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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

A Radiative Transfer Model for Microwave Emission from Soils

The radiative transfer equation for an absorbing medium is used to develop a model for microwave emission from soils. The model calculates the microwave emission intensity in terms of the brightness temperature as a function of the soil moisture and temperature. The consistency of the model is verified by a comparative study of the present model with other microwave emission models. The effect of surface roughness on the brightness temperature is studied by modifying the Fresnel reflection coefficient and by including the surface depolarization effect. The quantitative effect of the surface roughness is studied and it is demonstrated that the brightness temperatures observed for a natural agricultural terrain can be explained through the inclusion of the roughness effect. The surface roughness effect is further analyzed to obtain formulae which are useful in the analysis of the brightness temperatures, particularly, to obtain soil moisture information from the brightness. temperatures. The sensitivity of the brightness temperature to the soil temperature variations is studied both qualitatively and quantitatively. A simple formula is obtained to calculate the soil temperature dependence of the brightness temperature in terms of the surface and the deep soil temperatures. An algorithm to normalize the brightness temperatures so as to compare microwave observations under different soil temperature conditions is also discussed. A program listing of the model is given in the appendix.

Choudhury, B. J.↗
NASA NTRS2004

MODIS Snow and Sea Ice Products

In this chapter, we describe the suite of Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua snow and sea ice products. Global, daily products, developed at Goddard Space Flight Center, are archived and distributed through the National Snow and Ice Data Center at various resolutions and on different grids useful for different communities Snow products include binary snow cover, snow albedo, and in the near future, fraction of snow in a 5OO-m pixel. Sea ice products include ice extent determined with two different algorithms, and sea ice surface temperature. The algorithms used to develop these products are described. Both the snow and sea ice products, available since February 24,2000, are useful for modelers. Validation of the products is also discussed.

Hall, Dorothy K.↗
DOE OSTI2024

An Inverse Heat Conduction Algorithm Used to Calculate the Temperatures on the Inner and Outer Cylindrical Surfaces of an HMX-based PBX Explosive Annulus

In this work, a new Inverse Heat Conduction (IHC) algorithm is applied to estimate the surface temperatures at twelve locations on the inner and outer cylindrical boundaries of an HMX-based Plastic Bonded Explosive (PBX) annulus. This IHC algorithm was developed in references using a set of Direct Heat Conduction (DHC) solutions and a temperature correction method. The DHC solutions were calculated using a Galerkin based finite element (FE) method. This HMX based PBX annulus was used in the Large Scale Annular Cookoff (LSAC) experiment, Shot 5. The reason Shot 5 was chosen as a prototype mathematical model for this study is that the temperature was measured at eighteen locations in the midplane of the HMX-based PBX annulus. In addition, this annulus underwent an experimental thermal ignition and a deflagration that caused a thermal explosion and the disassembly of the experiment. The objective of this study is to describe how the application of the temperature correction algorithm produced the convergence of the DHC solutions to the measured temperatures at twelve internal locations in the midplane of the HMX-based PBX annulus.

36 MATERIALS SCIENCE↗
NASA NTRS1992

Arctic ice surface temperature retrieval from AVHRR thermal channels

The relationship between AVHRR thermal radiances and the surface (skin) temperature of Arctic snow-covered sea ice is examined through forward calculations of the radiative transfer equation, providing an ice/snow surface temperature retrieval algorithm for the central Arctic Basin. Temperature and humidity profiles with cloud observations collected on an ice island during 1986-1987 are used. Coefficients that correct for atmospheric attenuation are given for three Arctic clear sky 'seasons', as defined through statistical analysis of the daily profiles, for the NOAA 7, 9, and 11 satellites. Modeled directional snow emissivities, different in the two split-window (11 and 12 micron) channels, are used. While the sensor scan angle is included explicitly in the correction equation, its effect in the dry Arctic atmosphere is small, generally less than 0.1 K. Using the split-window channels and scan angle, the rms error in the estimated ice surface temperature is less than 0.1 K in all seasons. Inclusion channel 3(3.7 microns) during the winter decreases the rms error by less than 0.003

Key, J.↗
NASA NTRS1993

Vibrational nonequilibrium effects on diatomic dissociation rates

The collision-induced dissociation rate of diatomic molecules from a ladder of rotational and anharmonic vibrational states is developed, and the correction for vibrational nonequilibrium is considered. The result is similar to an analytic correction derived by Hammerling et al. (1959) for harmonic oscillators. An empirical correction algorithm suggested by Park (1987, 1990) gives similar results when vibrational temperature is comparable to kinetic temperature but underestimates the dissociation rate when vibrational temperature is small compared with the kinetic temperature. This algorithm uses an effective temperature in the experimentally determined Arrhenius expression for the rate coefficient, which is a weighted average of the vibrational and kinetic temperature, whereas theory indicates that kinetic temperature should appear only in the exponential term of the Arrhenius expression. Nevertheless, an effective temperature can always be found that will numerically duplicate the proper rate coefficient at any given condition, but a constant weighting factor cannot be expected to provide this. However, the algorithm can he adjusted to give reasonable results over a range of conditions if the geometric weighting factor is taken to be a simple linear function of the ratio of vibrational to kinetic temperature in the gas.

Hansen, C. F.↗
NASA NTRS1994

An Algorithm to Generate Deep-Layer Temperatures from Microwave Satellite Observations for the Purpose of Monitoring Climate Change

An algorithm for generating deep-layer mean temperatures from satellite-observed microwave observations is presented. Unlike traditional temperature retrieval methods, this algorithm does not require a first guess temperature of the ambient atmosphere. By eliminating the first guess a potentially systematic source of error has been removed. The algorithm is expected to yield long-term records that are suitable for detecting small changes in climate. The atmospheric contribution to the deep-layer mean temperature is given by the averaging kernel. The algorithm computes the coefficients that will best approximate a desired averaging kernel from a linear combination of the satellite radiometer's weighting functions. The coefficients are then applied to the measurements to yield the deep-layer mean temperature. Three constraints were used in deriving the algorithm: (1) the sum of the coefficients must be one, (2) the noise of the product is minimized, and (3) the shape of the approximated averaging kernel is well-behaved. Note that a trade-off between constraints 2 and 3 is unavoidable. The algorithm can also be used to combine measurements from a future sensor (i.e., the 20-channel Advanced Microwave Sounding Unit (AMSU)) to yield the same averaging kernel as that based on an earlier sensor (i.e., the 4-channel Microwave Sounding Unit (MSU)). This will allow a time series of deep-layer mean temperatures based on MSU measurements to be continued with AMSU measurements. The AMSU is expected to replace the MSU in 1996.

Goldberg, Mitchell D.↗
NASA NTRS2011

Validation of the MODIS "Clear-Sky" Surface Temperature of the Greenland Ice Sheet

Surface temperatures on the Greenland Ice Sheet have been studied on the ground, using automatic weather station (AWS) data from the Greenland-Climate Network (GC-Net), and from analysis of satellite sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented from 1981 to present. We extend and refine this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (MODIS) data from March 2000 to the present. To permit changes to be observed over time, we are developing a well-characterized monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using data from both the Terra and Aqua satellites. We use the MODIS ice-surface temperature (IST) algorithm. Validation of the CDR consists of several facets: 1) comparisons between the Terra and Aqua IST maps; 2) comparisons between ISTs and in-situ measurements; 3) comparisons between ISTs and AWS data; and 4) comparisons of ISTs with surface temperatures derived from other satellite instruments such as the Thermal Emission and Reflection Radiometer. In this work, we focus on 1) and 2) above. Surface temperatures on the Greenland Ice Sheet have been studied on the ground, using automatic weather station (AWS) data from the Greenland-Climate Network (GC-Net), and from analysis of satellite sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented from 1981 to present. We extend and refine this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (MODIS) data from March 2000 to the present. To permit changes to be observed over time, we are developing a well-characterized monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using data from both the Terra and Aqua satellites. We use the MODIS ice-surface temperature (IST) algorithm. Validation of the CDR consists of several facets: 1) comparisons between the Terra and Aqua IST maps; 2) comparisons between ISTs and in-situ measurements; 3) comparisons between ISTs and AWS data; and 4) comparisons of ISTs with surface temperatures derived from other satellite instruments such as the Thermal Emission and Reflection Radiometer. In this work, we focus on 1) and 2) above. First we provide comparisons between Terra and Aqua swath-based ISTs at approximately 14:00 Local Solar Time, reprojected to 12.5 km polar stereographic cells. Results show good correspondence when Terra and Aqua data were acquired within 2 hrs of each other. For example, for a cell centered over Summit Camp (72.58 N, 38.5 W), the average agreement between Terra and Aqua ISTs is 0.74 K (February 2003), 0.47 K (April 2003), 0.7 K (August 2003) and 0.96 K (October 2003) with the Terra ISTs being generally lower than the Aqua ISTs. More precise comparisons will be calculated using pixel data at the swath level, and correspondence between Terra and Aqua IST is expected to be closer. (Because of cloud cover and other considerations, only a few common cloud-free swaths are typically available for each month for comparison.) Additionally, previous work comparing land-surface temperatures (LSTs) from the standard MODIS LST product and in-situ surface-temperature data at Summit Camp on the Greenland Ice Sheet show that Terra MODIS LSTs are about 3 K lower than in-situ temperatures at Summit Camp, during the winter of 2008-09. This work will be repeated using both Terra and Aqua IST pixel data (in place of LST data). In conclusion, we demonstrate that the uncertainties in the CDR will be well characterized as we work through the various facets of its validation.

Hall, Dorothy K.↗
DOE OSTI2022

Iterative subspace algorithms for finite-temperature solution of Dyson equation

One-particle Green’s functions obtained from the self-consistent solution of the Dyson equation can be employed in the evaluation of spectroscopic and thermodynamic properties for both molecules and solids. However, typical acceleration techniques used in the traditional quantum chemistry self-consistent algorithms cannot be easily deployed for the Green’s function methods because of a non-convex grand potential functional and a non-idempotent density matrix. Moreover, the optimization problem can become more challenging due to the inclusion of correlation effects, changing chemical potential, and fluctuations of the number of particles. In this paper, we study acceleration techniques to target the self-consistent solution of the Dyson equation directly. We use the direct inversion in the iterative subspace (DIIS), the least-squared commutator in the iterative subspace (LCIIS), and the Krylov space accelerated inexact Newton method (KAIN). We observe that the definition of the residual has a significant impact on the convergence of the iterative procedure. Based on the Dyson equation, we generalize the concept of the commutator residual used in DIIS and LCIIS and compare it with the difference residual used in DIIS and KAIN. The commutator residuals outperform the difference residuals for all considered molecular and solid systems within both GW and GF2. For a number of bond-breaking problems, we found that an easily obtained high-temperature solution with effectively suppressed correlations is a very effective starting point for reaching convergence of the problematic low-temperature solutions through a sequential reduction of temperature during calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2001

Simultaneous Retrieval of Temperature, Water Vapor and Ozone Atmospheric Profiles from IASI: Compression, De-noising, First Guess Retrieval and Inversion Algorithms

A fast temperature water vapor and ozone atmospheric profile retrieval algorithm is developed for the high spectral resolution Infrared Atmospheric Sounding Interferometer (IASI) space-borne instrument. Compression and de-noising of IASI observations are performed using Principal Component Analysis. This preprocessing methodology also allows, for a fast pattern recognition in a climatological data set to obtain a first guess. Then, a neural network using first guess information is developed to retrieve simultaneously temperature, water vapor and ozone atmospheric profiles. The performance of the resulting fast and accurate inverse model is evaluated with a large diversified data set of radiosondes atmospheres including rare events.

Aires, F.↗
NASA NTRS1996

Land Surface Temperature Measurements form EOS MODIS Data

We have developed a physics-based land-surface temperature (LST) algorithm for simultaneously retrieving surface band-averaged emissivities and temperatures from day/night pairs of MODIS (Moderate Resolution Imaging Spectroradiometer) data in seven thermal infrared bands. The set of 14 nonlinear equations in the algorithm is solved with the statistical regression method and the least-squares fit method. This new LST algorithm was tested with simulated MODIS data for 80 sets of band-averaged emissivities calculated from published spectral data of terrestrial materials in wide ranges of atmospheric and surface temperature conditions. Comprehensive sensitivity and error analysis has been made to evaluate the performance of the new LST algorithm and its dependence on variations in surface emissivity and temperature, upon atmospheric conditions, as well as the noise-equivalent temperature difference (NE(Delta)T) and calibration accuracy specifications of the MODIS instrument. In cases with a systematic calibration error of 0.5%, the standard deviations of errors in retrieved surface daytime and nighttime temperatures fall between 0.4-0.5 K over a wide range of surface temperatures for mid-latitude summer conditions. The standard deviations of errors in retrieved emissivities in bands 31 and 32 (in the 10-12.5 micrometer IR spectral window region) are 0.009, and the maximum error in retrieved LST values falls between 2-3 K. Several issues related to the day/night LST algorithm (uncertainties in the day/night registration and in surface emissivity changes caused by dew occurrence, and the cloud cover) have been investigated. The LST algorithms have been validated with MODIS Airborne Simulator (MAS) dada and ground-based measurement data in two field campaigns conducted in Railroad Valley playa, NV in 1995 and 1996. The MODIS LST version 1 software has been delivered.

Wan, Zhengming↗
DOE OSTI2019

Friction stir processing of dual certified 304/304L austenitic stainless steel for improved cavitation erosion resistance

Cavitation phenomenon is known to be prevalent in equipment in hydraulic environments. Understanding cavitation and improving the cavitation resistance of commonly used materials is of interest for both scientific and economic reasons. In this study, friction stir processing was employed to modify commercial dual certified AISI 304/304L austenitic stainless steel plates. The cavitation erosion resistance of the processed plates was evaluated and compared to that of the unprocessed steel. A temperature control algorithm was employed to maintain a target tool temperature during the processing. The cross sections of the processed nuggets were evaluated using optical microscopy, scanning electron microscopy and Vickers hardness testing. Cavitation testing was performed conforming to ASTM G134 on specimens cut out of the nuggets of the commercially unprocessed and the processed 304/304L steel. The tool temperature was found to affect the microstructure and the cavitation performance. Friction stir processed steel showed 3 times better cavitation resistance than the unprocessed 304/304L. Surface cavitation patterns and cavitation rates were characterized and the mechanisms of material removal were discussed.

Jiang, Xiujuan↗
NASA NTRS1979

Evaluation and analysis of Seasat-A scanning multichannel Microwave Radiometer (SMMR) Antenna Pattern Correction (APC) algorithm

The brightness temperature data produced by the SMMR final Antenna Pattern Correction (APC) algorithm is discussed. The algorithm consisted of: (1) a direct comparison of the outputs of the final and interim APC algorithms; and (2) an analysis of a possible relationship between observed cross track gradients in the interim brightness temperatures and the asymmetry in the antenna temperature data. Results indicate a bias between the brightness temperature produced by the final and interim APC algorithm.

Kitzis, J. L.↗
NASA NTRS1991

Temperature dependence of optical properties of GaAs

The effect of temperature on the optical properties of GaAs was investigated using spectroscopic ellipsometry measurements, between room temperature and about 610 C in increments of 50 C, of pseudodielectric functions and related optical constants of GaAs. A quantitative analysis of the pseudodielectric function spectrum was carried out using a harmonic-oscillator approximation (HOA) to fit the measured dielectric functions. Good fits were obtained with this model, which provides a convenient means of reproducing the GaAs dielectric function at any temperature, by using the temperature-dependent oscillator parameters. The HOA analysis also provides information about band-gap variation with temperature. Using the measured optical constants at a number of fixed temperatures, an algorithm was developed for computing the dielectric function spectrum at an arbitrary temperature in the range 22-610 C.

Yao, Huade↗
NASA NTRS1993

Atmospheric infrared sounder

Work continued on analysis of data from the TOGA-COARE experiment. The MIT Microwave Temperature Sounder was flown on NASA's ER-2 at Wallops Island in the CAMEX experiment during September and October. The preliminary version of the 'microwave first-guess' algorithm for temperature and moisture was delivered to JPL. In the iterative minimum-variance algorithm moisture retrievals from MHS make use of the retrieved temperature profile in calculation of weighting functions and in determining the saturation moisture capacity at each level. Simulations have been run to address the question of how important the temperature profile accuracy is to the moisture retrieval.

Rosenkranz, Philip W.↗
DOE OSTI2026

Wet-Bulb Temperature from Pressure, Relative Humidity, and Air Temperature

Abstract The algorithms currently in use for calculating the wet-bulb temperature from pressure, relative humidity, and air temperature have errors of a degree or more. Here, the equation for the thermodynamic wet-bulb temperature is derived using the Rankine–Kirchhoff approximations, which are highly accurate for meteorological and climatological applications. Likewise, equations are derived for the thermodynamic ice-bulb temperature and for the psychrometric wet-bulb and ice-bulb temperatures. The equations are fast to solve, requiring only a microsecond on a current laptop computer, and the results match empirical data to within hundredths of a degree. Furthermore, the equations reveal the existence of air temperatures and humidities that generate bistability: Evaporating liquid water is stable at a liquid temperature above freezing and, simultaneously, sublimating ice is stable at an ice temperature below freezing.

Romps, David M↗
NASA NTRS1982

Determination of the horizontal and vertical distribution of clouds from infrared satellite sounding data

A numerical algorithm, based on a physical inversion of the radiative transfer equation, is developed to retrieve the global distribution of the horizontal cloud cover, the cloud-top pressure levels and their temperature. The algorithm makes use of infrared and microwave temperature sounding data to derive the clear-column vertical temperature profiles and then uses the same infrared sounding data to obtain the corresponding cloud parameters. Experimental verification of this method is carried out using data from the High resolution Infrared Sounder (HIRS) and the Microwave Sounding Unit (MSU) operating on the NOAA weather satellite system.

Chahine, M. T.↗
NASA NTRS1989

Modeling surface temperature distributions in forest landscapes

A model of the frequency distributions of the spatial variability in surface temperature is presented. Surface temperature data are obtained from two daytime and two nighttime flights of the Thermal IR Multispectral Scanner (TIMS) over forest land in western Oregon in August, 1985. The temperature values are corrected for atmospheric attenuation and thermal radiation emission with the LOWTRAN-6 algorithm. The temperature distributions were modeled with a two-parameter beta probability density distribution and the fit of the model was evaluated by comparison with the TIMS data set. Use of the model's parameters to identify and classify surface types shows good discrimination among various surfaces for the daytime images, with less distinct discrimination for the nighttime images.

Holbo, H. R.↗