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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Figure Descriptive Text Extraction Using Ontological Representation

Abstract Experimental research publications provide figure form resources including graphs, charts, and any type of images to effectively support and convey methods and results. To describe figures, authors add captions, which are often incomplete, and more descriptions reside in body text. This work presents a method to extract figure descriptive text from the body of scientific articles. We adopted ontological semantics to aid concept recognition of figure-related information, which generates human- and machine-readable knowledge representations from sentences. Our results show that conceptual models bring an improvement in figure descriptive sentence classification over word-based approaches.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Low-Energy Radon Backgrounds from Electrode Grids in Dual-Phase Xenon TPCs

The dual-phase xenon time projection chamber (TPC) is a powerful technology to detect rare interactions such as scatters of dark matter particles on nuclei. In particular, the built-in gain of ionization signals in a dual-phase TPC makes it sensitive to events in the few-electron regime, as expected from low-mass dark matter interactions. The pursuit of this low-energy sensitivity through ionization-only signal detection has so far been hindered by excessive electron backgrounds observed across experiments. Much of this background is attributed to the plate-out of $^{222}$Rn decay chain isotopes on the high voltage electrode grid surfaces that span the full cross section of the TPC. This work presents a first-principle model constructed for this background, the predictions of which are consistent with data from the LZ and LUX experiments. We then discuss mitigation strategies of this background in future dual-phase TPCs and the possibility of applying this grid background model to ionization-only dark matter searches.

Akerib, D. S. [SLAC; KIPAC, Menlo Park]↗
DOE OSTI2024

A Finite Difference informed Random Walk solver for simulating radiation defect evolution in polycrystalline structures with strongly inhomogeneous diffusivity

Diffusivity of species and defects on grain boundaries is usually several orders of magnitude larger than that inside grains. Such strongly inhomogeneous diffusivity requires prohibitively high computational demands for modeling microstructural evolution. Here, this paper presents a highly-efficient numerical solver, combining the Finite Difference method and Random Walk model, designed for accurately modeling strongly inhomogeneous diffusion within polycrystalline structures. The proposed solver, termed Finite Difference informed Random Walk (FDiRW), integrates a customized Finite Difference (cFD) scheme tailored for fast diffusion along thin grain boundaries represented by a single-layer of nodes. Numerical experiments demonstrate that the FDiRW solver achieves an impressive efficiency gain of 1560x compared to traditional Finite Difference methods while maintaining accuracy, making it feasible for personal computer machines to handle diffusional systems with strongly inhomogeneous diffusivity across static polycrystalline microstructures. The model has been successfully applied to simulate radiation defect evolution, showcasing its scalability to engineering scales in both length and time dimensions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Meteorological Conditions in Urban Sites in Knoxville, USA. 2025

This 2025 dataset, which contains five csv files, reports hourly air temperature, wind speed, solar radiation, incident short wave, reflected short wave, incident long wave, emitted long wave, net radiation, and photosynthetically active radiation (PAR) data measured in urban parks in Knoxville, Tennessee, USA. The sites include Cumberland Estates Park (CEP), Socially Equal Energy Efficient Development (SEEED), West Hills Park (WHP), West View Park (WVP), and Victor Ashe Park (VAP). Air temperature, wind speed, and solar radiation data were obtained from a METER ATMOS 41 All-in-One Weather Station (Pullman, Washington, USA). Incident and emitted radiation (shortwave and longwave) measurements were made using an Apogee (Logan, Utah, USA) net radiometer (Model SN-500-SS). The SQ-521 Full-Spectrum Quantum sensor (Apogee Instruments, Inc) recorded the PAR. The measurement data for all the sites started on January 1, 2025. and all measurement ended on December 31, 2025. This work is a part of a larger study which investigates the impact of soil moisture and plant evapotranspiration on ambient temperature and relative humidity in several city parks in Knoxville, Tennessee.

Salvador, Christian [ORNL] (ORCID:0000000283287777↗
DOE OSTI2022

Becoming a 10: A Closer Look at the U.S. Department of Energy Home Energy Score's Updates, Improvements, and Expansion

The U.S. Department of Energy (DOE)'s Home Energy Score provides homeowners, buyers, and renters directly comparable and credible information about a home's estimated energy use and costs. Certified Qualified Assessors conduct low-cost assessments to provide each home a 1-10 score alongside a set of cost-effective upgrades to improve the score. As of February 2022, hundreds of assessors have delivered over 175,000 scores to homes across the country. Originally released in 2012 using DOE2.1e as the modeling backend, after years of effort, a new version of Home Energy Score was released in 2021 utilizing DOE's flagship energy modeling software, EnergyPlus. The updated architecture leverages modeling advancements and enables new building technologies to be added to the Scoring Tool. The new release represents a leap forward in harmonizing modeling assumptions across DOE and industry programs. In this paper we discuss the rigorous approach to model comparison with DOE2 undertaken prior to the update, utilizing test homes and real homes from the Home Energy Score database to strike a balance between consistency and more accurate energy predictions. We also discuss additional new capabilities, including improvements made to the upgrade recommendations methodology, the inclusion of an energy cost estimate metric based on ResStock analysis for use in home appraisals, and improved data analysis for quality assurance. Finally, we look at the impact Home Energy Score has had over the last decade and its future potential as its uptake in state energy plans, local ordinances, utility programs, and real estate data continues to grow.

building energy modeling↗
DOE OSTI2020

nPINNs: Nonlocal physics-informed neural networks for a parametrized nonlocal universal Laplacian operator. Algorithms and applications

Physics-informed neural networks (PINNs) are effective in solving inverse problems based on differential and integro-differential equations with sparse, noisy, unstructured, and multifidelity data. PINNs incorporate all available information, including governing equations (reflecting physical laws), initial-boundary conditions, and observations of quantities of interest, into a loss function to be minimized, thus recasting the original problem into an optimization problem. In this paper, we extend PINNs to parameter and function inference for integral equations such as nonlocal Poisson and nonlocal turbulence models, and we refer to them as nonlocal PINNs (nPINNs). The contribution of the paper is three-fold. First, we propose a unified nonlocal Laplace operator, which converges to the classical Laplacian as one of the operator parameters, the nonlocal interaction radius $\delta$ goes to zero, and to the fractional Laplacian as $\delta$ goes to infinity. This universal operator forms a super-set of classical Laplacian and fractional Laplacian operators and, thus, has the potential to fit a broad spectrum of data sets. We also provide theoretical convergence rates with respect to $\delta$ and verify them via numerical experiments. Second, we use nPINNs to estimate the two parameters, $\delta$ and $\alpha$, characterizing the kernel of the unified operator. The strong non-convexity of the loss function yielding multiple (good) local minima reveals the occurrence of the operator mimicking phenomenon, that is, different pairs of estimated parameters could produce multiple solutions of comparable accuracy. Third, we propose another nonlocal operator with spatially variable order $\alpha(y)$, which is more suitable for modeling turbulent Couette flow. Our results show that nPINNs can jointly infer this function as well as $\delta$. More importantly, these parameters exhibit a universal behavior with respect to the Reynolds number, a finding that contributes to our understanding of nonlocal interactions in wall-bounded turbulence.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Identification of Performance Shaping Factor Lag and Linger Effects for Dynamic Human Reliability Analysis: Application of Experimental Data

Many researchers have emphasized the importance of dynamic probabilistic safety assessment (PSA), which highlights the necessity of studies for dynamic human reliability analysis (HRA). Dynamic HRA concentrates on a dynamic account of human actions or how performance shaping factors (PSFs) can dynamically modify the human error probability (HEP) over time. In contrast, existing static HRA does not consider human actions as changes over time or event progressions. Accordingly, previous research on dynamic HRA conceptually suggested PSF lag and linger effects to treat dependence between operator actions in dynamic HRA versus existing approaches. As follow-up research, this study attempted to identify PSF lag and linger effects for dynamic HRA on the basis of experimental data. Firstly, mathematical models for PSF lag and linger effects were developed based on a literature survey in the field of biology. Secondly, we analyzed experimental scenarios from a control room study to identify operator actions considered in PSA. Lastly, based on the experimental data, the effect of the stress PSF with lag and linger effects was compared to that without PSF lag and linger effects. This paper concludes with an overall discussion of PSF lag and linger effects based on the relation between the stress PSF and error occurrence.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Assessing mass balance-based inverse modeling methods via a pseudo-observation test to constrain NO x emissions over South Korea

This study constrains NO x emissions by utilizing mass balance–based inverse modeling methods and examines the optimization of inverse modeling conditions through a pseudo-observation test for South Korea, which has complex topography. Here, we applied mass balance–based inverse modeling methods such as Basic Mass Balance (BMB), Finite Difference Mass Balance (FDMB), and Iterative Finite Difference Mass Balance (IFDMB). We performed a numerical simulation of air quality using the Community Multi-scale Air Quality (CMAQ) model to calculate the NO 2 column density required for the inverse modeling. The pseudo-observation test was performed according to season, modeling resolution, and regridding methodology of satellite observation data to identify various conditions while applying the inverse modeling for South Korea. Comparing the inverse modeling results from the BMB, FDMB, and IFDMB methods, IFDMB was the most effective method in constraining NO x emissions in the South Korean region since it minimized smearing effects (i.e., transport-induced errors) through iterative calculations. The accuracy of the constrained NO x emissions using mass balance–based inversions in South Korea was the highest in the summer due to the minimized smearing effects, and the 9 km resolution modeling was the most efficient for inverse modeling of the region. In addition, the results of inverse modeling varied depending on the regridding methods, implying the importance of using a suitable regridding method and modeling resolution. This study used pseudo-observations, but the inversions are expected to be applied based on actual satellite data in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Regional Earthquake Ground Motion Simulations for Southern California With EQSIM: Insights From the 2008 Chino Hills, 2024 Highland Park, and 2021 Carson Earthquakes

This study presents physics-based, 3D simulations using the EQSIM framework for several earthquakes in the Los Angeles region. The primary objective was to assess the ability of deterministic physics-based ground motion simulations to reproduce the observed motions from historical events. The selected events included the mathematical equation M w 5.4 2008 Chino Hills, the mathematical equation M w 4.4 2024 Highland Park, and the mathematical equation M w 4.3 2021 Carson events. The simulated motions were evaluated by comparing the recorded and simulated seismograms, as well as the Fourier amplitude spectra, across multiple seismic stations. The SCEC 3D velocity model, CVM-S4.26.M01, was used to represent the regional geology, and ground motion simulations were carried out with a resolution of up to 5 Hz. The results indicate that the simulated motions captured the recorded motions up to approximately 4 Hz. While careful iterations regarding source parameters and corner frequencies were required, and, for the case of the Highland Park event, some of the near-source stations had relatively low accuracy, the present study established a positive step toward the utilization of physics-based simulations in practical applications. The computational efficiencies exhibited by EQSIM, especially on GPU clusters, further supported this assertion, as wall-clock times of simulations involving more than 10 billion grid points were as low as mathematical equation minutes. This permits ensemble simulations for a considered scenario event so that modeling uncertainties (e.g., source and geology) can be bracketed.

EQSIM↗
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 OSTI2022

Collisional Excitation and Non-LTE Modeling of Interstellar Chiral Propylene Oxide

Abstract The first set of theoretical rotational cross sections for propylene oxide (CH 3 CHCH 2 O) colliding with cold He atoms has been obtained at the full quantum level using a high-accuracy potential energy surface. By scaling the collision reduced mass, rotational rate coefficients for collisions with para-H 2 are deduced in the temperature range 5–30 K. These collisional coefficients are combined with radiative data in a non-LTE radiative transfer model in order to reproduce observations of propylene oxide made toward the Sagittarius B2(N) molecular cloud with the Green Bank and Parkes radio telescopes. The three detected absorption lines are found to probe the cold (∼10 K) and translucent ( n H ∼ 2000 cm −3 ) gas in the outer edges of the extended Sgr B2(N) envelope. The derived column density for propylene oxide is N tot ∼ 3 × 10 12 cm −2 , corresponding to a fractional abundance relative to total hydrogen of ∼2.5 × 10 −11 . The present results are expected to help our understanding of the chemistry of propylene oxide, including a potential enantiomeric excess, in the cold interstellar medium.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Quantum speed limit for the out-of-time-ordered correlator from an open-system perspective

Scrambling, the delocalization of initially localized quantum information, is commonly characterized by the out-of-time-ordered correlator (OTOC). Employing the OTOC–Renyi-2 entropy theorem, we derive a quantum speed limit for the OTOC, which sets a lower bound for the rate with which information can be scrambled. This bound becomes particularly tractable by describing the scrambling of information in a closed quantum system as an effective decoherence process of an open system interacting with an environment. We prove that decay of the OTOC can be bounded by the strength of the system-environment coupling and two-point environmental correlation functions. We validate our analytic bound numerically using the nonintegrable transverse field Ising model. Furthermore, our results provide a universal and model-agnostic quantitative framework for understanding the dynamical limits of information spreading across quantum many-body physics, condensed matter systems, and engineered quantum platforms.

Fermions↗
DOE OSTI2026

Dynamic modeling of near isothermal compressor for Transcritical carbon dioxide cycle to support efficiency improvement

Compressors are the primary components of energy consumption in vapor compression systems, drawing considerable research effort to reduce carbon emissions and improve energy efficiency. This work presents an isothermal compressor that integrates the compression chamber with the gas cooler to achieve near-isothermal compression, resulting in up to 30% energy reduction compared to traditional isentropic compression, according to the experiment results. A detailed dynamic model for the isothermal compression cycle of carbon dioxide (CO 2 ) is first presented, coupled with a liquid-piston model for chamber design. The model is experimentally validated on a 3.5 kW prototype, yielding a 6.2% relative error in chamber pressure and a 0.5 K deviation in chamber temperature. The liquid piston exhibits reduced frictional heating and geometric adaptability relative to the mechanical piston. Leveraging these attributes, the study further evaluates approaches that enhance the heat transfer to achieve isothermal compression by increasing the effective heat transfer area during compression. As a result, simulations demonstrated up to a 5% improvement in the coefficient of performance over the baseline case through chamber design, providing guidelines for design of isothermal compression cycle.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Behavior, Energy, Autonomy, Mobility Modeling Framework (BEAM) v1.0

The Behavior, Energy, Autonomy, and Mobility (BEAM) model is an integrated, agent-based travel demand simulation framework. Individual agents express preferences through a utility- maximizing evolutionary algorithm that minimizes each individual’s cost and time spent traveling via diverse modal options, including the competition for scarce supply resources such as parking spaces and charging infrastructure. BEAM simulates the essential elements that compose a dynamic transportation system. From the road network, parking and charging infrastructure, to the transit system and a synthetic population with plans and preferences, the virtual system is an amalgamation of multiple spatially resolved layers that together represent an integrated transportation system. BEAM is an extension to the MATSim (Multi-Agent Transportation Simulation) model, where agents employ reinforcement learning across successive simulated days to maximize their personal utility through plan mutation (exploration) and selecting between previously executed plans (exploitation). The BEAM model shifts some of the behavioral emphasis in MATSim from across-day planning to within- day planning, where agents dynamically respond to the state of the system during the mobility simulation. In BEAM, agents can plan across all major modes of travel including driving, walking, biking, transit, and demand-responsive ride hailing. It is designed to integrate with other open source transportation models, such as ActivitySim.

Lazarus, Jessica↗
DOE OSTI2023

Towards quantum black hole microstates

Abstract We study the cohomology of local BPS operators in$$ \mathcal{N} $$ N = 4 Yang-Mills theory. The finiteNcohomologies consist of the graviton part (subject to the stringy exclusion principle) and the rest which may describe black hole microstates in quantum AdS/CFT. We construct an infinite tower of non-graviton cohomologies in the SU(2) theory and study to what extent they simulate quantum black holes. We find signals for partial no-hair behaviors by showing that certain gravitons are forbidden to dress these cohomologies. This is in qualitative agreement with the perturbative hairs allowed around black holes, which also leads us to a natural setup to construct hairy BPS black holes. The cohomologies are simpler to study in the BMN matrix model truncation of the classical field theory.

Physics↗
DOE OSTI2024

A decade of insights: Delving into calendar aging trends and implications

Lithium-ion batteries remain at rest for extended periods and experience calendar aging. Although lithium-ion batteries are expected to perform for over 10 years at room temperature, long-term calendar aging data are seldom reported over such timescales. We present a dataset from 232 commercial cells across eight cell types and five manufacturers that underwent calendar aging across various temperatures and states of charge (SOCs) for up to 13 years. We analyze calendar aging across these conditions by tracking capacity loss and resistance growth as the cells degrade. This dataset is used to validate simple models, primarily the Arrhenius law and the power law, which explain the temperature and storage time on calendar aging. Certain applications of Arrhenius and power law fail to describe the dependence of capacity loss on temperature and resistance growth on storage time. Through this dataset, we demonstrate the complexity of calendar aging and the challenges in reducing trends into phenomenological models.

25 ENERGY STORAGE↗