Search NASA⌕ Search

SEARCH · Search NASA

Results for “Energy Modeling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

An Online Tool for Preliminary Design and Techno-Economic Analysis of District Geothermal Heating and Cooling Systems

District geothermal heating and cooling systems (DGHCS) have significant benefits for reducing energy consumption as well as building- and grid-level peak electric demand. Currently, no publicly available tools are available to effectively design and conduct techno-economic analysis of DGHCS. GeoWISE was originally developed for preliminary design and techno-economic analysis of geothermal heating and cooling systems in an individual commercial or residential building. This paper introduces recent upgrades of GeoWISE that allow users to design and conduct techno-economic analysis of DGHCS. Several new features are implemented in GeoWISE to allow selection and specification of multiple new or existing buildings. A database of information for over 125 million existing U.S. buildings was used in GeoWISE that allows users easily locate existing buildings of interest based on street addresses, and optionally edit information of the buildings (e.g., footprint, vintage, principal functions, number of floors, window-to-wall ratio). Unique energy simulation models of the selected buildings are then automatically created using the Automatic Building Energy Modeling (AutoBEM) and EnergyPlus simulations are performed to predict thermal loads of the buildings. A simplified DGHCS is then designed and simulated to predict its energy use. A central borehole heat exchanger (BHE) of the DGHCS is sized using the RowWise algorithm of GHEDesigner to meet the thermal loads within user-specified land areas for installing BHE. The upgraded GeoWISE reports the needed capacity of heating and cooling equipment in each building, design of the central BHE, energy consumption reduction, and energy cost saving resulting from using DGHCS compared with conventional HVAC systems. A case study is showcased using the upgraded GeoWISE to design and conduct techno-economic analysis of a simplified DGHCS.

Prem Anand Jayaprabha, Jyothis Anand [ORNL] (ORCID↗
NASA NTRS1991

A computational model for the analysis of diffusive binary alloy solid/liquid phase change energy transport

A model is presented for the prediction of solid/liquid, binary alloy, phase change energy transport. The model incorporates only one-dimensional, diffusive transport of both energy and species but is not inherently limited in any way to such a restriction. The model incorporates a previously developed algorithm for single constituent phase change energy transport and is applied to the energy transport as well as the species transport aspects of the problem. The model is applied to four example cooling problems and is shown to perform exceedingly well from an algorithmic point of view.

Schneider, G. E.↗
NASA NTRS1993

The role of atmospheric heat transport in the seasonal carbon dioxide cycle

We have carried out numerical experiments with a general circulations model (GCM) and energy balance model of the martian atmosphere to define the importance of heat transported to the polar regions in determining the amount of CO2 condensed on the surface during the fall and winter seasons and the amount sublimated during the spring and summer seasons. In so doing, we performed both sensitivity experiments, in which the dust opacity was varied over the full range of its observed values, and annual simulations, in which the dust opacity varied continuously with seasonal data, in accord with measurements taken at the Viking landers. Dust opacity represents the key variable for determining the contribution of atmospheric heat advection to the energy budget in the polar regions. The amount of heat advected to the winter polar regions increases monotonically as the dust opacity at low and middle latitudes increases. However, the increase is sharpest between optical depths of 0 and 1 tends to level off at still higher optical depths. Heat advection is more important at times of CO2 condensation than CO2 sublimation, since the temperature gradients are much steeper in the winter hemisphere than in the summer hemisphere. Because dust opacity is much higher during northern winter than during southern winter, atmospheric heat advection reduces the amount of CO2 that condenses in the north by a much larger factor than it does in the south.

Pollack, James B.↗
NASA NTRS2019

Modeling Mg II During Solar Flares. II. Nonequilibrium Effects

To extract the information that the Mg II NUV spectra (observed by the Interface Region Imaging Spectrograph) carry about the chromosphere during solar flares, and to validate models of energy transport via model–data comparison, forward modeling is required. The assumption of statistical equilibrium (SE) is typically used to obtain the atomic level populations from snapshots of flare atmospheres, due to computational necessity. However, it is possible that relying on SE could lead to spurious results. We compare solving the atomic level populations via SE versus a non-equilibrium (NEQ) time-dependent approach. This was achieved using flare simulations from RADYN alongside the minority species version MS_RADYN from which the time-dependent Mg II atomic level populations and radiation transfer were computed in complete frequency redistribution. The impacts on the emergent profiles, light curves, line ratios, and formation heights are discussed. In summary we note that NEQ effects during flares are typically important only in the initial stages and for a short period following the cessation of the energy injection. An analysis of the timescales of ionization equilibrium reveals that for most of the duration of the flare, when the temperatures and densities are sufficiently enhanced, the relaxation timescales are short (τrelax < 0.1 s), so that the equilibrium solution is an adequate approximation. These effects vary with the size of the flare, however. In weaker flares, effects can be more pronounced. We recommend that NEQ effects be considered when possible but that SE is sufficient at most stages of the flare.

Kerr, Graham S.↗
DOE OSTI2024

Machine-Learning-Based Mapping and Modeling of Solar Energy with Ultra-High Spatiotemporal Granularity

Despite the rapid growth of solar energy, we still lack a dynamic, high-fidelity database that tracks the spatiotemporal variations of solar PVs and their associated infrastructures across different places at a spatially resolved scale. The absence of such data presents a barrier to various applications such as solar PV growth projection, solar energy integration, solar incentive design, and climate risk assessment. In this project, we aim to bridge this gap by developing AI-based algorithms to extract granular information about solar PV installations and their associated infrastructures (i.e., distribution grids) from widely available unstructured data like remote sensing images and street views. As a result, we have built the Solar Energy Atlas, a fine-grained, large-scale geospatial overlay of distributed solar PVs and distribution grids. On top of it, we have advanced the understanding of solar adoption and distribution grid vulnerability to climate-induced extremes. Our major contributions can be summarized as follow: (1) By developing new AI algorithms, we have built the most comprehensive solar PV spatiotemporal database covering the entire US. This is the first time we obtained the exact GPS locations, size, subtype, and installation year information for rooftop solar PVs across the US. This database can be used for solar PV growth projection, solar energy integration, solar energy policy analysis and design, and spatially-resolved climate risk assessment. (2) Leveraging this database, we have uncovered the socioeconomic driving factors that are correlated with earlier onset of solar adoption and higher saturated adoption levels. We have identified the heterogeneity in the effects of different types of financial incentives on solar adoption and provided implications for tailoring incentive design based on local income levels to promote equitable solar adoption. (3) We have developed a distribution grid GIS mapping algorithm which can obtain granular geospatial and topology information about distribution grids using multi-modal open data, reducing the dependency on hard-to-obtain smart meter data of conventional approaches. It shows effectiveness in both the U.S. and Sub-Saharan Africa. Using this algorithm, we have uncovered the non-uniform vulnerability of distribution grids to wildfires in California in the aspects of undergrounding protection and Distributed Energy Resources (DER) preparedness. This has provided important implications for improving the affordability and equity of grid adaptation approaches. (3) We have made our produced database publicly available and provided user-friendly interface to enable various stakeholders and the general public to interact with the data. We have also integrated the produced data into the Data Commons platform to enable the public to access the data and correlate it with other location-specific characteristics simply using natural language as queries. The impact of our project is three-fold: (1) New algorithms for mapping solar PVs and distribution grids across space and time, which are open source to facilitate researchers and industry; (2) New databases of solar PVs and distribution grids that have been made publicly available for engineering, social, and policy applications; (3) New understandings and actionable insights on the potential approaches to promoting solar adoption and reducing energy infrastructure vulnerabilities. In this report, we start by discussing the project background and motivation (section 5), followed by the overview of project objectives (section 6). Results and discussion for each task are presented in section 7. Significant accomplishments are summarized in section 8. This report will be concluded by discussing the paths forwards (section 9), products (section 10), and team roles (section 11).

14 SOLAR ENERGY↗
DOE OSTI2024

Optimal Electrification Using Renewable Energies: Microgrid Installation Model with Combined Mixture k-Means Clustering Algorithm, Mixed Integer Linear Programming, and Onsset Method

Optimal planning and design of microgrids are priorities in the electrification of off-grid areas. Indeed, in one of the Sustainable Development Goals (SDG 7), the UN recommends universal access to electricity for all at the lowest cost. Several optimization methods with different strategies have been proposed in the literature as ways to achieve this goal. This paper proposes a microgrid installation and planning model based on a combination of several techniques. The programming language Python 3.10 was used in conjunction with machine learning techniques such as unsupervised learning based on K-means clustering and deterministic optimization methods based on mixed linear programming. These methods were complemented by the open-source spatial method for optimal electrification planning: onsset. Four levels of study were carried out. The first level consisted of simulating the model obtained with a cluster, which is considered based on the elbow and k-means clustering method as a case study. The second level involved sizing the microgrid with a capacity of 40 kW and optimizing all the resources available on site. The example of the different resources in the Togo case was considered. At the third level, the work consisted of proposing an optimal connection model for the microgrid based on voltage stability constraints and considering, above all, the capacity limit of the source substation. Finally, the fourth level involved a planning study of electrification strategies based mainly on microgrids according to the study scenario. The results of the first level of study enabled us to obtain an optimal location for the centroid of the cluster under consideration, according to the different load positions of this cluster. Then, the results of the second level of study were used to highlight the optimal resources obtained and proposed by the optimization model formulated based on the various technology costs, such as investment, maintenance, and operating costs, which were based on the technical limits of the various technologies. In these results, solar systems account for 80% of the maximum load considered, compared to 7.5% for wind systems and 12.5% for battery systems. Next, an optimal microgrid connection model was proposed based on the constraints of a voltage stability limit estimated to be 10% of the maximum voltage drop. The results obtained for the third level of study enabled us to present selective results for load nodes in relation to the source station node. Finally, the last results made it possible to plan electrification using different network technologies and systems in the short and long term. The case study of Togo was taken into account. The various results obtained from the different techniques provide the necessary leads for a feasibility study for optimal electrification of off-grid areas using microgrid systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1972

Liquid rocket performance computer model with distributed energy release

Development of a computer program for analyzing the effects of bipropellant spray combustion processes on liquid rocket performance is described and discussed. The distributed energy release (DER) computer program was designed to become part of the JANNAF liquid rocket performance evaluation methodology and to account for performance losses associated with the propellant combustion processes, e.g., incomplete spray gasification, imperfect mixing between sprays and their reacting vapors, residual mixture ratio striations in the flow, and two-phase flow effects. The DER computer program begins by initializing the combustion field at the injection end of a conventional liquid rocket engine, based on injector and chamber design detail, and on propellant and combustion gas properties. It analyzes bipropellant combustion, proceeding stepwise down the chamber from those initial conditions through the nozzle throat.

Combs, L. P.↗
NASA NTRS1974

Liquid rocket combustion computer model with distributed energy release. DER computer program documentation and user's guide, volume 1

A computer program for analyzing rocket engine performance was developed. The program is concerned with the formation, distribution, flow, and combustion of liquid sprays and combustion product gases in conventional rocket combustion chambers. The capabilities of the program to determine the combustion characteristics of the rocket engine are described. Sample data code sheets show the correct sequence and formats for variable values and include notes concerning options to bypass the input of certain data. A seperate list defines the variables and indicates their required dimensions.

Combs, L. P.↗
NASA NTRS1975

A dynamic model for the time evolution of the modulated cosmic ray spectrum

A recently developed model predicts an energy dependent phase lag in the modulated cosmic ray density U(t) given by U(t) approximately equal to US (t - tau) where US is the solution to the Fokker-Planck equation under time independent conditions and tau is the average time spent by particles inside the modulating region. The delay times tau are functions of modulating parameters R (the radius of the modulating cavity), V (the solar wind velocity), and K (the effective average diffusion-coefficient which is a function of energy). This model is applied to predict the time evolution of the modulated cosmic ray proton spectrum over a simulated solar cycle. A modulation produced mostly by varying R over the solar cycle is less consistent with the observations.

Ogallagher, J. J.↗