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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Model-based estimation of wind fields over the ocean from wind scatterometer measurements. I - Development of the wind field model. II - Model parameter estimation

Techniques for the determination of near-surface mesoscale ocean wind fields on the basis of satellite scatterometer data are developed and demonstrated. The derivation of normal-boundary and parameterized-boundary-condition (PBC) wind-field models is outlined, and results from a simulation performed to estimate the model errors are presented in tables. It is shown that the PBC model provides accurate results while minimizing the number of unknowns. After a review of the principles of scatterometry and an analysis of scatterometer measurement noise, an objective function for the measurement parameters is developed and optimized on the basis of gradient search with initial values computed from pointwise wind estimates. The model is then applied to data from a simulation of the NASA Scatterometer (Li et al., 1984), and the results are presented in extensive graphs. The feasibility of model-based wind-field estimation and the appropriateness of the PBC model are demonstrated.

Long, David G.↗
NASA NTRS1987

A numerical modeling study of a Montana thunderstorm. I - Model results versus observations involving nonelectrical aspects. II - Model results versus observations involving electrical aspects

Model results and the observed cloud behavior are examined in terms of nonelectrical and electrical aspects of a thunderstorm. The characteristics of the two-dimensional, time-dependent atmospheric electricity model used to simulate the cloud observations of July 19, 1981 in Miles City, Montana are described. The interactions of the dynamics and microphysics of the cloud with the charge separation mechanisms are analyzed. It is observed that the model accurately represents many of the observed characteristics of the cloud; however, the cloud base height, maximum liquid water content, and the time from first formation of precipitation until it reaches the ground are not accurately modeled. It is found that the model adequately represents the electrical field structure of the cloud and the electrical field strengths.

Helsdon, John H., Jr.↗
NASA NTRS1954

Wind-Tunnel Investigation of the Effects on the Aerodynamic Characteristics of Modifications to a Model of a Bomb Mounted on a Wing-Fuselage Model and to a Model of the Bomb Alone

An investigation was conducted in the Langley high-speed 7- by 10-foot tunnel to determine effects of modifications to a bomb model (particularly with regard to drag) when mounted on a wing-fuselage model and tested at Mach numbers from 0.70 to 1.10. In addition, the static longitudinal stability characteristics of several configurations of a larger scale model of the bomb alone were obtained over a Mach number range from 0.50 to 0.95. The results obtained for the wing-fuselage-bomb model indicate that large reductions in installation drag were obtained for the wing-fuselage-bomb model when the flat nose of the basic bomb was replaced by rounded or pointed noses of various calibers. Shortening the mounting pylon gave further decreases in the installation drag. The tests of the bomb alone indicated that only the flat-nose configurations were stable over the greater part of the Mach number range. Nose-shape modifications which improved the drag also caused the bombs to become unstable at low angles of attack. The stability of the low-drag bomb configurations could be improved by lengthening the cylindrical portion of the body behind the center of gravity.

King, Thomas J., Jr.↗
NASA NTRS1984

Inversion of vegetation canopy reflectance models for estimating agronomic variables. III - Estimation using only canopy reflectance data as illustrated by the suits model. IV - Total inversion of the SAIL model

The possibility of estimating agronomic and spectral parameters for a vegetation canopy from the canopy reflectance (CR) data in the infrared region is investigated for a set of solar/view directions. It is shown that such an estimation is possible, in principle, for the Suits (1972) model for a homogeneous canopy. The technique is then applied to a more complex model, the SAIL (scattering by arbitrarily inclined leaves) model which explicitly includes the leaf angle distribution in the computation of the canopy reflectance. It is concluded that, given the expected accuracy of CR measurements and the accuracy of the SAIL model in representing CR in the infrared region, the agronomic parameters, leaf area index, and leaf angle distribution can be estimated fairly accurately using ancillary data on spectral parameters.

Goel, N. S.↗
NASA NTRS1984

An Eulerian transport/transformation/removal model for SO2 and sulfate. I - Model development. II - Model calculation of SO(x) transport in the eastern United States

A three-dimensional, time dependent Eulerian atmospheric SO2 and sulfate transport/transformation/removal model is described and applied to the eastern U.S. The model was developed in anticipation of increased input to the atmospheric sulfur content by coal-burning power plants in the near future and is intended as an aid in identifying sources of SO2. The Eulerian transport model incorporates functions for chemical transformations, dry deposition, spatial topographical variations, spatial and temporal variations of mixing layer heights, the wind field, eddy diffusivities, deposition velocities, and temperature and water concentration profiles. Attention is also given to the SO2 photochemical oxidation mechanism and rates. Results from a 72-hr simulation of SO(x) transport over the eastern U.S., using actual 1974 meteorological data, illustrate the model's capability to depict interactions between emissions, transport, chemistry and removal. Concentration distributions are demonstrated to have significant spatial and temporal variations.

Carmichael, G. R.↗
NASA NTRS1985

A systems analysis of the erythropoietic responses to weightlessness. Volume 2: Description of the model of erythropoiesis regulation. Part A: Model for regulation of erythropoiesis. Part B: Detailed description of the model for regulation of erythropoiesis

A mathematical model of the erythropoiesis on total red blood cell mass is presented. The loss of red cell mass has been a consistent finding during space flight. Computer simulation of this phenomenon required a model that could account for oxygen transport, red cell production, and red cell destruction. The elements incorporated into the feedback regulation loop of the model are based on the accepted concept that erythrocyte production is governed by the balance between oxygen supply and demand in the body. The mechanisms and pathways of the control circuit include oxygenation of hemoglobin and oxygenation of tissues by blood transport and diffusional processes. Other features of the model include a variable oxygen-hemoglobin affinity, and time delays which represent time for erythropoietin (erythrocyte-stimulating hormone) distribution in plasma, and time for maturation of the erythrocytes in bone marrow.

Leonard, J. I.↗
NASA NTRS1991

Improved large perturbation propulsion models for control system design (1988-1989) and large perturbation models of high velocity propulsion systems (1989-1990) and reduced order propulsion models for control system design (1990-1991)

Methods for modeling high speed propulsion systems will be discussed. Included in this category are internal flow propulsion systems without rotating machinery, such as inlets, ramjets, and scramjets. Among the modeling topics discussed are modeling of linear isentropic flow, heat exchange, gasdynamics, lumped parameter systems, and infinite dimensional systems. Furthermore, a generalized overview of modeling high speed propulsion systems is presented in this collection of papers.

Hartley, Tom T.↗
NASA NTRS1975

Aerodynamic results of a separation test (CA20) conducted at the Boeing transonic wind tunnel using 0.030-scale models of the configuration 140A/B (modified) SSV orbiter (model no. 45-0) and the Boeing 747 carrier (model no. AX 1319 I-1), volume 1

A Rockwell built 0.030-scale 45-0 modified Space Shuttle Orbiter Configuration 14?A/B model and a Boeing built 0.030-scale 747 carrier model were tested to provide six component force and moment data for each vehicle in proximity to the other at a matrix of relative positions, attitudes and test conditions (angles of attack and sideslip were varied). Orbiter model support system tare effects were determined for corrections to obtain support-free aerodynamics. In addition to the balance force data, pressures were measured. Pressure orifices were located at the base of the Orbiter, on either side of the vertical blade strut, and at the mid-root chord on either side of the vertical tail. Strain gages were installed on the Boeing 747 vertical tail to indicate buffet onset. Photographs of aerodynamic configurations tested are shown.

Dziubala, T.↗
NASA NTRS1985

Description, validation, and modification of the Guyton model for space-flight applications. Part A. Guyton model of circulatory, fluid and electrolyte control. Part B. Modification of the Guyton model for circulatory, fluid and electrolyte control

The mathematical model that has been a cornerstone for the systems analysis of space-flight physiological studies is the Guyton model describing circulatory, fluid and electrolyte regulation. The model and the modifications that are made to permit simulation and analysis of the stress of weightlessness are described.

Leonard, J. I.↗
NASA NTRS1997

Physics and Process Modeling (PPM) and Other Propulsion R and T: Materials Processing, Characterization, and Modeling; Lifting Models - Volume 1

This CP contains the extended abstracts and presentation figures of 36 papers presented at the PPM and Other Propulsion R&T Conference. The focus of the research described in these presentations is on materials and structures technologies that are parts of the various projects within the NASA Aeronautics Propulsion Systems Research and Technology Base Program. These projects include Physics and Process Modeling; Smart, Green Engine; Fast, Quiet Engine; High Temperature Engine Materials Program; and Hybrid Hyperspeed Propulsion. Also presented were research results from the Rotorcraft Systems Program and work supported by the NASA Lewis Director's Discretionary Fund. Authors from NASA Lewis Research Center, industry, and universities conducted research in the following areas: material processing, material characterization, modeling, life, applied life models, design techniques, vibration control, mechanical components, and tribology. Key issues, research accomplishments, and future directions are summarized in this publication.

Source record↗
NASA NTRS1961

Aerodynamic Loads at Mach Numbers from 0.70 to 2.22 on an Airplane Model Having a Wing and Canard of Triangular Plan Form and Either Single or Twin Vertical Tails Supplement I-Tabulated Data for the Model with Single Vertical Tails: Tabulated Data for the Model with Single Vertical Tail - Supplement 1

Tabulated results of a wind-tunnel investigation of the aerodynamic loads on a canard airplane model with a single vertical tail are presented for Mach numbers from 0.70 to 2.22. The Reynolds number for the measurements was 2.9 x 10(exp 6) based on the wing mean aerodynamic chord. The results include local static pressure coefficients measured on the wing, body, and vertical tail for angles of attack from -4 deg to + 16 deg, angles of sideslip of 0 deg and 5.3 deg, vertical-tail settings of 0 deg and 5 deg, and nominal canard deflections of 0 deg and 10 deg. Also included are section force and moment coefficients obtained from integrations of the local pressures and model-component force and moment coefficients obtained from integrations of the section coefficients. Geometric details of the model and the locations of the pressure orifices are shown. An index to the data contained herein is presented and definitions of nomenclature are given.

Peterson, Victor L.↗
NASA NTRS2024

Crew State and Risk Model (CSRM) - Medication Impacts on Physiologic Models for Exploration Class EVA Predictive Modeling and Operations

EVA and Environmental Physiology Laboratory (EEPL) wanted to expand upon the previous CSRM Physiologic Map to visually demonstrate the impact of medications on various modeling inputs that map to the seven physiologic models. It is acknowledged various physiologic states present during EVA could impact drug pharmacokinetics (i.e. pressure changes, core body temperature), which could impact pharmacodynamics. However, that is outside the scope of this document. The medications below represent the authors’ assumption of what medications will be available and able to impact an Artemis EVA and do not include the full ISS formulary, a final Artemis medical kit, or additional personal medications for individual crewmember’s chronic medical conditions.

Emma Ives↗
DOE OSTI2026

A bespoke model of Arctic river basins based on hillslope delineation: Model Archive

This dataset is a model archive of the paper A bespoke model of Arctic river basins based on hillslope delineation (in prep), which introduces a watershed decomposition and parameterization method for large scale permafrost hydrology simulation. With this dataset, this study aims to address the research question: whether a computationally efficient hillslope-based modeling framework can reliably simulate discharge at Arctic river-basin scales. This dataset contains model input and output data for five modeling scenarios at a study site located in the Sagavanirktok River basin. The five modeling scenarios include three modeling cases under temperate conditions using full 3D, decomposed 3D, and decomposed 2D modeling strategies; and two modeling cases under actual Arctic conditions with permafrost using full 3D and decomposed 2D modeling strategies. Simulations were performed using the Advanced Terrestrial Simulator (ATS, v1.6 for three temperate scenarios and v1.5 for two Arctic scenarios), a physics-rich integrated surface–subsurface hydrologic model with cryo-hydrology features. For the three temperate models, simulations were conducted for the period of 10/01/1993 - 09/30/2002; and for the two Arctic models, simulations were conducted for the period of 01/01/1994 - 12/31/2002. To facilitate reproducibility of simulations, all datasets are organized hierarchically. The dataset contains: (1) Mesh files (.exo) for full 3D model, decomposed 3D models, and decomposed 2D models, located in huc/190604020802_gauge15906000/mesh/. Mesh files can be visualized through Paraview or read by Python. (2) Climate forcings (.h5) for full 3D model and decomposed 3D/2D models are located in huc/190604020802_gauge15906000/daymet_onePiece/, and huc/190604020802_gauge15906000/vp_pr_revised_daymet_1980_2006_with_wind/ separately. Accessible by Python. (3) Raw measured gage discharge (.csv) from USGS, located in huc/190604020802_gauge15906000/gaged_basin15906000_discharge_usgs/. Accessible by Python. (4) Delineated subdomain raster (.tif) and shape files (.shp), and the final parameterized results (.npy) for decomposed models, located in huc/190604020802_gauge15906000/data_preprocessed-meshing. Accessible by Python. (5) Temperate models are located in nonpermaf_huc190604020802_gauge15906000/, which includes three cases: decomposed 2D models (inside model_0*-hillslope_*), decomposed 3D models (inside model_1*-subcatchment_*), and full 3D model (inside model_2*-onepiece_*). Two step spin-up results (checkpoint_final.h5) are located in model_*1-*_spinup_steadystate and model_*2-*_spinup_cycle, separately, which are used to initialize real transient models. The input files (.xml) and output results (.dat) of the real transient models are located in model_*3-*_transient/. Especially, for two example hillslope models (ID=-11 and 11), additional h5py files are included in model_03-hillslope_transient/hillslope-11/, model_03-hillslope_transient/hillslope11, model_13-subcatchment_transient/subcatchment-11/, model_13-subcatchment_transient/subcatchment/11, respectively, which are used to plot the saturation figure (Figure 5) in the manuscript. Accessible by Python. (6) Arctic models are located in huc190604020802_gauge15906000/, which includes two cases: decomposed 2D models (inside model_04-hillslope_transient), and full 3D model (inside model_05-onepiece_transient_mannp1_ra). Three step spin-up results (checkpoint_final.h5) are located in model_01-column_freezeup/, model_02-column_spinup/, model_03-hillslope_spinup/, respectively, which are used to initialize real 2D transient hillslope models. The input files (.xml) and output results (.dat) of transient 2D hillslope models are located in model_04-hillslope_transient/. The input files (.xml) and output results (.dat) of the full 3D transient model is located in model_05-onepiece_transient_mannp1_ra/. The full 3D transient model is initialized by model_02-column_spinup/. Accessible by Python. (7) The MOSART routed discharge results (.csv) under Arctic conditions is located in huc190604020802_gauge15906000/MOSART/. Accessible by Python. (8) All Python codes (.py) used to parameterize full 3D model to decomposed 2D models are located in script/. These codes fit with watershed workflow (a watershed delineation tool) v1.4 under the branch gaob/v1.4 from https://github.com/gaobhub/watershed-workflow.git.

EARTH SCIENCE > CRYOSPHERE↗
NASA NTRSDate not supplied

Regional and Model-Specific Response Types in A Global Gridded Crop Model Ensemble

Crop models are often employed to project crop yields under changing conditions such as global warming and associated management change for adaptation. Multi-model ensembles are promoted to enhance the robustness of projections, but questions remain on what causes often large differences between projections of individual models. Global Gridded Crop Models (GGCMs) are especially exposed to this question when applied for assessing climate change impacts, adaptation, environmental impacts of agricultural production, because their results are used in downstream analyses, such as in integrated assessment or economic modeling for projecting future land-use change. Even though global gridded crop models are often based on detailed field-scale models or have implemented similar modeling principles in other ecosystem models, global-scale models are subject to substantial uncertainties from both model structure and parametrization as well as from calibration and input data quality. AgMIP’s Global Gridded Crop Model Intercomparison (GGCMI) has thus set out to intercompare GGCMs in order to evaluate model performance, describe model uncertainties, identify inconsistencies within the ensemble and underlying reasons, and to ultimately improve models and modeling capacities. In phase 2 of the GGCMI activities, 12 modeling groups followed a modeling protocol that asked for up to 1404 31-year global simulations at 0.5 arc-degree spatial resolution to assess models’ sensitivities to changes in carbon dioxide (C; 4 different levels) temperature (T; 7 different offset levels), water supply (W; 9 levels), and nitrogen (N; 3 levels), the so-called CTWN experiment (Franke et al. 2020; http://dx.doi.org/10.5194/gmd-13-2315-2020). We here present analyses of model response types using impact response surfaces along the C, T, W, and N dimensions, respectively and collectively. Doing so, we can understand differences in simulated responses per driver rather than aggregated changes in yields. We find that models’ sensitivities to the individual driver dimensions are substantially different and often more different across models than across regions. A cluster analysis finds regional and model-specific patterns. There is some agreement across models with respect to the spatial patterns of response types but strong differences in the distribution of response type clusters across models suggests that models need to undergo further scrutiny. We suggest establishing standards in model process evaluation not only against historical dynamics but also against dedicated experiments across the CTWN dimensions.

crop models↗
DOE OSTI2025

Guiding Principles for Geochemical/Thermodynamic Model Development and Validation in Nuclear Waste Disposal: A Close Examination of Recent Thermodynamic Models for H + —Nd 3+ —NO 3 - (—Oxalate) Systems

Development of a defensible source-term model (STM), usually a thermodynamical model for radionuclide solubility calculations, is critical to a performance assessment (PA) of a geologic repository for nuclear waste disposal. Such a model is generally subjected to rigorous regulatory scrutiny. In this article, we highlight key guiding principles for STM model development and validation in nuclear waste management. We illustrate these principles by closely examining three recently developed thermodynamic models with the Pitzer formulism for aqueous H + —Nd 3+ —NO 3 - (—oxalate) systems in a reverse alphabetical order of the authors: the XW model developed by Xiong and Wang, the OWC model developed by Oakes et al., and the GLC model developed by Guignot et al., among which the XW model deals with trace activity coefficients for Nd(III), while the OWC and GLC models are for concentrated Nd(NO 3 ) 3 electrolyte solutions. The principles highlighted include the following: (1) Principle 1. Validation against independent experimental data: A model should be validated against experimental data or field observations that have not been used in the original model parameterization. We tested the XW model against multiple independent experimental data sets including electromotive force (EMF), solubility, water vapor, and water activity measurements. The results show that the XW model is accurate and valid for its intended use for predicting trace activity coefficients and therefore Nd solubility in repository environments. (2) Principle 2. Testing for relevant and sensitive variables: Solution pH is such a variable for an STM and easily acquirable. All three models are checked for their ability to predict pH conditions in Nd(NO 3 ) 3 electrolyte solutions. The OWC model fails to provide a reasonable estimate for solution pH conditions, thus casting serious doubt on its validity for a source-term calculation. In contrast, both the XW and GLC models predict close-to-neutral pH values, in agreement with experimental measurements. (3) Principle 3. Honoring physical constraints: Upon close examination, it is found that the Nd(III)-NO 3 association schema in the OWC model suffers from two shortcomings. Firstly, its second stepwise stability constant for Nd(NO 3 ) 2+ (log K 2 ) is much higher than the first stepwise stability constant for NdNO 3 2+ (log K 1 ), thus violating the general rule of (log K 2 –log K 1 ) < 0, or $\frac{K1}{K2}$>1. Secondly, the OWC model predicts abnormally high activity coefficients for Nd(NO 3 ) 2 + (up to ~900) as the concentration increases. (4) Principle 4. Minimizing degrees of freedom for model fitting: The OWC model with nine fitted parameters is compared with the GLC model with five fitted parameters, as both models apply to the concentrated region for Nd(NO 3 ) 3 electrolyte solutions. The latter appears superior to the former because the latter can fit osmotic coefficient data equally well with fewer model parameters. The work presented here thus illustrates the salient points of geochemical model development, selection, and validation in nuclear waste management.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2006

Radiation Environment Modeling for Spacecraft Design: New Model Developments

A viewgraph presentation on various new space radiation environment models for spacecraft design is described. The topics include: 1) The Space Radiatio Environment; 2) Effects of Space Environments on Systems; 3) Space Radiatio Environment Model Use During Space Mission Development and Operations; 4) Space Radiation Hazards for Humans; 5) "Standard" Space Radiation Environment Models; 6) Concerns about Standard Models; 7) Inadequacies of Current Models; 8) Development of New Models; 9) New Model Developments: Proton Belt Models; 10) Coverage of New Proton Models; 11) Comparison of TPM-1, PSB97, AP-8; 12) New Model Developments: Electron Belt Models; 13) Coverage of New Electron Models; 14) Comparison of "Worst Case" POLE, CRESELE, and FLUMIC Models with the AE-8 Model; 15) New Model Developments: Galactic Cosmic Ray Model; 16) Comparison of NASA, MSU, CIT Models with ACE Instrument Data; 17) New Model Developmemts: Solar Proton Model; 18) Comparison of ESP, JPL91, KIng/Stassinopoulos, and PSYCHIC Models; 19) New Model Developments: Solar Heavy Ion Model; 20) Comparison of CREME96 to CREDO Measurements During 2000 and 2002; 21) PSYCHIC Heavy ion Model; 22) Model Standardization; 23) Working Group Meeting on New Standard Radiation Belt and Space Plasma Models; and 24) Summary.

Barth, Janet↗
NASA NTRS2021

Harmonized Emissions Component (HEMCO) 3.0 as a Versatile Emissions Component for Atmospheric Models: Application in the GEOS-Chem, NASA GEOS, WRF-GC, CESM2, NOAA GEFS-Aerosol, and NOAA UFS Models

Emissions are a central component of atmospheric chemistry models. The Harmonized Emissions Component (HEMCO) is a software component for computing emissions from a user-selected ensemble of emission inventories and algorithms. It allows users to re-grid, combine, overwrite, subset, and scale emissions from different inventories through a configuration file and with no change to the model source code. The configuration file also maps emissions to model species with appropriate units. HEMCO can operate in offline stand-alone mode, but more importantly it provides an online facility for models to compute emissions at runtime. HEMCO complies with the Earth System Modeling Framework (ESMF) for portability across models. We present a new version here, HEMCO 3.0, that features an improved three-layer architecture to facilitate implementation into any atmospheric model and improved capability for calculating emissions at any model resolution including multiscale and unstructured grids. The three-layer architecture of HEMCO 3.0 includes (1) the Data Input Layer that reads the configuration file and accesses the HEMCO library of emission inventories and other environmental data, (2) the HEMCO Core that computes emissions on the user-selected HEMCO grid, and (3) the Model Interface Layer that re-grids (if needed) and serves the data to the atmospheric model and also serves model data to the HEMCO Core for computing emissions dependent on model state (such as from dust or vegetation). The HEMCO Core is common to the implementation in all models, while the Data Input Layer and the Model Interface Layer are adaptable to the model environment. Default versions of the Data Input Layer and Model Interface Layer enable straightforward implementation of HEMCO in any simple model architecture, and options are available to disable features such as re-gridding that may be done by independent couplers in more complex architectures. The HEMCO library of emission inventories and algorithms is continuously enriched through user contributions so that new inventories can be immediately shared across models. HEMCO can also serve as a general data broker for models to process input data not only for emissions but for any gridded environmental datasets. We describe existing implementations of HEMCO 3.0 in (1) the GEOS-Chem “Classic” chemical transport model with shared-memory infrastructure, (2) the high-performance GEOS-Chem (GCHP) model with distributed-memory architecture, (3) the NASA GEOS Earth System Model (GEOS ESM), (4) the Weather Research and Forecasting model with GEOS-Chem (WRF-GC), (5) the Community Earth System Model Version 2 (CESM2), and (6) the NOAA Global Ensemble Forecast System – Aerosols (GEFS-Aerosols), as well as the planned implementation in the NOAA Unified Forecast System (UFS). Implementation of HEMCO in CESM2 contributes to the Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA) by providing a common emissions infrastructure to support different simulations of atmospheric chemistry across scales.

Haipeng Lin↗