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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 271 records · Page 15
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NASA NTRS1976

A global reference atmospheric model for surface to orbital altitudes

An empirical atmospheric model has been developed which generates values for pressure, density, temperature and winds from surface levels to orbital altitudes. The output parameters consist of components for: (1) latitude, longitude, and altitude dependent monthly means; (2) quasi-biennial oscillations; and (3) random perturbations to partially simulate the variability due to synoptic, diurnal, planetary wave and gravity wave variations. The monthly mean models consist of: NASA's four dimensional worldwide model for height, latitude, and longitude dependent monthly means from the surface to 25 km; and a newly developed latitude-longitude dependent model which is an extension of the Groves latitude dependent model for the region between 25 and 90 km. The Jacchia 1970 model is used above 90 km and is faired with the modified Groves values between 90 and 115 km. Quasi-biennial and random variation perturbations are computed from parameters determined from various empirical studies, and are added to the monthly mean values.

Justus, C. G.↗
NASA NTRS1989

Image processing software for providing radiometric inputs to land surface climatology models

During the First International Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), 80 gigabytes of image data were generated from a variety of satellite and airborne sensors in a multidisciplinary attempt to study energy and mass exchange between the land surface and the atmosphere. To make these data readily available to researchers with a range of image data handling experience and capabilities, unique image-processing software was designed to perform a variety of nonstandard image-processing manipulations and to derive a set of standard-format image products. The nonconventional features of the software include: (1) adding new layers of geographic coordinates, and solar and viewing conditions to existing data; (2) providing image polygon extraction and calibration of data to at-sensor radiances; and, (3) generating standard-format derived image products that can be easily incorporated into radiometric or climatology models. The derived image products consist of easily handled ASCII descriptor files, byte image data files, and additional per-pixel integer data files (e.g., geographic coordinates, and sun and viewing conditions). Details of the solutions to the image-processing problems, the conventions adopted for handling a variety of satellite and aircraft image data, and the applicability of the output products to quantitative modeling are presented. They should be of general interest to future experiment and data-handling design considerations.

Newcomer, Jeffrey A.↗
NASA NTRS2018

Mars 2020 Surface Mission Modeling Landing Site Thermal Environments

This paper presents work done by the Mars 2020 Mission Planning Team to characterize landing site thermal environments. A process was developed to take in ground temperature simulation data for each landing site and efficiently discretize it into six thermal environment bins. The Mars 2020 Thermal Team then performed detailed heater and energy modeling in each of those environments. The heater modeling results were implemented into a Monte Carlo based surface mission model to understand mission performance impacts. The Mars 2020 Instrument Teams used the results to inform their design and to better understand how the thermal conditions at each landing site affected their instruments.

Lange, Robert D.↗
NASA NTRS2018

Mars 2020 Surface Mission Modeling Landing Site Thermal Environments

This paper presents work done by the Mars 2020 Mission Planning Team to characterize landing site thermal environments. A process was developed to take in ground temperature simulation data for each landing site and efficiently discretize it into six thermal environment bins. The Mars 2020 Thermal Team then performed detailed heater and energy modeling in each of those environments. The heater modeling results were implemented into a Monte Carlo based surface mission model to understand mission performance impacts. The Mars 2020 Instrument Teams used the results to inform their design and to better understand how the thermal conditions at each landing site affected their instruments.

Lange, Robert D.↗
NASA NTRS2018

Mars 2020 Surface Mission Modeling: Landing Site Thermal Environments

This paper presents work done by the Mars 2020 Mission Planning Team to characterize landing site thermal environments. A process was developed to take in ground temperature simulation data for each landing site and efficiently discretize it into a handful of thermal bin environments. The Mars 2020 Thermal Team then performed detailed heater and energy modeling in each of those environments. The heater modeling results were implemented into a Monte Carlo based surface mission model to understand mission performance impacts. The Mars 2020 Instrument Teams used the results to inform their design and to better understand how the thermal conditions at each landing site affected their instruments.

Lange, Robert D.↗
NASA NTRS1991

Method and apparatus for sensor fusion

Method and apparatus for fusion of data from optical and radar sensors by error minimization procedure is presented. The method was applied to the problem of shape reconstruction of an unknown surface at a distance. The method involves deriving an incomplete surface model from an optical sensor. The unknown characteristics of the surface are represented by some parameter. The correct value of the parameter is computed by iteratively generating theoretical predictions of the radar cross sections (RCS) of the surface, comparing the predicted and the observed values for the RCS, and improving the surface model from results of the comparison. Theoretical RCS may be computed from the surface model in several ways. One RCS prediction technique is the method of moments. The method of moments can be applied to an unknown surface only if some shape information is available from an independent source. The optical image provides the independent information.

Krishen, Kumar↗
NASA NTRS1995

Estimating the urban bias of surface shelter temperatures using upper-air and satellite data. Part 1: Development of models predicting surface shelter temperatures

Multiple regression techniques were used to predict surface shelter temperatures based on the time period 1986-89 using upper-air data from the European Centre for Medium-Range Weather Forecasts (ECMWF) to represent the background climate and site-specific data to represent the local landscape. Global monthly mean temperature models were developed using data from over 5000 stations available in the Global Historical Climate Network (GHCN). Monthly maximum, mean, and minimum temperature models for the United States were also developed using data from over 1000 stations available in the U.S. Cooperative (COOP) Network and comparative monthly mean temperature models were developed using over 1150 U.S. stations in the GHCN. Three-, six-, and full-variable models were developed for comparative purposes. Inferences about the variables selected for the various models were easier for the GHCN models, which displayed month-to-month consistency in which variables were selected, than for the COOP models, which were assigned a different list of variables for nearly every month. These and other results suggest that global calibration is preferred because data from the global spectrum of physical processes that control surface temperatures are incorporated in a global model. All of the models that were developed in this study validated relatively well, especially the global models. Recalibration of the models with validation data resulted in only slightly poorer regression statistics, indicating that the calibration list of variables was valid. Predictions using data from the validation dataset in the calibrated equation were better for the GHCN models, and the globally calibrated GHCN models generally provided better U.S. predictions than the U.S.-calibrated COOP models. Overall, the GHCN and COOP models explained approximately 64%-95% of the total variance of surface shelter temperatures, depending on the month and the number of model variables. In addition, root-mean-square errors (rmse's) were over 3 C for GHCN models and over 2 C for COOP models for winter months, and near 2 C for GHCN models and near 1.5 C for COOP models for summer months.

Epperson, David L.↗
NASA NTRS2015

Evaluation of a Model-Based Groundwater Drought Indicator in the Conterminous U.S.

Monitoring groundwater drought using land surface models is a valuable alternative given the current lack of systematic in situ measurements at continental and global scales and the low resolution of current remote sensing based groundwater data. However, uncertainties inherent to land surface models may impede drought detection, and thus should be assessed using independent data sources. In this study, we evaluated a groundwater drought index (GWI) derived from monthly groundwater storage output from the Catchment Land Surface Model (CLSM) using a GWI similarly derived from in situ groundwater observations. Groundwater observations were obtained from unconfined or semi-confined aquifers in eight regions of the central and northeastern U.S. Regional average GWI derived from CLSM exhibited strong correlation with that from observation wells, with correlation coefficients between 0.43 and 0.92. GWI from both in situ data and CLSM was generally better correlated with the Standard Precipitation Index (SPI) at 12 and 24 month timescales than at shorter timescales, but it varied depending on climate conditions. The correlation between CLSM derived GWI and SPI generally decreases with increasing depth to the water table, which in turn depends on both bedrock depth (a CLSM parameter) and mean annual precipitation. The persistence of CLSM derived GWI is spatially varied and again shows a strong influence of depth to groundwater. CLSM derived GWI generally persists longer than GWI derived from in situ data, due at least in part to the inability of coarse model inputs to capture high frequency meteorological variability at local scales. The study also showed that groundwater can have a significant impact on soil moisture persistence where the water table is shallow. Soil moisture persistence was estimated to be longer in the eastern U.S. than in the west, in contrast to previous findings that were based on models that did not represent groundwater. Assimilation of terrestrial water storage data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission improved the correlation between CLSM based regional average GWI and that based on in situ data in six of the eight regions. Practical issues regarding the application of GRACE assimilated groundwater storage for drought detection are discussed. An important conclusion of this study is that model parameters that control the depth to the water table, including bedrock depth, strongly influence the evolution and persistence of simulated groundwater and require careful configuration for drought monitoring.

Evaluation↗
NASA NTRS2014

Evaluation of a Model-Based Groundwater Drought Indicator in the Conterminous U.S.

Monitoring groundwater drought using land surface models is a valuable alternative given the current lack of systematic in situ measurements at continental and global scales and the low resolution of current remote sensing based groundwater data. However, uncertainties inherent to land surface models may impede drought detection, and thus should be assessed using independent data sources. In this study, we evaluated a groundwater drought index (GWI) derived from monthly groundwater storage output from the Catchment Land Surface Model (CLSM) using a GWI similarly derived from in situ groundwater observations. Groundwater observations were obtained from unconfined or semi-confined aquifers in eight regions of the central and northeastern U.S. Regional average GWI derived from CLSM exhibited strong correlation with that from observation wells, with correlation coefficients between 0.43 and 0.92. GWI from both in situ data and CLSM was generally better correlated with the Standard Precipitation Index (SPI) at 12 and 24 month timescales than at shorter timescales, but it varied depending on climate conditions. The correlation between CLSM derived GWI and SPI generally decreases with increasing depth to the water table, which in turn depends on both bedrock depth (a CLSM parameter) and mean annual precipitation. The persistence of CLSM derived GWI is spatially varied and again shows a strong influence of depth to groundwater. CLSM derived GWI generally persists longer than GWI derived from in situ data, due at least in part to the inability of coarse model inputs to capture high frequency meteorological variability at local scales. The study also showed that groundwater can have a significant impact on soil moisture persistence where the water table is shallow. Soil moisture persistence was estimated to be longer in the eastern U.S. than in the west, in contrast to previous findings that were based on models that did not represent groundwater. Assimilation of terrestrial water storage data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission improved the correlation between CLSM based regional average GWI and that based on in situ data in six of the eight regions. Practical issues regarding the application of GRACE assimilated groundwater storage for drought detection are discussed. An important conclusion of this study is that model parameters that control the depth to the water table, including bedrock depth, strongly influence the evolution and persistence of simulated groundwater and require careful configuration for drought monitoring.

hydrology↗
NASA NTRS2011

Surface Contact Model for Comets and Asteroids

A contact force model was developed for use in touch and go (TAG) surface sampling simulations on small celestial bodies such as comets and asteroids. In TAG scenarios, a spacecraft descending toward the surface of a small body comes into contact with the surface for a short duration of time, collects material samples with a sampler device, and then ascends to leave the surface. The surface contact required 6-DOF (degrees of freedom) dynamics models due to coupling of the attitude and translation dynamics during the contact. The model described here is for contact scenarios that utilize a rotating brush wheel sampler (BWS) to collect surface material. The model includes stiffness and damping of the surface material during BWS vertical motion, lateral friction from the BWS dragging across the surface, and lateral shear from the rotating BWS scooping the surface material. This model is useful for any mission to asteroids or comets that incorporates surface sampling operations.

Blackmore, Lars James C.↗
NASA NTRS1977

Effects of geometry and jet velocity on noise associated with an upper-surface-blowing model

The noise characteristics associated with various upper surface blowing configurations were investigated using a small model consisting of a plate and flap assembly (simulated wing with flap) attached to a rectangular nozzle. Nozzle aspect ratio, flow-run length, and flap-deflection angle were the experimental parameters studied. Three nozzle-exit velocities were used. The normalized noise spectra obtained for different nozzle aspect ratios proved to be similar in terms of Strouhal number based on jet velocity and flow-run length. Consequently, the need for knowing local flow velocity and length scales (for example, at the flap trailing edge) as required in some of the existing noise prediction schemes is eliminated. Data are compared with results computed from three different noise prediction schemes, and the validity of each scheme is assessed. A simple method is proposed to evaluate the frequency dependence of acoustic shielding obtained with the simulated wing flap.

Clark, L. R.↗
NASA NTRS2013

Bayesian Revision of Residual Detection Power

This paper addresses some issues with quality assessment and quality assurance in response surface modeling experiments executed in wind tunnels. The role of data volume on quality assurance for response surface models is reviewed. Specific wind tunnel response surface modeling experiments are considered for which apparent discrepancies exist between fit quality expectations based on implemented quality assurance tactics, and the actual fit quality achieved in those experiments. These discrepancies are resolved by using Bayesian inference to account for certain imperfections in the assessment methodology. Estimates of the fraction of out-of-tolerance model predictions based on traditional frequentist methods are revised to account for uncertainty in the residual assessment process. The number of sites in the design space for which residuals are out of tolerance is seen to exceed the number of sites where the model actually fails to fit the data. A method is presented to estimate how much of the design space in inadequately modeled by low-order polynomial approximations to the true but unknown underlying response function.

DeLoach, Richard↗
NASA NTRS1974

Gulf Stream model

Surface elevation deviations in the Gulf Stream region off the eastern coast of the United States between Wallops Island, Virginia and Miami, Florida were investigated. The main causes of surface elevation deviations are geoid perturbations due to the continental shelf and the geostrophic adjustment of the density field due to the Gulf Stream. Quantitative surface elevation profiles were calculated based on geophysical measurements of gravity anomalies and hydrographic data. The results are presented graphically along with contemporaneous weather data. Comparisons are made between the profiles based on hydrographic data and a mean theoretical model. The theory of geostrophic flows including some classical Gulf Stream models is also presented briefly.

Source record↗
NASA NTRS2024

A Physics-Based Antarctic Melt Detection Technique: Combining Advanced Microwave Scanning Radiometer 2, Radiative-Transfer Modeling, and Firn Modeling

Surface melt on ice shelves has been linked to hydrofracture and subsequent ice shelf breakup. Since the 1990s, scientists have been using microwave radiometers to detect melt on ice shelves and ice sheets by applying various statistical thresholding techniques to identify significant increases in brightness temperature that are associated with melt. In this study, instead of using a fixed threshold, we force the Snow Radiative Transfer model (SMRT) with outputs from the Community Firn Model (CFM) to create a dynamic, physics-based threshold for melt. In the process, we also combine our method with statistical thresholding techniques and produce microwave grain size information in the process. We run this “Hybrid Method” across the Larsen C ice shelf as well as thirteen sites on the Antarctic Ice Sheet. Melt and non-melt days from the Hybrid Method and three statistical thresholding techniques match with surface energy balance within 94±1%; the effect of melt on the passive microwave is mostly binary and thus largely detectable by statistical thresholding techniques as well as physics-based techniques. Rather than always replacing statistical thresholding techniques with the Hybrid Method, we recommend using the Hybrid Method in studies where melt volume or grain size is of interest. In this study, we show that the Hybrid Method can be used to (a) model dry snow brightness temperatures of Antarctic snow and (b) derive a measure of grain size; therefore, it is an important step forwards towards using firn and radiative transfer modeling to quantify melt rather than to simply detect melt days.

Marissa E Dattler↗
NASA NTRS1995

Image Registration: A Necessary Evil

Registration of test and reference images is a key component of nearly all PSP data reduction techniques. This is done to ensure that a test image pixel viewing a particular point on the model is ratioed by the reference image pixel which views the same point. Typically registration is needed to account for model motion due to differing airloads when the wind-off and wind-on images are taken. Registration is also necessary when two cameras are used for simultaneous acquisition of data from a dual-frequency paint. This presentation will discuss the advantages and disadvantages of several different image registration techniques. In order to do so, it is necessary to propose both an accuracy requirement for image registration and a means for measuring the accuracy of a particular technique. High contrast regions in the unregistered images are most sensitive to registration errors, and it is proposed that these regions be used to establish the error limits for registration. Once this is done, the actual registration error can be determined by locating corresponding points on the test and reference images, and determining how well a particular registration technique matches them. An example of this procedure is shown for three transforms used to register images of a semispan model. Thirty control points were located on the model. A subset of the points were used to determine the coefficients of each registration transform, and the error with which each transform aligned the remaining points was determined. The results indicate the general superiority of a third-order polynomial over other candidate transforms, as well as showing how registration accuracy varies with number of control points. Finally, it is proposed that image registration may eventually be done away with completely. As more accurate image resection techniques and more detailed model surface grids become available, it will be possible to map raw image data onto the model surface accurately. Intensity ratio data can then be obtained by a "model surface ratio," rather than an image ratio. The problems and advantages of this technique will be discussed.

Bell, James↗
NASA NTRS1993

Mg II and Ly-alpha fluxes in M dwarfs - Evaluation of an acoustic model

Surface fluxes of Mg II and Ly-alpha from a sample of M dwarfs have been reported by Panagi and Mathioudakis (PM, 1992). In order to determine if acoustic effects can reproduce the fluxes in the least active ('basal') stars in the PM sample, we have constructed steady state models of plane-parallel atmospheres with T(eff) = 3000 and 4000 K including heating by shock dissipation. The models incorporate radiative losses in the chromosphere by solving the transfer equation for two strong lines (Mg II k and Ly-alpha). Predictions of standard weak shock theory are expected to overestimate the rate of energy deposition in the chromospheres of M dwarfs compared to the rate of deposition in F, G, or K dwarfs. In order to incorporate this effect in M dwarfs, we compute a series of atmospheric models in which, for a given T(eff), the standard weak shock dissipation rate is reduced by a series of factors F(r). Although the input acoustic flux F(mech) may in principle be determined uniquely by T(eff) and log g, the correct value to use in any particular case is not well known. We therefore use F(mech) and F(r) as parameters to construct a family of M dwarf models at various T(eff) and g. Comparing with the observed fluxes in the least active M dwarfs of the PM sample, we find that our models reproduce the observed fluxes of both Mg II and Ly-alpha best if F(mech) is close to the value predicted by Bohn (1984) and if F(r) is approximately equal to 10-20.

Mullan, D. J.↗
NASA NTRS2011

Simulation of the Indian Summer Monsoon Using Comprehensive Atmosphere-land Interactions, in the Absence of Two-way Air-sea Interactions

Community Land Model version 2 (CLM2) as a comprehensive land surface model and a simple land surface model (SLM) were coupled to an atmospheric climate model to investigate the role of land surface processes in the development and the persistence of the South Asian summer monsoon. Two-way air-sea interactions were not considered in order to identify the reproducibility of the monsoon evolution by the comprehensive land model, which includes more realistic vertical soil moisture structures, vegetation and 2-way atmosphere-land interactions at hourly intervals. In the monsoon development phase (May and June). comprehensive land-surface treatment improves the representation of atmospheric circulations and the resulting convergence/divergence through the improvements in differential heating patterns and surface energy fluxes. Coupling with CLM2 also improves the timing and spatial distribution of rainfall maxima, reducing the seasonal rainfall overestimation by approx.60 % (1.8 mm/d for SLM, 0.7 mm/dI for CLM2). As for the interannual variation of the simulated rainfall, correlation coefficients of the Indian seasonal rainfall with observation increased from 0.21 (SLM) to 0.45 (CLM2). However, in the mature monsoon phase (July to September), coupling with the CLM2 does not exhibit a clear improvement. In contrast to the development phase, latent heat flux is underestimated and sensible heat flux and surface temperature over India are markedly overestimated. In addition, the moisture fluxes do not correlate well with lower-level atmospheric convergence, yielding correlation coefficients and root mean square errors worse than those produced by coupling with the SLM. A more realistic representation of the surface temperature and energy fluxes is needed to achieve an improved simulation for the mature monsoon period.

Monsoon Precipitation↗