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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 OSTI2025

ampworks: Battery analysis tools in Python [SWR-25-39]

Ampworks is a collection of tools designed to process experimental battery data with a focus on model-relevant analyses. It currently provides functions for incremental capacity analysis and GITT data processing, helping extract key properties for life and physics-based models (e.g., SPM and P2D). Some tools, like the incremental capacity analysis module, also include graphical user interfaces for ease of use. https://github.com/NREL/ampworks/ https://pypi.org/project/ampworks/

Randall, Corey [National Renewable Energy Laborato↗
NASA NTRS1979

A comparison of limited-area energetic processes between observations and primitive equation model predictions

Energetic analyses of the NMC initial conditions and NMC six-layer primitive equation operational prediction model 12-hr forecast for a developing cyclone are presented. Consideration is given to the total kinetic energy, the energetics of the divergent and nondivergent flows and the baroclinic (vertical shear flow) and barotropic (vertical mean flow) components of the kinetic energy. It is found that the model initial conditions lose 10-15% of the kinetic energy at various levels compared to a limited-area multivariate statistical analysis of the observational data, leading to a decrease in the horizontal kinetic energy flux, a misrepresentation of the synoptic scale wave system in the 12-hr forecast. Similar results are obtained for the nondivergent flow, while the divergent flow energetics are not reproduced accurately by the model. The horizontal flux terms of the vertical mean and vertical shear energetics are also not found to be reproduced in the upper levels, although horizontal flux contributions to the baroclinic component are improved at middle and lower levels. Finally, vertical shear kinetic energy generation is found to be well represented in the model prediction, however kinetic energy conversion between vertical shear and mean flow is not reproduced in the lower layer.

Alpert, J. C.↗
NASA NTRS2013

The Effect of Scale Dependent Discretization on the Progressive Failure of Composite Materials Using Multiscale Analyses

A multiscale modeling methodology, which incorporates a statistical distribution of fiber strengths into coupled micromechanics/ finite element analyses, is applied to unidirectional polymer matrix composites (PMCs) to analyze the effect of mesh discretization both at the micro- and macroscales on the predicted ultimate tensile (UTS) strength and failure behavior. The NASA code FEAMAC and the ABAQUS finite element solver were used to analyze the progressive failure of a PMC tensile specimen that initiates at the repeating unit cell (RUC) level. Three different finite element mesh densities were employed and each coupled with an appropriate RUC. Multiple simulations were performed in order to assess the effect of a statistical distribution of fiber strengths on the bulk composite failure and predicted strength. The coupled effects of both the micro- and macroscale discretizations were found to have a noticeable effect on the predicted UTS and computational efficiency of the simulations.

Ricks, Trenton M.↗
DOE OSTI2026

Monthly Mean In Situ Surface Flux Observations Paired with Satellite-Derived and Reanalysis-Based Flux Data for the Great Lakes Region, 2001–2020

Surface radiative and turbulent heat fluxes over the Great Lakes strongly influence regional hydrological and meteorological processes, and their accurate representation is critical for numerical weather prediction and coupled atmosphere–lake modeling. However, direct flux observations are spatially sparse across the region, so gridded reanalysis and satellite-derived products are often used for climatological analyses and model evaluation despite differences in their flux representations. This dataset provides processed, quality-controlled, monthly mean surface flux observations from the Great Lakes Evaporation Network (GLEN), AmeriFlux, and the National Data Buoy Center, paired with spatiotemporally matched flux estimates from two reanalysis products, the fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset (ERA5) and the Modern Era Reanalysis for Research and Applications, version 2 (MERRA-2), and two satellite-derived products, the Clouds and Earth's Radiant Energy Systems Energy Balanced and Filled (CERES-EBAF) and the Cloud, Albedo and Surface Radiation dataset from AVHRR data - Edition 3 (CLARA-A3). The dataset includes sixteen observational stations with variable temporal coverage within 2001–2020. For each station, a CSV file contains monthly time series of available flux variables, including surface downwelling shortwave radiation (SW), surface downwelling longwave radiation (LW), sensible heat (SH) flux, and latent heat flux (LH), alongside matched gridded product values where available. Columns in the CSV file correspond to different variables sourced from each dataset, with column titles structured as "{dataset}_{variable}". Columns with relevant metadata are also provided in each CSV file, including station latitude and longitude, monthly timestamps, and the name of the sourced observational data. These files are structured for direct use in common analysis tools, including Microsoft Excel, Python pandas, and Python matplotlib. This dataset supports climatological analysis of the Great Lakes regional surface energy budget, evaluation of satellite-derived and reanalysis-based flux products, and development or validation of flux representations in numerical weather prediction and coupled atmosphere–lake models.

Great Lakes↗
NASA NTRS2002

An Illumination Modeling System for Human Factors Analyses

Seeing is critical to human performance. Lighting is critical for seeing. Therefore, lighting is critical to human performance. This is common sense, and here on earth, it is easily taken for granted. However, on orbit, because the sun will rise or set every 45 minutes on average, humans working in space must cope with extremely dynamic lighting conditions. Contrast conditions of harsh shadowing and glare is also severe. The prediction of lighting conditions for critical operations is essential. Crew training can factor lighting into the lesson plans when necessary. Mission planners can determine whether low-light video cameras are required or whether additional luminaires need to be flown. The optimization of the quantity and quality of light is needed because of the effects on crew safety, on electrical power and on equipment maintainability. To address all of these issues, an illumination modeling system has been developed by the Graphics Research and Analyses Facility (GRAF) and Lighting Environment Test Facility (LETF) in the Space Human Factors Laboratory at NASA Johnson Space Center. The system uses physically based ray tracing software (Radiance) developed at Lawrence Berkeley Laboratories, a human factors oriented geometric modeling system (PLAID) and an extensive database of humans and environments. Material reflectivity properties of major surfaces and critical surfaces are measured using a gonio-reflectometer. Luminaires (lights) are measured for beam spread distribution, color and intensity. Video camera performances are measured for color and light sensitivity. 3D geometric models of humans and the environment are combined with the material and light models to form a system capable of predicting lighting conditions and visibility conditions in space.

Huynh, Thong↗
DOE OSTI2022

Application of machine learning approaches in the analysis of mass absorption cross-section of black carbon aerosols: Aerosol composition dependencies and sensitivity analyses

Physics-based models typically require an in-depth understanding of a phenomenon and assumptions of the underlying process(es), which are often hard to obtain in practice, whereas data-driven machine learning models learn the structure and patterns in the training data without any prior theoretical assumptions and then use inference to develop useful predictions. A novel machine learning-based algorithm has been previously developed for the prediction of black carbon mass absorption cross-section (MAC BC ) and applied to a variety of different atmospheric environments. In contrast to light scattering theories which require assumptions about the underlying physics, this algorithm uses time-series data of aerosol properties to estimate the temporally-varying MAC BC at 870 nm. Here, we analyze our algorithm and discuss the influence of aerosol optical properties (such as Ångström exponents and single scattering albedo) and chemical composition on the model outputs and the associated accuracy. Additionally, we conduct sensitivity analyses on our models to understand how the predictions change in response to different sets of input variables. Our support vector machine (SVM) for regression model is the least sensitive to variations in the input variables, although all models tend to exhibit a degradation to their accuracy when scattering Ångström exponents are less than one.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Projecting climate change in South America using variable‐resolution Community Earth System Model: An application to Chile

Abstract We introduce variable‐resolution enabled Community Earth System Model (VR‐CESM) results simulating historical and future climate conditions at 28 km over South America and 14 km over the Andes. Three 30‐year simulations are performed: a historic (1985–2014), a near future (2030–2059), and an end‐century (2070–2099) simulation under the RCP8.5 scenario. Historic results compare favourably to several temperature and precipitation reanalysis products, though local biases are present, particularly during austral summer. Future simulations highlight broad warming patterns (+3–6°C by end‐century) and heterogeneous precipitation responses across South America that qualitatively agree with prior modelling efforts. Our results reveal that the interaction between temperature and precipitation changes produce shifts in several Köppen–Geiger climates. Notable changes include the near‐elimination of the Andean Tundra or Alpine climates, a 15% decrease in Tropical Rainforests and a Tropical Savannah expansion of 20%. To provide a regionally focused analysis of projected climate change and to illustrate the benefits of variable resolution modelling, we analyse changes in the magnitude and trend in seasonal and daily temperature and precipitation in Chile. We also examined several metrics [e.g., snow water equivalent (SWE), temperatures on wet days, and days below 0°C] to evaluate potential impacts of climate change on the Chilean cryosphere between the end‐of‐century and historic periods, finding wide‐ranging indications of cryospheric decline. These changes are interpreted through reductions in the timing (1–2.5 months earlier peak SWE) and magnitude (200–1,000 mm SWE decreases) of water stored as snow in the Andes, a 10–30% decrease in number of cool season wet days with temperatures below 1°C, and 50–200 fewer days (annually) with minimum temperatures below 0°C. Our aim in producing a high‐resolution dataset of climate projections from VR‐CESM is to support analyses of climate change throughout South America but especially in vulnerable montane regions and to provide additional results for comparison with previous, ongoing, and upcoming modelling efforts.

variable-resolution global climate models↗
DOE OSTI2014

Internal air flow analysis of a bladeless micro aerial vehicle hemisphere body using computational fluid dynamic

This paper explain the analysis of internal air flow velocity of a bladeless vertical takeoff and landing (VTOL) Micro Aerial Vehicle (MAV) hemisphere body. In mechanical design, before produce a prototype model, several analyses should be done to ensure the product's effectiveness and efficiency. There are two types of analysis method can be done in mechanical design; mathematical modeling and computational fluid dynamic. In this analysis, I used computational fluid dynamic (CFD) by using SolidWorks Flow Simulation software. The idea came through to overcome the problem of ordinary quadrotor UAV which has larger size due to using four rotors and the propellers are exposed to environment. The bladeless MAV body is designed to protect all electronic parts, which means it can be used in rainy condition. It also has been made to increase the thrust produced by the ducted propeller compare to exposed propeller. From the analysis result, the air flow velocity at the ducted area increased to twice the inlet air. This means that the duct contribute to the increasing of air velocity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective

Long-term capacity expansion models of the U.S. electricity sector have long been used to inform electric sector stakeholders and decision-makers. With the recent surge in variable renewable energy (VRE) generators — primarily wind and solar photovoltaics — the need to appropriately represent VRE generators in these long-term models has increased. VRE generators are especially difficult to represent for a variety of reasons, including their variability, uncertainty, and spatial diversity. This report summarizes the analyses and model experiments that were conducted as part of two workshops on modeling VRE for national-scale capacity expansion models. It discusses the various methods for treating VRE among four modeling teams from the Electric Power Research Institute (EPRI), the U.S. Energy Information Administration (EIA), the U.S. Environmental Protection Agency (EPA), and the National Renewable Energy Laboratory (NREL). The report reviews the findings from the two workshops and emphasizes the areas where there is still need for additional research and development on analysis tools to incorporate VRE into long-term planning and decision-making. This research is intended to inform the energy modeling community on the modeling of variable renewable resources, and is not intended to advocate for or against any particular energy technologies, resources, or policies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Cloud-atmosphere impacts on the central Arctic surface energy budget (Final Report)

This project investigated how clouds and atmosphere-sea ice interactions shape the central Arctic surface energy budget using observations from the MOSAiC expedition and coordinated model experiments. Analyses focused on three themes. First, a new method applied to thermistor string data revealed that snow thermal conductivity is systematically higher than assumed in most models, strongly influencing conductive heat flux and sea ice growth, especially under clear skies. Second, a full annual cycle of surface energy budget observations, combined with detailed cloud microphysical retrievals, demonstrated how cloud regimes regulate radiative, turbulent, and conductive fluxes, driving seasonal contrasts in sea ice energy balance: in winter, radiative forcing elicits strong turbulent and conductive responses, while in summer excess energy is primarily partitioned into surface melt. Third, these observations were used to evaluate and improve regional and global forecast models. While some models captured key Arctic cloud-radiation states, most exhibited persistent deficiencies in representing liquid-containing clouds, snow-on-sea-ice processes, and flux responses to radiative forcing. Together, these results provide unprecedented benchmarks for understanding coupled Arctic processes, improve parameterizations of snow, sea ice, and cloud interactions, and highlight critical pathways by which atmospheric variability drives sea ice change in a rapidly evolving Arctic system. Lastly, the project was a resounding success, resulting in 38 peer-reviewed publications and dozens of presentations, while also supporting an early career scientist.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1996

Utilization of STRAT Data

One of the goals of the STRAT mission was to improve our understanding of transport in the stratosphere. We have used our coupled 2-D model to analyse transport between the tropics and midlatitudes using aircraft measurements of (CO2) and (N2O) made during the SPADE and ASHOE/MAESA campaigns (Boering et al. 1994) for model validation. We have further used the model to estimate errors in the experimental determination of the age of stratospheric air that arise from nonlinear increases of real tracers such as (CO2) and (SF6). The interpretation of measurements made during STRAT is still in progress. Most of the work performed under this contract has been described in the second year progress report, submitted in April of 1996. In the following, the research is summarized and some additional work that has become relevant in the meantime is described. We have developed an interactive model of the dynamics, chemistry and radiation of the stratosphere with partial support from this contract. The dynamics module integrates the primitive equations on a sphere. Lower boundary zonal winds and eddy geopotential heights are specified from observations. Chemistry and tracer transport are done in two dimensions. The chemistry model is a family model. Long lived species are transported and short lived species are determined in intervals of 5 to 10 days by assuming photochemical steady state. Full diurnal integrations with the fast species are performed periodically and diurnal coefficients, derived from the explicit integration are used to determine the steady state solution. Heating rates in the stratosphere are calculated from model ozone and the model temperatures and circulation fields are used in the chemistry transport module.

Source record↗
NASA NTRS1998

Collision-induced Absorption in the Infrared: A Data Base for Modelling Planetary and Stellar Atmospheres

Accurate knowledge of certain collision-induced absorption continua of molecular pairs such as H2-H2, H2-He, H2-CH4, CO2-CO2, etc., is a prerequisite for most spectral analyses and modelling attempts of atmospheres of planets and cold stars. We collect and regularly update simple, state of the art computer programs for the calculation of the absorption coefficient of such molecular pairs over a broad range of temperatures and frequencies, for the various rotovibrational bands. The computational results are in agreement with the existing laboratory measurements of such absorption continua, recorded with a spectral resolution of a few wavenumbers, but reliable computational results may be expected even in the far wings, and at temperatures for which laboratory measurements do not exist. Detailed information is given concerning the systems thus studied, the temperature and frequency ranges considered, the rotovibrational bands thus modelled, and how one may obtain copies of the FORTRAN77 computer programs by e-mail.

Borysow, Aleksandra↗
DOE OSTI2020

Mitigating energy demand sector emissions: The integrated modelling perspective

Mitigating carbon emissions in the current energy system will require fundamental changes of both the energy supply and the energy demand sectors. Previous global model-based analyses, however, have focused mostly on energy supply transformations, while the energy demand sector changes are less well understood. In this study, this knowledge gap is addressed by analysing in detail the projected future energy demand projections, and the required demand-side changes to reach stringent mitigation targets using a suite of integrated assessment models. We examine industry, transport and buildings sector pathways across four models and three different reference scenarios from the Shared-Socioeconomic Pathway framework which is used as a set of common future perspectives by the climate research community. The demand side mitigation efforts are compared to a more detailed, sector-specific, technology-oriented assessments of abatement potential based on a literature review for the year 2030. The results indicate that strong emission growth in the industry and transport sector can be attributed to increasing final energy per capita and population growth. In the stringent mitigation scenarios energy efficiency, electrification and switching to low carbon fuel are all required in the short term. In the green growth SSP1 scenario the required emission reduction is significantly less than other scenarios showing that the demand growth and the technology development largely affects the sectors’ mitigation challenge. The technology assessment estimates that in particular in the transport and buildings sector there is a higher potential to reduce demand-side emissions through energy efficiency improvements than currently envisioned in the integrated assessment models.

Edelenbosch, Oreane Y.↗
DOE OSTI2026

Systems-To-Atoms (S2A): enabling hydrogen for climate security

The project addresses a critical gap in hydrogen infrastructure by integrating system-level energy models with atomic-scale material simulations in a unified Systems-to-Atoms (S2A) framework. The motivation stems from the need to develop efficient, cost-effective, and durable hydrogen transport and utilization technologies to support decarbonization of hard-to-electrify sectors such as heavy-duty transportation. Current system models lack awareness of material performance mechanisms, while material-scale models do not account for system-level usage and variability. To bridge this divide, the team developed a co-simulation capability linking techno-economic analyses, reactor/process-flow modeling, and molecular-scale catalysis simulations. Applied to hydrogen delivery in California, the framework enabled comparative evaluations of compressed, cryogenic, and liquid organic hydrogen carrier (LOHC) pathways, highlighting how catalyst operation and unit process efficiency influence overall performance. The results demonstrate that no single material or transport mode is universally optimal; instead, heterogeneous solutions tuned to specific operational contexts deliver better performance. The project delivers a new capability for cross-scale material co-design, advancing hydrogen infrastructure readiness and informing DOE and LLNL missions in climate and energy resilience.

organic↗
DOE OSTI2023

Observationally driven Resource Assessment with CoupLEd models (ORACLE)

This project seeks to carry out a multifaceted analysis combining buoy observations, machine learning, turbulence, satellite data and high-resolution modeling. Our analyses will investigate air–sea interaction physics governing the variation of the winds with height and influence of clouds, uncertainty in coupled ocean-wave-atmosphere mesoscale models to capture certain key atmospheric phenomenon observed over the U.S. West Coast, impact of climate change, and the fidelity with which resource characterization models describe the range of observed offshore wind conditions. This project will focus its efforts on characterizing and assessing the atmospheric and oceanographic conditions along the U.S. West Coast.

Wind, Energy↗
DOE OSTI2022

Climate change impacts on the energy system: a model comparison

Increasing renewable energy use is an essential strategy for mitigating climate change. Nevertheless, the sensitivity of renewable energy to climatic conditions means that the energy system’s vulnerability to climate change can also become larger. In this research, we used two integrated assessment models and data from four climate models to analyse climate change impacts on primary energy use at a global and regional scale under a low-level (RCP2.6) and a medium-level (RCP6.0) climate change scenario. The impacts are analysed on the energy system focusing on four renewable sources (wind, solar, hydropower, and biomass). Globally, small climate impacts on renewable primary energy use are found in both models (5% for RCP2.6 and 6% for RCP6.0). These impacts lead to a decrease in the use of fossil sources for most regions, especially for North America and Europe under the RCP60 scenario. Overall, IMAGE and GCAM provide a similar signal impact response for most regions. E.g. in Asia (excluding China and India), climate change induces an increase in wind and hydropower use under the RCP6.0 scenarios; however, for India, a decrease in solar energy use can be expected under both scenarios and models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Jupiter: A Proposed Benchmark for Lead Void Worth with Plutonium

In the summer of 2017, a series of measurements were performed at the National Criticality Experiments Research Center (NCERC) in collaboration with the Japanese Atomic Energy Agency (JAEA) to measure the reactivity worth of voids in an array of lead and plutonium. This experiment, called Jupiter, measured multiple configurations of an array of aluminum boxes containing plutonium, aluminum, and lead plates. For some configurations, a selection of the lead interstitial plates were swapped with aluminum spacer frames to create “voids” in the lead interstitial material. Comparing the excess reactivity of the systems provides an empirical value of the lead void reactivity worth. These measurements were part of a larger collaboration to measure lead void reactivity worth with multiple nuclear material types and enrichments. This included other measurement series with both highly-enriched uranium (HEU), and a mixture of HEU and natural uranium to simulate low-enriched uranium (LEU). These data sets will be useful to the JAEA for a potential lead-bismuth cooled accelerator driven system. Additionally, there are not very many benchmarks in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) handbook sensitive to lead cross sections. Given that lead is widely used as a radiation shield and is part of new reactor designs, having more benchmarks in the ICSBEP handbook to better support cross section validation is important. Additional integral experiments could also aid in determining whether improvements have been made in new lead cross section evaluations. A benchmark evaluation for this experiment is being proposed in order to help fulfill these needs. Such evaluations contain both measured data, results from detailed transport code models, and analyses of the uncertainties associated with each. Examples of these uncertainties include the uncertainty in the measured excess reactivity, the composition of components, or their positioning within the model. This means it is easier to make comparisons between the measured and simulated data and better understand where improvements can be made to nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Neutrino Interaction Model and Uncertainties for MicroBooNE Analyses

The MicroBooNE experiment is searching for an excess of electron-like events at low neutrino energy, as well as making the first high-statistics measurements of neutrino interactions on argon. Interpretation of these results requires a reliable model of neutrino interaction physics with well-motivated uncertainties. This note describes the neutrino interaction model and uncertainties adopted for use in MicroBooNE’s cross section measurements and low-energy excess search.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗