracy. Hence, this work proposes a novel AI-enabled method that uses a convolutional neural network (CNN) to extract rich and relevant features from a two-dimensional image representation of 1D time-domain AE signals (known as scalograms), subsequently classifying the AE signature based on pedigreed experimental data and finally predicting the process-induced surface quality. The results of the present work show good classification accuracy of 80.83% using scalogram images, in-situ experimental data, and a VGG-19 pre-trained neural network, establishing the significant potential for real-time quality monitoring in manufacturing processes.

36 MATERIALS SCIENCE↗
DOE OSTI2020

SAM Code Validation on Frictional Pressure Drop through Pebble Beds

The System Analysis Module (SAM) is currently under development at Argonne National Laboratory as a modern system-level modeling and simulation tool for safety analyses of advanced non-light water reactors. This report presents a recent effort to validate the capability of SAM to predict the frictional pressure drop through pebble beds. Selected experimental data were used for code validation, including data from test facilities at Texas A&M University, Missouri University of Science and Technology, and North-West University of South Africa. SAM implements three empirical correlations to predict frictional pressure drop: the classical Ergun correlation; the KTA correlation, which is widely used in high-temperature gas-cooled reactor applications; and the Eisfeld and Schnitzlein correlation, which explicitly considers wall effect. Code validation was performed using all three correlations. For all selected experimental data, the KTA correlation shows the best performance and agrees very well with experimental measurement; the Eisfeld and Schnitzlein correlation, explicitly considering wall effects, shows acceptable accuracy, while there is no evidence that it is better than the KTA correlation; the Ergun correlation, however, over-predicts frictional pressure drop for most selected data points.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Analysis of fusion alphas interaction with RF waves in D-T plasma at JET

This work studies the influence of RF waves in ICRH range of frequency on fusion alphas during the recent JET D-T campaign. Fusion alphas from D-T reactions are born with energies of about 3.5MeV and therefore have significant Doppler shift enabling synergistic interaction between them and RF waves at broad range of frequencies including the ones foreseen for future fusion machines ITER and SPARC. Resonant interaction between RF waves and alphas, also called synergistic effects, will modify the alpha distribution and ultimately will have an impact on alpha orbit losses and heating. Data from JET 3.43T/2.3MA pulses based on the hybrid scenario during the DTE2 campaign were used for the analysis in this study. The impact of synergistic effects on alpha orbit losses and alpha heating is assessed. Conclusions are based on analysis of experimental data for fast alphas losses, i.e. measurements from neutral particle analyser, fast ion losses scintillator detector, Faraday cups, and TRANSP simulations. Experimental data and TRANSP analysis indicate that there are indeed changes in the alphas' distribution function due to interaction with RF waves. Data from the scintillator detector and the Faraday cups were compared for pulses with and without ICRH power and versus cases with enhanced alpha losses due to MHD activities. The trends from these diagnostics consistently show no additional alpha losses due to interaction with RF waves. TRANSP predictions for the impact of the synergistic effects on alpha heating show up to 42% increase in alpha electron heating and up to 25% increase in alpha ion heating. These effects however become negligibly small, less than 1%, when alpha heating is compared to the total auxiliary hearting power in the investigated JET pulses.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

A comprehensive model of Drosophila epithelium reveals the role of embryo geometry and cell topology in mechanical responses

In order to understand morphogenesis, it is necessary to know the material properties or forces shaping the living tissue. In spite of this need, very few in vivo measurements are currently available. Here, using the early Drosophila embryo as a model, we describe a novel cantilever-based technique which allows for the simultaneous quantification of applied force and tissue displacement in a living embryo. By analyzing data from a series of experiments in which embryonic epithelium is subjected to developmentally relevant perturbations, we conclude that the response to applied force is adiabatic and is dominated by elastic forces and geometric constraints, or system size effects. Crucially, computational modeling of the experimental data indicated that the apical surface of the epithelium must be softer than the basal surface, a result which we confirmed experimentally. Further, we used the combination of experimental data and comprehensive computational model to estimate the elastic modulus of the apical surface and set a lower bound on the elastic modulus of the basal surface. More generally, our investigations revealed important general features that we believe should be more widely addressed when quantitatively modeling tissue mechanics in any system. Specifically, different compartments of the same cell can have very different mechanical properties; when they do, they can contribute differently to different mechanical stimuli and cannot be merely averaged together. Additionally, tissue geometry can play a substantial role in mechanical response, and cannot be neglected.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Noise reduction in X-ray photon correlation spectroscopy with convolutional neural networks encoder–decoder models

Abstract Like other experimental techniques, X-ray photon correlation spectroscopy is subject to various kinds of noise. Random and correlated fluctuations and heterogeneities can be present in a two-time correlation function and obscure the information about the intrinsic dynamics of a sample. Simultaneously addressing the disparate origins of noise in the experimental data is challenging. We propose a computational approach for improving the signal-to-noise ratio in two-time correlation functions that is based on convolutional neural network encoder–decoder (CNN-ED) models. Such models extract features from an image via convolutional layers, project them to a low dimensional space and then reconstruct a clean image from this reduced representation via transposed convolutional layers. Not only are ED models a general tool for random noise removal, but their application to low signal-to-noise data can enhance the data’s quantitative usage since they are able to learn the functional form of the signal. We demonstrate that the CNN-ED models trained on real-world experimental data help to effectively extract equilibrium dynamics’ parameters from two-time correlation functions, containing statistical noise and dynamic heterogeneities. Strategies for optimizing the models’ performance and their applicability limits are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Spectral and Temperature-Dependent Optical Metrology: Towards More Robust, Effective and Durable Materials for Concentrated Solar Power

The primary objective of this project is to develop reliable and standardized spectroscopic measurement techniques to determine radiative properties, specifically the emittance and reflectance, of materials relevant for the next generation (Gen3) concentrated solar power (CSP) technologies. Experimental measurements will span near- and mid-infrared wavelengths (1–20 µm) with emphasis on quantifying the influences of: (1) operating temperatures of 25–1000 °C, (2) thermal cycling, and (3) environmental exposure of materials during operation (vacuum/air). A secondary goal is to develop open-access and digitized databases to host and share experimental data, together with standardized measurement protocols and operating procedures to determine optical properties of materials. This project will also include reasonable emphasis on developing predictive modeling tools to augment experimental data to extract more fundamental and material-specific radiative properties.

14 SOLAR ENERGY↗
DOE OSTI2024

Modeling of Additively Manufactured Ceramic Heat Exchangers with Semi-Elliptical Cross-Section Flow Channels

An approximate and easily applied analytical model was developed for heat transfer calculations of heat exchangers consisting of multiple rows and columns of heat transfer fluid flow channels with semi-elliptical cross sections. Heat exchangers of this type are being developed by using ceramic material and additive manufacturing for high temperature and pressure-concentrating solar electric power plants. Calculations using the model require only the geometrical dimensions and flow conditions of the heat exchanger. Comparisons of modeling predictions, with both simulation results and experimental data, were conducted to verify the viability of the model. The results showed good agreement where almost all the modeling predictions were within 20% of the simulation results or the experimental data. Finally, the proposed modeling approach is more generally applicable to heat transfer analysis of heat exchangers with similar flow channel configurations to those considered in this study.

Ceramic↗
DOE OSTI2022

Collectivity in Ultraperipheral Pb+Pb Collisions at the Large Hadron Collider

In this work, we present the first full (3+1)D dynamical simulations of ultraperipheral Pb+Pb collisions at the Large Hadron Collider. Extrapolating from p + Pb collisions, we explore whether a quasireal photon γ* interacting with the lead nucleus in an ultraperipheral collision can create a many-body system exhibiting fluid behavior. Assuming strong final-state interactions, we provide model results for charged hadron multiplicity, identified particle mean transverse momenta, and charged hadron anisotropic flow coefficients, and compare them with experimental data from the ALICE and ATLAS Collaborations. The elliptic flow hierarchy between p + Pb and γ*+Pb collisions is dominated by the difference in longitudinal flow decorrelations and reproduces the experimental data well. We have demonstrated that our theoretical framework provides a quantitative tool to study particle production and collectivity for all system sizes, ranging from central heavy-ion collisions to small asymmetric collision systems at the Relativistic Heavy-Ion Collider and the Large Hadron Collider and even at the future Electron-Ion Collider.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗