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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Incorporating long-range dependence and fractal features in turbulence spectra

We introduce an advanced turbulence spectrum model developed from mathematical foundations from a covariance function class and empirically validated using extensive field data. This model captures the complex dynamics of long-range dependence, and fractal characteristics prevalent in riverine and atmospheric boundary layer (ABL) flows that are ignored by classical spectrum models, such as IEC (International Electrotechnical Commission) von Kármán and Kaimal model. The model delineates scaling behaviors across distinct frequency bands and offers substantial flexibility through five well-defined parameters each characterizing a distinct physical aspect of the velocity time series. A detailed procedure for obtaining each parameter from time series data is outlined. The comprehensive validations with field data from tidal currents and ABL flows substantiate the model’s fidelity in accurately replicating observed phenomena. This validation establishes the reliability of the proposed model and, when incorporated into stochastic full-field simulators such as TurbSim, demonstrates its potential to advance the predictive modeling and analysis of turbulent flows in environmental science and engineering contexts.

Cheng, Shyuan [Univ. of Illinois at Urbana-Champai↗
DOE OSTI2025

PHASE: Personalized Head-based Automatic Simulation for Electromagnetic properties in 7T MRI

Accurate and individualized human head models are becoming increasingly important for electromagnetic (EM) simulations. These simulations depend on precise anatomical representations to realistically model electric and magnetic field distributions, particularly when evaluating Specific Absorption Rate (SAR) within safety guidelines. State of the art simulations use the Virtual Population due to limited public resources and the impracticality of manually annotating patient data at scale. Here, this paper introduces Personalized Head-based Automatic Simulation for EM properties (PHASE), an automated open-source toolbox that generates high-resolution, patient-specific head models for EM simulations using paired T1-weighted (T1w) magnetic resonance imaging (MRI) and computed tomography (CT) scans with 14 tissue labels. To evaluate the performance of PHASE models, we conduct semi-automated segmentation and EM simulations on 15 real human patients, serving as the gold standard reference. The PHASE model achieved comparable global SAR and localized SAR averaged over 10 grams of tissue (SAR-10g), demonstrating its potential as a promising tool for generating large-scale human model datasets in the future. The code and models of PHASE toolbox have been made publicly available: https://github.com/hrlblab/PHASE.

Deep learning↗
DOE OSTI2025

Bottomonium meson spectrum with quenched and unquenched quark models

An open question in hadronic phenomenology concerns the “unquenching” effects of higher Fock space components on the leading Fock space description of hadrons. Here, we address this by making a comparison of the bottomonium spectrum as computed with the relativized Godfrey–Isgur quark model and an unquenched coupled channel model driven by the “$^3P_0$” mechanism of hadronic decay. Our results show that both models can describe the spectrum well, indicating that the influence of coupled channel effects can be largely absorbed into the parameters of the quenched quark model. This conclusion is reinforced by a perturbative calculation that shows that the spin-dependence of mass splittings due to mixing with the continuum recapitulates quenched quark model spin-dependent interactions. We also show that softening of the quark-antiquark wavefunction due to continuum mixing improves the description of vector bottomonium decay constants. Together, these results illustrate and substantiate the surprising robustness of simple constituent quark model descriptions of hadrons.

Sultan, M. Atif [Nankai Univ., Tianjin (China); Un↗
DOE OSTI2022

An electrochemical mesoscale tool for modeling the corrosion of structural alloys by molten salt

Understanding the impact of microstructure on corrosion rates can aid the development of corrosion-resistant alloys for molten salt reactors. Here in this work, we develop an electrochemical phase-field model for capturing the microstructure-dependent corrosion of structural alloys by molten salts. As a demonstration problem, we apply this model to capture the selective depletion of Cr from Ni-Cr grain boundaries during corrosion in molten FLiBe salt. We perform sensitivity analysis and model verification on 1D simulations to confirm that the model predicts diffusion-limited kinetics. The model is validated using 1D, 2D, and 3D simulations against experimental data for Ni-5Cr and Ni-20Cr corrosion in molten FLiBe. The 1D simulations predict the corrosion behavior with reasonable accuracy when using an effective diffusion coefficient that accurately represents the grain boundary diffusion. 2D simulations that represent the grain structure underpredict the corrosion. 3D simulations that represent the grain structure predict the corrosion with reasonable accuracy. The corrosion rate predicted by the 3D simulations is proportional to the average grain size at the alloy/salt interface.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

1.2-kV Vertical GaN PIN Rectifier With Ion-Implanted Floating Guard Rings

Here, this work reports on the fabrication and properties of a homojunction gallium nitride (GaN) p-i-n (PIN) rectifier fabricated on a free-standing GaN substrate. Uniform device performance is achieved with breakdown voltage (BV) >1.2 kV and low ON-resistance × area ( R ON A ). The statistics of the BV measurements show 58.5% of devices achieve BV >1.3 kV, and 71.1% of devices achieve BV >1.2 kV, as attributed to high quality and control in both epitaxial growth and device process. At room temperature, R ON A is 0.23 mΩ∙ cm 2 at a current density ( J ) of 6.9 kA/cm2. The corresponding Baliga’s figure of merit is >5.97 GW/cm 2 . Temperature-dependent reverse I – V measurements were performed and show a positive temperature coefficient of 0.42 V/K, indicating the avalanche capability of reverse breakdown. Further analysis with the Poole-Frenkel model on the temperature-dependent measurement suggested that a trap-assisted tunneling process contributed to the reverse leakage current. Floating guard rings (FGRs) formed by nitrogen implantation serve as an effective edge termination technique in these GaN PIN rectifiers, resulting in uniform performance in both forward and reverse bias.

42 ENGINEERING↗
DOE OSTI2020

Validation of Reactive Flow Capabilities in PAGOSA

Several reactive flow modeling capabilities are studied and applied to physics problems of interest in the PAGOSA hydrocode with an emphasis on validation. The Davis equation of state and the Arrhenius shock temperature dependent WSD (AWSD) reactive flow model have been implemented by the author in PAGOSA over the last year. These high-explosive modeling options along with the previously existing HE-JWL equation of state and the SURF/SURFplus reactive flow models are discussed, exercised and compared. Validation of the models analyze numerical results against experimental data from cylinder tests, two-stage gas gun experiments and proton radiography (pRad) experiments. Applications of the modeling options are explored involving both HMX based PBX 9501 and TATB based PBX 9502. The effect of mesh size is considered for prediction of phenomena such as corner turning and dead zones, and the relative code performance of the modeling options is discussed.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

Machine-learning techniques for model-independent searches in dijet final states

Anomaly detection methods used in a recent search for new phenomena by CMS at the CERN LHC are presented. The methods use machine learning to detect anomalous jets produced in the decay of new massive particles without depending on a specific theory model. The effectiveness of these approaches in enhancing sensitivity to various simulated signal samples is studied and compared using data collected in proton–proton collisions at a center-of-mass energy of 13 TeV. In an example analysis, the capabilities of anomaly detection methods are further demonstrated by identifying large-radius jets consistent with Lorentz-boosted hadronically decaying top quarks in a model-agnostic framework.

CMS↗
DOE OSTI2024

Reactive Modified Epoxy Resin and Its Miscible Blends Based on Recycled Oligomers from Solvolysis

Chemical depolymerization of fully cured epoxy resin with 20% reactive modifier was successfully performed via a solvent-assisted solvolysis process into low molecular weight recyclable oligomers (RO) at 240 °C in a pressure vessel at 650 psi for 4 h. The thermoset epoxy resin was depolymerized into transparent brown viscous fluid with a higher viscosity than the uncured epoxy resin with approximately 93% yield. Different concentrations of the RO were homogeneously mixed with the pure epoxy resin, and their curing kinetics, viscosity, FTIR, mechanical properties, DMA, and cross-link density were investigated. The curing kinetics of the pure reactive modified epoxy resin (baseline) and its mixtures with RO of different concentrations were investigated under both isothermal and nonisothermal conditions using small amplitude oscillatory shear flow. The elastic and viscous moduli (G′ and G″), complex viscosity (η*), and tan δ values were evaluated at different curing times and temperatures. The G′, G″, and η* increased dramatically, while tan δ decreased strongly by several orders of magnitude at the gel point. The zero-shear viscosity (η 0 ) was determined from the angular frequency dependent on η* based on the Cross model for different blend compositions in the liquid state before curing. The composition dependence of η 0 showed a positive deviation from the linear mixing rule and was well described by the Lecyar model. Here, the apparent activation energy of curing (E a ) was also evaluated according to the Arrhenius equation and was found to be 46 ± 2 kJ/mol regardless of the different contents of RO. For all blends up to 40 wt % RO, only one tan δ peak systematically shifting to lower temperatures with increasing content of RO was observed in the DMA measurements, indicating that the epoxy resin and the RO are miscible with up to 40 wt % RO.

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

Beam-energy and collision-system dependence of the linear and mode-coupled flow harmonics from STAR

Recent measurements and hydrodynamic model calculations suggest that the higher-order flow coefficients ν 4 and ν 5 have two contributions: a linear contribution driven by the initial-state eccentricities, εn, and a mode-coupled contribution derived from the lower-order eccentricity coefficients ε 2 and ε 3 . Measurements of these two contributions to ν 4 and ν 5 provide crucial insights to discern initial-state models and to constrain the temperature-dependent specific shear viscosity, η/s, of the plasma produced in heavy-ion collisions. In this work, we have employed the two-subevents cumulant technique to provide the first beam-energy and collision-system dependence of the linear and mode-coupled contributions to the higher-order flow harmonics. Furthermore, our results are shown and discussed for several centrality intervals for U+U collisions at √s NN = 193GeV, Au+Au collisions at √s NN = 200 ,and 54.4GeV and Cu+Au collisions at √s NN = 200GeV. The results are compared with similar studies performed by the ALICE experiment at LHC.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

COZMIC. III. Cosmological Zoom-in Simulations of Self-interacting Dark Matter with Suppressed Initial Conditions

We present eight cosmological dark matter (DM)-only zoom-in simulations of a Milky Way–like system that include suppression of the linear matter power spectrum P(k), and/or velocity-dependent DM self-interactions, as the third installment of the COZMIC suite. We consider a model featuring a massive dark photon that mediates DM self-interactions and decays into massless dark fermions. The dark photon and dark fermions suppress linear matter perturbations, resulting in dark acoustic oscillations in P(k), which ultimately affect dwarf galaxy scales. The model also features a velocity-dependent elastic self-interaction between DM particles (SIDM), with a cross section that can alleviate small-scale structure anomalies. For the first time, our simulations test the impact of P(k) suppression on gravothermal evolution in an SIDM scenario that leads to core collapse in (sub)halos with present-day virial masses below ≈10 9 M ⊙ . In simulations with P(k) suppression and self-interactions, the lack of low-mass (sub)halos and the delayed growth of structure reduce the fraction of core-collapsed systems relative to SIDM simulations without P(k) suppression. In particular, P(k) suppression that saturates current warm DM constraints almost entirely erases core collapse in isolated halos. Models with less extreme P(k) suppression produce core collapse in ≈20% of subhalos and ≈5% of isolated halos above 10 8 M ⊙ , and also increase the abundance of extremely low-concentration isolated low-mass halos relative to SIDM. These results reveal a complex interplay between early and late-Universe DM physics, revealing new discovery scenarios in the context of upcoming small-scale structure measurements.

dark matter↗
DOE OSTI2021

A crystal plasticity finite element model embedding strain-rate sensitivities inherent to deformation mechanisms: Application to alloy AZ31

We report the fundamental power-law relationship representing the flow rule in crystal visco-plasticity ensures uniqueness in the selection of slip systems accommodating imposed plastic strain-rates. The power-law relationship also introduces an artificially high strain-rate sensitivity in crystal plasticity simulations, unless a high value of the power-law exponent is used. However, the use of high values for the exponent is limited by numerical tractability. This paper presents a numerical method implemented in a crystal plasticity finite element (CPFE) model for embedding any value of the power-law exponent reflecting the true material strain-rate sensitivity. Importantly, the method does not increase computation time involved in the simulations. The enhanced CPFE model is used to interpret and predict a complex strain-rate sensitive response and microstructural evolution of AZ31 Mg alloy. Measured values of strain-rate sensitivity for slip and twinning modes are used in the simulations. Calculations show that the model successfully captures the phenomena pertaining to the effect of changing applied strain-rate on the mechanical response including flow stress and evolution of texture and twinning for a broad range of strain-rates ranging from 10 -3 s -1 to 10 3 s -1 and loading orientations in tension and compression. It is shown that such predictions are a consequence of not only relative amounts of slip and twinning activities driven by a set of accurately characterized hardening law parameters but also values of the strain-rate sensitivities inherent to individual deformation mechanisms. Besides, the model validates the measured strain-rate dependency of deformation mechanisms while accurately reproducing the mechanical data. Hence, the model can be used to verify and further refine or infer measured strain-rate sensitivity per deformation mechanism by reproducing experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Droplet breakup by multimodal nonlinear Rayleigh Taylor instability

A droplet impacted by a shock wave will undergo a process of fragmentation due to the development of interfacial hydrodynamic instabilities. The interface experiences variable acceleration and shear that result in the development of both inertial (Rayleigh–Taylor) and shear (Kelvin–Helmholtz) instabilities. These perturbations grow in time and drive the fragmentation and breakup of the deformed droplet. Experiments are performed on nominally 0.86 mm water droplet subjected to a Mach 7.6 detonation wave, resulting in a high Weber number (~36,000) breakup event. Perturbation growth is measured from a series of high-speed (> MHz) shadowgraph images. It is proposed that, given the size of the large-scale perturbations observed in experiments, these instabilities are growing in the non-linear regime and can be described by bubble-merger models for nonlinear mixing. Calculations are performed for the growth rates and size of these instabilities using deformation and external flow models to establish the time-dependent boundary conditions. The concurrence of the measured perturbation widths and the predictions of the simple model lend credence to the theory. This novel approach serves to open a new avenue in the characterization of droplet breakup via hydrodynamic instabilities.

Droplet breakup↗
DOE OSTI2025

Genetic programming for the nuclear many-body problem: a guide

Genetic Programming (GP) is an evolutionary algorithm that generates computer programs, or mathematical expressions, to solve complex problems. In this Guide, we demonstrate how to use GP to develop surrogate models to mitigate the computational costs of modeling atomic nuclei with ever increasing complexity. The computational burden escalates when uncertainty quantification is pursued, or when observables must be globally computed for thousands of nuclei. By studying three models in which the mean field depends on the total particle density self-consistently, we show that by constructing reduced order models supported by GP one can speed up many-body computations by several orders of magnitude with a negligible loss in accuracy.

dimensionality reduction↗
DOE OSTI2023

CCSI Toolset 3.19 Release

CCSI Toolset 3.19 Release Highlights A gradient generation tool was developed to support GENN models in FOQUS. Certain machine learning tools train gradient-enhanced neural network (GENN) models which can be more accurate for complex datasets given a priori knowledge of model derivatives. However, the derivatives must be known beforehand and are not often available for process data. This tool automatically predicts the gradients for a training dataset in a form usable by common GENN trainers, such as Surrogate Modeling Toolbox. Support was added for Surrogate Modeling Toolbox GENN models in FOQUS, including updates to the run methods, node properties, test framework, documentation and optional dependencies list. Users can train/save Surrogate Modeling Toolbox gradient-enhanced neural network (GENN) models with custom objects and produce .pkl files compatible with the Machine Learning/Artificial Intelligence Plugin in FOQUS. A simpler implementation of the ordering algorithm in the Sequential Design of Experiments (SDOE) module was included. The SDOE examples documentation was updated. The Optimality-Based Design of Experiments was updated to improve the error handling when the results are None.

AS↗
DOE OSTI2023

Understanding the fusion yield dependencies in OMEGA DT-layered implosion experiments using a physics-based statistical mapping model

Improving the performance of inertial confinement fusion implosions requires physics models that can accurately predict the response to changes in the experimental inputs. Good predictive capability has been demonstrated for the fusion yield using a statistical mapping of simulated outcomes to experimental data [Gopalaswamy et al., Nature 565(771), 581–586 (2019)]. In this paper, a physics-based statistical mapping approach is used to extract and quantify all the major sources of degradation of fusion yield for direct-drive implosions on the OMEGA laser. Here, the yield is found to be dependent on the age of the deuterium tritium fill, the ℓ = 1 asymmetry in the implosion core, the laser beam-to-target size ratio, and parameters related to the hydrodynamic stability. A controlled set of experiments were carried out where only the target fill age was varied while keeping all other parameters constant. The measurements were found to be in excellent agreement with the fill age dependency inferred using the mapping model. In addition, a new implosion design was created, guided by the statistical mapping model by optimizing the trade-offs between increased laser energy coupling at larger target size and the degradations caused by the laser beam-to-target size ratio and hydrodynamic instabilities. When experimentally performed, an increased fusion yield was demonstrated in targets with larger diameters.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Quantifying molecular deformation in polymer melts by a generalized Zimm plot approach

The Zimm plot has been widely used to characterize the molecular dimensions of polymers from small-angle scattering experiments, where the reciprocal intensity is analyzed as a function of the square of the magnitude of the scattering wavevector Q. Here, this work explores the benefits of analyzing the reciprocal scattering intensity from deformed polymers, extending the original Zimm plot to anisotropic materials. In the small-angle limit, a tensorial extension of the Guinier law is found for the gyration tensor and the reciprocal single-chain structure factor. In the high-Q limit, application of the spherical harmonic expansion technique to the reciprocal structure factor permits direct model-independent analysis of spatially dependent molecular deformation of polymers. Additionally, the contributions from high-order spherical harmonics become insignificant in the reciprocal-intensity representation. The proposed generalized Zimm plot approach is demonstrated computationally with the affine deformation model and the Rouse model, and experimentally with small-angle neutron scattering measurements of deformed polystyrene melts.

36 MATERIALS SCIENCE↗
DOE OSTI2024

WIND Toolkit Long-Term Ensemble Dataset

WIND Toolkit Long-term Ensemble Dataset (WTK-LED), an updated version of the meteorological WIND Toolkit, is a meteorological dataset providing high-resolution time series, including interannual variability and model uncertainty of wind speed at every modeling grid point to indicate ranges of possible wind speeds. The data were produced using the Weather Research and Forecasting Model (WRF). The vertical grid used in WTK-LED includes many vertical layers in the atmospheric boundary layer to provide information of atmospheric quantities across the rotor layer of utility scale and distributed wind turbines. The WTK-LED includes: (1) Numerical simulations of wind speed and other meteorological variables covering the contiguous United States (CONUS) and Alaska, with high-resolution (5-minute [min], 2-kilometer [km]) data for 3 years (2018-2020): WTK-LED CONUS, WTK-LED Alaska. (2) Climate simulations from Argonne National Laboratory covering North America, including Alaska, Canada, and most of Mexico and the Caribbean islands. These simulations complement the new WTK-LED to offer a 4-km, hourly dataset covering 20 years (2001-2020): WTK-LED Climate. (3) Specific long-term, high-resolution offshore simulations have been conducted separately for the U.S. coasts, Hawaii, and the Great Lakes, leading to the 2023 National Offshore Wind dataset: NOW-23. The data for Hawaii include land-based data and are part of WTK-LED Hawaii. Because the accuracy of simulations from a mesoscale model, such as WRF, varies depending on the location and weather situation, and can reach up to several m/s for wind speed, we provide simulated wind speed uncertainty estimates to the community to be used in conjunction with the deterministic model simulations. This dataset was developed to satisfy a wide group of stakeholders across various wind energy disciplines, including but not limited to stakeholders in the distributed and utility scale wind industry, the new emerging airborne wind energy field, grid integration, power systems modeling, environmental modeling, and researchers in academia, and to close some of the gaps that current public datasets have. Based on our validation results to date, we suggest use cases and applications for each dataset of the WTK-LED as shown in "WTK-LED Use Cases" resource below.

Array↗