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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Reanalyses and Essential Climate Variables

Reanalyses are a potentially powerful climate data collection driven by observations but also subjected to model bias. Additionally, reanalyses can produce and use essential climate variables in a consistent method. For example, snow cover and soil moisture (among other variables) will eventually be assimilated into the reanalyses, but also provide crucial validation data. Sea surface temperature can be prescribed or assimilated in a coupled reanalysis. The strength of reanalysis lies in the ancillary data that is produced from the modeling components but not routinely observed thereby providing more complete Earth system information. The weakness in this concept is that the model derived data can be affected by model bias and may also change relative to the available observing system. Here, we will review the status of existing reanalyses and the ECVs being considered for the workshop. Purpose of Michael Bosilovich's contribution to the workshop: Michael Bosilovich will represent US reanalysis community in this international discussion of Essential Climate Variables (ECVs) and the relative nature of reanalyses to ECVs.

Bosilovich, Michael↗
NASA NTRS2020

GEOS S2S Version 3: The New NASA/GMAO High Resolution Seasonal Prediction System

The NASA/Goddard Global Modeling and Assimilation Office (GMAO) released Version 2 of the Subseasonal to Seasonal (GEOS-S2S) forecast system in the fall of 2017, and it has been producing near-real time subseasonal to seasonal forecasts and a weakly coupled atmosphere-ocean data assimilation record since then. A new version of the coupled modeling and analysis system (Version 3) was released by the GMAO at the end of 2019. The new version runs at higher oceanic resolution than the previous (approximately 1/2 degree for the atmosphere, 1/4 degree for the ocean), and includes interactive earth system model components not typically present in seasonal prediction systems (two moment cloud microphysics for aerosol indirect effect and an interactive aerosol model). The weakly coupled atmosphere-ocean data assimilation system now includes assimilation of sea surface salinity, that has been shown to result in improved ocean mixed layer simulation and ENSO prediction skill.

Molod, Andrea↗
DOE OSTI2022

Stand-Alone and Hybrid Electric Thermal Energy Storage in the System Advisor Model

This project developed stand-alone electric-thermal energy storage (ETES), stand-alone pumped thermal energy storage (PTES), and hybrid molten-salt power tower (MSPT)-ETES performance and dispatch optimization techno-economic models. The models are available to the public through the System Advisor Model (SAM) software, scripting, and as open-source code. We compared results of the dispatch model to PLEXOS dispatch of a similar generator using the same initial grid pricing signal and found our dispatch model performed well, but closer agreement between the models was limited by the inherent differences between price-taker and unit commitment models. Nevertheless, the price-taker models developed in this project are useful to analyze proposed ETES and PTES technologies because they provide more detailed system and component models, solve several orders of magnitude faster, and are available as free open-source software. The model results represent the most optimistic returns considering grid arbitrage from the input electricity pricing, so the financial results can be applied as a feasibility stage-gate. We also submitted a journal draft paper that describes the ETES dispatch model methodology and demonstrates model functionality. An accepted journal article will serve as peer-reviewed documentation for the models, along with the open-source code, SAM help-menu content, and eventually this final project report.

14 SOLAR ENERGY↗
NASA NTRS1991

Propulsion stability codes for liquid propellant propulsion systems developed for use on a PC computer

Research into component modeling and system synthesis leading to the analysis of the major types of propulsion system instabilities and the characterization of various components characteristics are presented. Last year, several programs designed to run on a PC were developed for Marshall Space Flight Center. These codes covered the low, intermediate, and high frequency modes of oscillation of a liquid rocket propulsion system. No graphics were built into these programs and only simple piping layouts were supported. This year's effort was to add run time graphics to the low and intermediate frequency codes, allow new types of piping elements (accumulators, pumps, and split pipes) in the low frequency code, and develop a new code for the PC to generate Nyquist plots.

Doane, George B., III↗
NASA NTRS1991

Correlations between the far-infrared, radio, and blue luminosities of spiral galaxies

FIR-radio luminosity correlations are presently derived for two statistically complete samples spanning a wide luminosity range. While observed correlations are tight, they are not linear; the observed scattering is mostly intrinsic. An empirical correction to the radio luminosities, based on observed blue luminosities, makes the corrected FIR-radio correlation linear and eliminates most of the residual variance. A two-component model that is consistent with the improved correlation is proposed for the heating luminosity within galaxies. The first, radio-loud component contains young massive stars that heat the dust, while contributing to the cool cirrus dust-heating interstellar radiation field. The second, radio-quiet component is made up of less massive older stars.

Condon, J. J.↗
NASA NTRS1992

A microwave scattering model for layered vegetation

A microwave scattering model was developed for layered vegetation based on an iterative solution of the radiative transfer equation up to the second order to account for multiple scattering within the canopy and between the ground and the canopy. The model is designed to operate over a wide frequency range for both deciduous and coniferous forest and to account for the branch size distribution, leaf orientation distribution, and branch orientation distribution for each size. The canopy is modeled as a two-layered medium above a rough interface. The upper layer is the crown containing leaves, stems, and branches. The lower layer is the trunk region modeled as randomly positioned cylinders with a preferred orientation distribution above an irregular soil surface. Comparisons of this model with measurements from deciduous and coniferous forests show good agreements at several frequencies for both like and cross polarizations. Major features of the model needed to realize the agreement include allowance for: (1) branch size distribution, (2) second-order effects, and (3) tree component models valid over a wide range of frequencies.

Karam, Mostafa A.↗
NASA NTRS2022

Exploration of an Adaptive Routine for Battery Modeling

The purpose of this document is to explore the use of adaptive routines in battery modeling. The adaptive routines consist of real-time state estimators combined with battery parameter model components that are adjusted in real-time as battery data becomes available. Several aspects are explored. It is shown that model parameter identification is possible for simple battery models using available input/output data measurements. The online system identification used is recursive least squares. Model identification may be combined with a state observer such as the extended Kalman filter or the unscented Kalman filter to form an adaptive model combined with state estimation. However, such a combination is found to be problematic due to uncertainty, observability and stability issues. This paper is organized as follows. Section 1 introduces adaptive routines and possible roles they play in battery modeling. In Section 2 real-time parameter identification is described with results based on battery data. Section 3 reviews various state estimators and results using a simple battery model. In Section 4 parameter identification and state estimation are combined to form an adaptive routine. Finally, in Section 5 conclusions are drawn and future work is suggested.

Adaptive↗
NASA NTRS1992

Single-phase power distribution system power flow and fault analysis

Alternative methods for power flow and fault analysis of single-phase distribution systems are presented. The algorithms for both power flow and fault analysis utilize a generalized approach to network modeling. The generalized admittance matrix, formed using elements of linear graph theory, is an accurate network model for all possible single-phase network configurations. Unlike the standard nodal admittance matrix formulation algorithms, the generalized approach uses generalized component models for the transmission line and transformer. The standard assumption of a common node voltage reference point is not required to construct the generalized admittance matrix. Therefore, truly accurate simulation results can be obtained for networks that cannot be modeled using traditional techniques.

Halpin, S. M.↗
NASA NTRS2016

Numerical Modeling of Pressurization of Cryogenic Propellant Tank for Integrated Vehicle Fluid System

This paper presents a numerical model of pressurization of a cryogenic propellant tank for the Integrated Vehicle Fluid (IVF) system using the Generalized Fluid System Simulation Program (GFSSP). The IVF propulsion system, being developed by United Launch Alliance, uses boiloff propellants to drive thrusters for the reaction control system as well as to run internal combustion engines to develop power and drive compressors to pressurize propellant tanks. NASA Marshall Space Flight Center (MSFC) has been running tests to verify the functioning of the IVF system using a flight tank. GFSSP, a finite volume based flow network analysis software developed at MSFC, has been used to develop an integrated model of the tank and the pressurization system. This paper presents an iterative algorithm for converging the interface boundary conditions between different component models of a large system model. The model results have been compared with test data.

Majumdar, Alok K.↗
NASA NTRS1994

On the use of radiative surface temperature to estimate sensible heat flux over sparse shrubs in Nevada

The accurate partitioning of available energy into sensible and latent heat flux is crucial to the understanding of surface atmosphere interactions. This issue is more complicated in arid and semi arid regions where the relative contribution to surface fluxes from the soil and vegetation may vary significantly throughout the day and throughout the season. A three component model to estimate sensible heat flux over heterogeneous surfaces is presented. The surface was represented with two adjacent compartments. The first compartment is made up of two components, shrubs and shaded soil, the second of open 'illuminated' soil. Data collected at two different sites in Nevada (U.S.) during the Summers of 1991 and 1992 were used to evaluate model performance. The results show that the present model is sufficiently general to yield satisfactory results for both sites.

Chehbouni, A.↗
DOE OSTI2021

An AI-Enabled MODEX Framework for Improving Predictability of Subsurface Water Storage across Local and Continental Scales

Focal Area: (2) Predictive modeling through the use of AI techniques and AI-derived model components. (3) Insight gleaned from complex data using AI, big data analytics, and other advanced methods. We propose an AI-enabled model-experiment (MODEX) framework to improve the predictability of subsurface water storage (SWS) from local to conus scales in a changing environment by taking advantage of DOE’s observation and simulation capabilities, as well as to inform the model and the observation development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

High-Accuracy Module Emulators from Physically-Constrained AI Algorithms

Focal Area(s): How do we use AI tools to integrate observations, simulated data and physical and chemical fundamentals (Focal Area 3) into model components (Focal Area 2) that have high accuracy and stability and low computational burden to improve Earth System Predictability? Science Challenge: Earth system modeling of the hydrological cycle involves compute-intensive modules representing complex chemical and physical process. Recently, AI tools that are far less compute intensive have been developed that emulate these modules, but many of these efforts are not yet sufficiently accurate or even stable. We know a lot about the physics and chemistry of earth system processes. The Science Challenge is developing AI tools that not only incorporate observations and simulated data, but also incorporate the physics and chemistry of the process, while still maintaining the compute efficiency.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

Multicomponent analysis of total COS-B gamma-ray data at intermediate lattitudes

The final COS-B database was used to study the gamma ray emission in the latitude range 10 deg /b/ 20 deg in terms of a four component model. The emissivity spectrum of the local interstellar medium is derived and compared with that found in previous studies. The intensity-Compton component is determined from the fitting procedure and is in good agreement with theoretical values.

Strong, A. W.↗
NASA NTRS1991

GRIS observations of positron annihilation radiation from the Galactic center

In the present Gamma-Ray Imaging Spectrometer (GRIS) observations, the 511 keV line has been spectrally resolved and the Galactic plane and center components have been independently measured. These data, in combination with those from other narrow-field observations in the 1980s, support the two-component model of the positron annihilation source. A strong hard-X-ray continuum was detected in the Galactic plane observation; this 'diffuse' continuum component solves the mystery as to why wide-field instruments have detected such high continuum emission from the Galactic center, in virtue of its source contributions.

Gehrels, N.↗
NASA NTRS2003

Rapid Prototyping of an Aircraft Model in an Object-Oriented Simulation

A team was created to participate in the Mars Scout Opportunity. Trade studies determined that an aircraft provided the best opportunity to complete the science objectives of the team. A high fidelity six degree of freedom flight simulation was required to provide credible evidence that the aircraft design fulfilled mission objectives and to support the aircraft design process by providing performance evaluations. The team created the simulation using the Langley Standard Real-Time Simulation in C++ (LaSRS++) application framework. A rapid prototyping approach was necessary because the team had only three months to both develop the aircraft simulation model and evaluate aircraft performance as the design and mission parameters matured. The design of LaSRS++ enabled rapid-prototyping in several ways. First, the framework allowed component models to be designed, implemented, unit-tested, and integrated quickly. Next, the framework provides a highly reusable infrastructure that allowed developers to maximize code reuse while concentrating on aircraft and mission specific features. Finally, the framework reduces risk by providing reusable components that allow developers to build a quality product with a compressed testing cycle that relies heavily on unit testing of new components.

Kenney, P. Sean↗
DOE OSTI2025

Terra-Populus v0.1: A Python Library for LandScan High-Definition Population Analysis and Modeling

The terra-populus library is designed for use by the LandScan HD technical team, offering a streamlined set of tools for generating and updating LandScan HD datasets from foundational building-level data, referred to as 'molecules,' provided by the building-level attribution team. This document serves as the primary technical documentation for terra-populus. Version 0.1 of the library includes the core modeling components necessary for LandScan HD production. It enables the generation of the LandScan HD Baseline dataset as well as corresponding confidence measures for the occupancy rates used. Parameters have been included for incorporating damaged building indicators and changes in population, to faciliate the creation of rapid updates for LandScan HD. Future iterations of terra-populus will introduce tools for creating a confidence index, and quantifying and propagating uncertainty, facilitating the creation of probabilistic LandScan HD outputs. This report provides an overview of the tools available in the library and the corresponding code implementations. One of the key advancements implemented in terra-populus is a redefinition of the atomic modeling unit for LandScan HD. Traditionally, the LandScan HD vector analytical framework has generated population estimates at the building sub-component (molecule) level. However, terra-populus adopts a building-level modeling approach. This shift is an operational decision aimed at aligning LandScan HD outputs with confidence measures, which are computed and validated at the building level (confidence measures are not included in this version of terra-populus, aside from those associated with the occupancy rates). Additional advancements to the LandScan HD modeling, as implemented by terra-populus, include a minimum population value parameter and an auto assignment of building floor counts. The population minimum value was implemented to prevent buildings and subsequent LandScan HD pixels that contained small values that may not rasterize in production. An 'auto' value has been included as a method for dealing with buildings lacking floor count information, where it is the average floor count of all other buildings with a residential building use type tag. The logic behind this is to remain consistent with the current logic employed for dealing with building use type null instances, where a null use type is defaulted to residential since it is the most common building type. The auto logic is intended to apply the most common building floor count of the most common type of buildings. The tools provided in terra-populus represent a significant step forward in improving the efficiency, reproducibility, and transparency of the LandScan HD modeling process. As the library evolves, it will continue to serve as a foundational resource for high-resolution population modeling.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2026

Data from: "Towards CONUS-Wide ML-Augmented Conceptually-Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics"

This data package was generated to support the manuscript “Towards CONUS-Wide Machine Learning-Augmented Conceptually Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics.” It provides input files, model outputs, plotting data, scripts, notebooks, and documentation used to develop, evaluate, and reproduce Mass-Conserving Perceptron (MCP)-based hydrologic modeling experiments across 513 selected Catchment Attributes and Meteorology for Large-sample Studies in the United States (CAMELS-US) basins. The files are organized by modeling component and analysis purpose, including rainfall–runoff experiments, snow module experiments, coupled hydrologic-snow experiments, Long Short-Term Memory (LSTM) benchmark results, model skill metrics, initialization and epoch records, cell-state normalization files, Akaike Information Criterion (AIC)-based model comparison files, and data used to generate manuscript figures. Tabular files can be opened using standard spreadsheet software or Python/R data-analysis tools. Python scripts, Jupyter notebooks, and selected MATLAB scripts are included for model execution, postprocessing, plotting, and statistical analysis. Quality assurance and quality control were conducted through the source-data selection and modeling workflow. Meteorological forcing, streamflow, and static catchment attributes were derived from the CAMELS-US dataset, and snow water equivalent data were derived from the University of Arizona (UA) Snow Water Equivalent dataset. Selected basins and time periods were screened during the associated research workflow to avoid missing observations or poor-quality cases. Static geospatial features were processed primarily using Quantum Geographic Information System (QGIS) and Geospatial Data Abstraction Library (GDAL) workflows. Additional details are provided in the associated manuscript and documentation.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗