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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

A simplified model for estimating population-scale energy impacts of building envelope air-tightening and mechanical ventilation retrofits

Changing the air exchange rate of a home (the sum of the infiltration and mechanical ventilation airflow rates) affects the annual thermal conditioning energy. Large-scale changes to air exchange rates of the housing stock can significantly alter the residential sector’s energy consumption. However, the complexity of existing residential energy models is a barrier to the accurate quantification of the impact of policy changes on a state or national level.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Comparison of software models for energy savings from cool roofs

For this study, a web-based Roof Savings Calculator (RSC) has been deployed for the United States Department of Energy as an industry-consensus tool to help building owners, manufacturers, distributors, contractors and researchers easily run complex roof and attic simulations. RSC simulates multiple roof and attic technologies for side-by-side comparison including reflective roofs, different roof slopes, above sheathing ventilation, radiant barriers, low-emittance roof surfaces, duct location, duct leakage rates, multiple substrate types, and insulation levels. Annual simulations of hour-by-hour, whole-building performance are used to provide estimated annual energy and cost savings from reduced HVAC use. While RSC reported similar cooling savings to other simulation engines, heating penalty varied significantly. RSC results show reduced cool roofing cost-effectiveness, thus mitigating expected economic incentives for this countermeasure to the urban heat island effect. This paper consolidates comparison of RSC's projected energy savings to other simulation engines including DOE-2.1E, AtticSim, Micropas, and EnergyPlus. Also included are comparisons to previous simulation-based studies, analysis of RSC cooling savings and heating penalties, the role of radiative heat exchange in an attic assembly, and changes made for increased accuracy of the duct model. Finally, radiant heat transfer and duct interaction not previously modeled is considered a major contributor to heating penalties.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Dynamically Downscaled Hourly Future Weather Data with 12-km Resolution Covering Most of North America

This is an hourly future weather dataset for energy modeling applications. The dataset is primarily based on the output of a regional climate model (RCM), i.e., the Weather Research and Forecasting (WRF) model version 3.3.1. The WRF simulations are driven by the output of a general circulation model (GCM), i.e., the Community Climate System Model version 4 (CCSM4). This dataset is in the EPW format, which can be read or translated by more than 25 building energy modeling programs (e.g., EnergyPlus, ESP-r, and IESVE), energy system modeling programs (e.g., System Advisor Model (SAM)), indoor air quality analysis programs (e.g., CONTAM), and hygrothermal analysis programs (e.g., WUFI). It contains 13 weather variables, which are the Dry-Bulb Temperature, Dew Point Temperature, Relative Humidity, Atmospheric Pressure, Horizontal Infrared Radiation Intensity from Sky, Global Horizontal Irradiation, Direct Normal Irradiation, Diffuse Horizontal Irradiation, Wind Speed, Wind Direction, Sky Cover, Albedo, and Liquid Precipitation Depth. The weather data is created for two emissions scenarios: RCP4.5 and RCP8.5 and spans two 10-year time slices in the future: 2045 - 2054 and 2085 - 2094. It offers a spatial resolution of 12 km by 12 km with extensive coverage across most of North America. Due to the enormous size of the entire dataset, in the first stage of its distribution, we provide 20 years of future weather data for the centroid of each Public Use Microdata Area (PUMA), excluding Hawaii. PUMAs are non-overlapping, statistical geographic areas that partition each state or equivalent entity into geographic areas containing no fewer than 100,000 people each. The 2,378 PUMAs as a whole cover the entirety of the U.S. The weather data can be utilized alongside the large-scale energy analysis tools, ResStock and ComStock, developed by National Renewable Energy Laboratory, whose smallest resolution is at the PUMA scale. The data for RCP4.5 is still being processed and will be published soon.

Array↗
DOE OSTI2024

Reduced Order Costs for CO 2 Saline Storage for Use in Energy Market Models

This report provides the results of a collaboration between NETL, Los Alamos National Laboratory (LANL) and FECM headquarters personnel. NETL's FECM/NETL CO 2 Saline Storage Cost Model (CO2_S_COM) and LANL's Sequestration of CO 2 Tool (SCO 2 T) model were run with the same assumptions to generate costs for 314 potential storage formations in the U.S. The two models gave similar results. The results from CO2S_COM were then aggregated into a smaller number of costs that can be utilized in energy market models. The report has a companion spreadsheet called red_ord_costs_CO2_S_COM with the reduced order costs. The spreadsheet can be viewed online here: https://www.netl.doe.gov/energy-analysis/details?id=fb6d93df-0702-47aa-8147-59a5ae0c7cfd

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

One dimensional heavy ion beam transport: Energy independent model

Attempts are made to model the transport problem for heavy ion beams in various targets, employing the current level of understanding of the physics of high-charge and energy (HZE) particle interaction with matter are made. An energy independent transport model, with the most simplified assumptions and proper parameters is presented. The first and essential assumption in this case (energy independent transport) is the high energy characterization of the incident beam. The energy independent equation is solved and application is made to high energy neon (NE-20) and iron (FE-56) beams in water. The numerical solutions is given and compared to a numerical solution to determine the accuracy of the model. The lower limit energy for neon and iron to be high energy beams is calculated due to Barkas and Burger theory by LBLFRG computer program. The calculated values in the density range of interest (50 g/sq cm) of water are: 833.43 MeV/nuc for neon and 1597.68 MeV/nuc for iron. The analytical solutions of the energy independent transport equation gives the flux of different collision terms. The fluxes of individual collision terms are given and the total fluxes are shown in graphs relative to different thicknesses of water. The values for fluxes are calculated by the ANASTP computer code.

Farhat, Hamidullah↗
NASA NTRS1979

Differences between seasonal and mean annual energy balance model calculations of climate and climate sensitivity

The paper extends a simple Budyko-Sellers mean annual energy balance climate model with diffusive transport to include a seasonal cycle. In the model the latitudinal distribution of the zonal average surface temperature is represented by Legendre polynomials and its time-dependence by a Fourier sine-cosine series, and it has three parameters adjusted so that the observed amplitudes of the Northern Hemisphere zonal mean surface temperature are recovered. The seasonal model is used to reveal how the annual mean climate and the sensitivity to changes in incident radiation differ from the predictions obtained with the corresponding mean annual model. The distribution of the incident solar radiation in the models is shown to be insensitive to changes in the eccentricity and the longitude of perihelion and sensitive only to changes in the obliquity of the earth, and for past orbital changes both the seasonal and the mean annual model fail to produce glacial advances of the magnitude that are thought to have occurred.

North, G. R.↗
DOE OSTI2017

Modeling turbulent energy behavior and sudden viscous dissipation in compressing plasma turbulence

Here, we present a simple model for the turbulent kinetic energy behavior of subsonic plasma turbulence undergoing isotropic three-dimensional compression, which may exist in various inertial confinement fusion experiments or astrophysical settings. The plasma viscosity depends on both the temperature and the ionization state, for which many possible scalings with compression are possible. For example, in an adiabatic compression the temperature scales as 1/L 2 , with L the linear compression ratio, but if thermal energy loss mechanisms are accounted for, the temperature scaling may be weaker. As such, the viscosity has a wide range of net dependencies on the compression. The model presented here, with no parameter changes, agrees well with numerical simulations for a range of these dependencies. This model permits the prediction of the partition of injected energy between thermal and turbulent energy in a compressing plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Report of the Topical Group on Physics Beyond the Standard Model at Energy Frontier for Snowmass 2021

This is the Snowmass2021 Energy Frontier (EF) Beyond the Standard Model (BSM) report. It combines the EF topical group reports of EF08 (Model-specific explorations), EF09 (More general explorations), and EF10 (Dark Matter at Colliders). The report includes a general introduction to BSM motivations and the comparative prospects for proposed future experiments for a broad range of potential BSM models and signatures, including compositeness, SUSY, leptoquarks, more general new bosons and fermions, long-lived particles, dark matter, charged-lepton flavor violation, and anomaly detection.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Multiphysics Degradation Modeling of Energy Storage Materials via RKPM with a Neural Network-Enhancement

In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. A coupled electro-chemo-mechanical reproducing kernel particle method (RKPM) formulation is developed, and a patch-test is formulated to certify optimal convergence of the proposed RKPM method for the coupled physics system. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), pixel-based model construction by RKPM is then used to represent the complex material microstructures for modeling the coupled physics of these systems. Further, a neural network-enhanced reproducing kernel particle method (NN-RKPM) [1, 2] is introduced to effectively model damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. Reference: [1] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, pp 4422-4454, https://doi.org/10.1002/nme.7040, 2022. [2] Baek, J., Chen, J. S., "A Neural Network-Based Enrichment of Reproducing Kernel Approximation for Modeling Brittle Fracture", Computer Methods in Applied Mechanics and Engineering Vol. 410, 116590, 2024.

electro-chemo-mechanical coupling↗
DOE OSTI2024

Renewable Energy Potential Model: Priority Geothermal Leasing Areas ReEDs Results

This dataset contains the results of a study conducted by the National Renewable Energy Laboratory (NREL) to identify potential future priority geothermal leasing areas on Bureau of Land Management (BLM) and United States Forest Service (USFS) lands. The analysis uses the Regional Energy Deployment System (ReEDS) model to evaluate geothermal resource potential under different scenarios of resource depth and technology combinations through the year 2050. The study considers geothermal resource potential, natural resource conflicts, and transmission access to categorize areas into near, mid, and far deployment priorities. The dataset includes outputs from the ReEDS model, such as geothermal capacity, generation, system costs, and emissions under various economic and technical scenarios. Favorability site data with geographic coordinates and site-specific attributes (e.g., resource favorability, land type) are also provided. Supporting resources include a technical report detailing methodologies and assumptions, along with a link to the ReEDS model GitHub repository, which requires GAMS and Python software for execution.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

pvlib python: a python package for modeling solar energy systems

pvlib python is a community-supported open source tool that provides a set of functions and classes for simulating the performance of photovoltaic energy systems. pvlib python aims to provide reference implementations of models relevant to solar energy, including for example algorithms for solar position, clear sky irradiance, irradiance transposition, DC power, and DC-to-AC power conversion. pvlib python is an important component of a growing ecosystem of open source tools for solar energy (William F. Holmgren, Hansen, Stein, & Mikofski, 2018).

14 SOLAR ENERGY↗
DOE OSTI2018

Development of an integrated model for energy systems planning and carbon dioxide mitigation under uncertainty – Tradeoffs between two-level decision makers

Highlights: • A bi-level model is developed for energy systems planning and carbon dioxide mitigation. • Tradeoffs between two-level decision-makers’ demands are quantified under uncertainty. • The energy and environmental impact of CO{sub 2} mitigation policy is analyzed for Beijing. • Results provide a range of decision alternatives between system optimality and reliability. A bi-level fuzzy programming (BFLP) method was developed for energy systems planning (ESP) and carbon dioxide (CO{sub 2}) mitigation under uncertainty. BFLP could handle fuzzy information and leader-follower problem in decision-making processes. It could also address the tradeoffs among different decision makers in two decision-making levels through prioritizing the most important goal. Then, a BFLP-ESP model was formulated for planning energy system of Beijing, in which the upper-level objective is to minimize CO{sub 2} emission and the lower-level objective is to minimize the system cost. Results provided a range of decision alternatives that corresponded to a tradeoff between system optimality and reliability under uncertainty. Compared to the single-level model with a target to minimize system cost, the amounts of pollutant/CO{sub 2} emissions from BFLP-ESP were reduced since the study system would prefer more clean energies (i.e. natural gas, LPG and electricity) to replace coal fuel. Decision alternatives from BFLP were more beneficial for supporting Beijing to adjust its energy mix and enact its emission-abatement policy. Results also revealed that the low-carbon policy for power plants (e.g., shutting down all coal-fired power plants) could lead to a potentially increment of imported energy for Beijing, which would increase the risk of energy shortage. The findings could help decision makers analyze the interactions between different stakeholders in ESP and provide useful information for policy design under uncertainty.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Quantifying and Zoning Urban Heat Island Effects Using Unsupervised Machine Learning

This work explores the Urban Heat Island (UHI) effects in Maricopa County, Arizona, employing a simulation-based approach that combines large-scale building energy modeling with advanced spatial analysis. Utilizing the Automatic Building Energy Modeling (AutoBEM) software suite, we simulated the energy consumption for approximately 1.35 million buildings based on the Model America version 1.0 (MAv1) dataset. Our methodology incorporated spatial analysis at multiple scales, including individual buildings, clusters of zones determined by K-means clustering, and geographical level evaluation based on Zip codes. The results revealed significant variations in energy consumption and heat emissions across different building types and urban zones. High-emission hotspots identified through clustering pointed to areas most contributing to the UHI effects. Zip code-based area analysis further contextualized these findings, offering an urban context-based perspective on emission distribution and informing potential urban energy policies for mitigating UHI effects.

Chowdhury, Shovan [ORNL]↗
DOE OSTI2017

Assessing the Validity of the Simplified Potential Energy Clock Model for Modeling Glass-Ceramics

Glass-ceramic seals may be the future of hermetic connectors at Sandia National Laboratories. They have been shown capable of surviving higher temperatures and pressures than amorphous glass seals. More advanced finite-element material models are required to enable model-based design and provide evidence that the hermetic connectors can meet design requirements. Glass-ceramics are composite materials with both crystalline and amorphous phases. The latter gives rise to (non-linearly) viscoelastic behavior. Given their complex microstructures, glass-ceramics may be thermorheologically complex, a behavior outside the scope of currently implemented constitutive models at Sandia. However, it was desired to assess if the Simplified Potential Energy Clock (SPEC) model is capable of capturing the material response. Available data for SL 16.8 glass-ceramic was used to calibrate the SPEC model. Model accuracy was assessed by comparing model predictions with shear moduli temperature dependence and high temperature 3-point bend creep data. It is shown that the model can predict the temperature dependence of the shear moduli and 3- point bend creep data. Analysis of the results is presented. Suggestions for future experiments and model development are presented. Though further calibration is likely necessary, SPEC has been shown capable of modeling glass-ceramic behavior in the glass transition region but requires further analysis below the transition region.

36 MATERIALS SCIENCE↗
DOE OSTI2017

The impact of shale gas on the cost and feasibility of meeting climate targets—A global energy system model analysis and an exploration of uncertainties

There exists considerable uncertainty over both shale and conventional gas resource availability and extraction costs, as well as the fugitive methane emissions associated with shale gas extraction and its possible role in mitigating climate change. This study uses a multi-region energy system model, TIAM (TIMES integrated assessment model), to consider the impact of a range of conventional and shale gas cost and availability assessments on mitigation scenarios aimed at achieving a limit to global warming of below 2 °C in 2100, with a 50% likelihood. When adding shale gas to the global energy mix, the reduction to the global energy system cost is relatively small (up to 0.4%), and the mitigation cost increases by 1%–3% under all cost assumptions. The impact of a “dash for shale gas”, of unavailability of carbon capture and storage, of increased barriers to investment in low carbon technologies, and of higher than expected leakage rates, are also considered; and are each found to have the potential to increase the cost and reduce feasibility of meeting global temperature goals. Finally, we conclude that the extraction of shale gas is not likely to significantly reduce the effort required to mitigate climate change under globally coordinated action, but could increase required mitigation effort if not handled sufficiently carefully.

energy economics↗
DOE OSTI2025

Incident Energy Systems Model: User Guide and Examples

U.S. Forest Service (USFS) wildfire base camps use portable power for electrical needs, including yurts and trailers from which logistics staff work during the incident. These yurts and trailers are conventionally powered by portable diesel generators. Hybrid portable power systems consisting of a combination of solar photovoltaics (PV), battery energy storage systems (BESS), and/or backup diesel generators have been used in recent years and were piloted by the National Technology and Development Program (NTDP) on incidents in fall 2024 as part of NTDP's Portable Power Project. As part of that project, this work included the development of two Excel-based tools and two reports explaining the tools. The first tool, the Incident Energy Systems Model, is an Excel-based tool that models the power output of hybrid portable power systems powering yurts and/or trailers at fire camps over a typical day.

14 SOLAR ENERGY↗
NASA NTRS1976

Statistical mechanics of light elements at high pressure. IV - A model free energy for the metallic phase

A large quantity of data on the thermodynamic properties of hydrogen-helium metallic liquids have been obtained in extended computer calculations in which a Monte Carlo code essentially identical to that described by Hubbard (1972) was used. A model free energy for metallic hydrogen with a relatively small mass fraction of helium is discussed, taking into account the definition of variables, a procedure for choosing the free energy, values for the fitting parameters, and the evaluation of the entropy constants. Possibilities concerning a use of the obtained data in studies of the interiors of the outer planets are briefly considered.

Dewitt, H. E.↗
DOE OSTI2023

Development of a dynamical model and energy analysis for wheel loader

The objective of this paper is to develop a fully integrated model for the wheel loader, including the subsystem dynamics of the engine, drivetrain, working circuit, steering circuit, and vehicle. It leads to a high-order strongly nonlinear system, and all state variables are coupled together to form a Multi-Input and Multi-Output (MIMO) system. A control architecture is proposed to decouple the MIMO system into several Single-Input and Single-Output (SISO) systems. Here, a tracking problem has been formulated to validate this fully integrated model with the field test data. The accuracy of the model is verified by the 2.3% difference between the measured and simulated fuel consumption. Meanwhile, an energy distribution analysis is conducted to reveal the energy consumption and energy loss of each portion of the wheel loader. Such a model can be used to plan the working pattern, guide the driving habits of human operators, or refine the underlying architecture, leading to the ultimate goal of reducing total fuel consumption and improving productivity.

42 ENGINEERING↗