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At least 1,603 records · Page 89

Power Law Versus Exponential Form of Slow Crack Growth of Advanced Structural Ceramics: Dynamic Fatigue

The life prediction analysis based on an exponential crack velocity formulation was examined using a variety of experimental data on glass and advanced structural ceramics in constant stress-rate ("dynamic fatigue") and preload testing at ambient and elevated temperatures. The data fit to the strength versus In (stress rate) relation was found to be very reasonable for most of the materials. It was also found that preloading technique was equally applicable for the case of slow crack growth (SCG) parameter n > 30. The major limitation in the exponential crack velocity formulation, however, was that an inert strength of a material must be known priori to evaluate the important SCG parameter n, a significant drawback as compared to the conventional power-law crack velocity formulation.

Choi, Sung R.↗

Areas of Weakly Anomalous to Anomalous Surface Temperature in Dolores County, Colorado, as Identified from ASTER Thermal Data

Note: This "Weakly Anomalous to Anomalous Surface Temperature" dataset differs from the "Anomalous Surface Temperature" dataset for this county (another remotely sensed CIRES product) by showing areas of modeled temperatures between 1o and 2o above the mean, as opposed to the greater than 2o temperatures contained in the "Anomalous Surface Temperature" dataset. This layer contains areas of anomalous surface temperature in Dolores County identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled very warm surface exposures (thermal anomalies) Note: 'o' is used in this description to represent lowercase sigma.

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Areas of Weakly Anomalous to Anomalous Surface Temperature in Chaffee County, Colorado, as Identified from ASTER Thermal Data

Note: This "Weakly Anomalous to Anomalous Surface Temperature" dataset differs from the "Anomalous Surface Temperature" dataset for this county (another remotely sensed CIRES product) by showing areas of modeled temperatures between 1o and 2o above the mean, as opposed to the greater than 2o temperatures contained in the "Anomalous Surface Temperature" dataset. This layer contains areas of anomalous surface temperature in Chaffee County identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled very warm surface exposures (thermal anomalies). Note: 'o' is used in this description to represent lowercase sigma.

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Areas of Weakly Anomalous to Anomalous Surface Temperature in Archuleta County, Colorado, as Identified from ASTER Thermal Data

Note: This "Weakly Anomalous to Anomalous Surface Temperature" dataset differs from the "Anomalous Surface Temperature" dataset for this county (another remotely sensed CIRES product) by showing areas of modeled temperatures between 1o and 2o above the mean, as opposed to the greater than 2o temperatures contained in the "Anomalous Surface Temperature" dataset. This layer contains areas of anomalous surface temperature in Archuleta County identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature between 1o and 2o were considered ASTER modeled warm surface exposures (thermal anomalies). Note: 'o' is used in this description to represent lowercase sigma.

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Areas of Anomalous Surface Temperature in Archuleta County, Colorado, as Identified from ASTER Thermal Data

This layer contains areas of anomalous surface temperature in Archuleta County identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled very warm surface exposures (thermal anomalies). Note: 'o' is used in this description to represent lowercase sigma

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A comparison between Nimbus 5 THIR and ITPR temperatures and derived winds with rawinsonde data obtained in the AVE II experiment

During the second Atmospheric Variability Experiment (AVE II), atmospheric temperature profiles were computed from Nimbus 5 data, which comprised ITPR, NEMS, and SCR measurements. Rawinsonde data were obtained from NWS stations in the AVE II network and processed for each pressure contact; the soundings closest in space and time were interpolated to the Nimbus 5 sounding points for comparison purposes. Cross sections of thermal and geostrophic winds were computed from satellite-derived cross sections of temperature along the Nimbus orbital track.

Arnold, J. E.↗

As-built design specification for the digital derivation of daily and monthly data bases from synoptic observations of temperature and precipitation for the People's Republic of China

A data base of synoptic meteorological information was compiled for the People's Republic of China, as an integral part of the Large Area Crop Inventory Experiment. A system description is provided, including hardware and software specifications, computation algorithms and an evaluation of output validity. Operations are also outlined, with emphasis placed on least squares interpolation.

Jeun, B. H.↗

Ion thruster thermal characteristics and performance.

Experimental and analytical results for a typical 20-cm-diam, hollow-cathode ion thrustor are reported. The foundation of the investigation was the application of thermal model correction techniques. Pertinent thermal properties and plasma heating characteristics of the thrustor were determined through correlation and integration of temperature measurement data with a single-state Wiener-Kalman filter. The thrustor self-heating levels on various parts were realistically estimated. Analytically predicted temperatures were forced to agree with the measured values for the purpose of constructing a corrected thermal model, which could then be used to evaluate more realistic thrustor circumstances and environments. The expected accuracy of the resultant analytical network model was demonstrated to be plus or minus 10 K. Thrustor thermal performance data for a typical five-thrustor array are presented as functions of environmental solar intensities. The thermal analyses are also extended to a 30-cm thrustor system.

Wen, L.↗

Areas of Weakly Anomalous to Anomalous Surface Temperature in Routt County, Colorado, as Identified from ASTER Thermal Data

Note: This "Weakly Anomalous to Anomalous Surface Temperature" dataset differs from the "Anomalous Surface Temperature" dataset for this county (another remotely sensed CIRES product) by showing areas of modeled temperatures between 1o and 2o above the mean, as opposed to the greater than 2o temperatures contained in the "Anomalous Surface Temperature" dataset. This layer contains areas of anomalous surface temperature in Routt County identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature between 1o and 2o were considered ASTER modeled warm surface exposures (thermal anomalies). Note: 'o' is used in this description to represent lowercase sigma.

15 GEOTHERMAL ENERGY↗

Areas of Anomalous Surface Temperature in Chaffee County, Colorado, as Identified from ASTER Thermal Data

This layer contains areas of anomalous surface temperature in Chaffee County identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled very warm surface exposures (thermal anomalies). Note: 'o' is used in this description to represent lowercase sigma

15 GEOTHERMAL ENERGY↗

Areas of Anomalous Surface Temperature in Routt County, Colorado, as Identified from ASTER Thermal Data

This layer contains areas of anomalous surface temperature in Routt County identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled very warm surface exposures (thermal anomalies). Note: 'o' is used in this description to represent lowercase sigma.

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Synthesis method comparison of compositionally complex rare earth-based Ruddlesden–Popper n = 1 T'-type cuprates

The multicomponent approach has been successfully expanded to the Ruddlesden–Popper structure with the synthesis of two different high-entropy cuprate compositions: (La 0.2 Nd 0.2 Gd 0.2 Tb 0.2 Dy 0.2 ) 2 CuO 4 and (La 0.2 Pr 0.2 Nd 0.2 Sm 0.2 Eu 0.2 ) 2 CuO 4 . Additionally, the effect of synthesis method is explored using both solid-state reaction and polymeric steric entrapment (PSE) methods. It is found that PSE leads to more randomly distributed cation species, providing an advantageous method of synthesis for the growing field of high entropy oxides. In situ high-temperature x-ray diffraction tracks the amorphous to crystalline phase transformation in (La 0.2 Nd 0.2 Gd 0.2 Tb 0.2 Dy 0.2 ) 2 CuO 4 powder, synthesized using the PSE method. Using the High-Temperature XRD data, a method for gaining information on the kinetic behavior is also applied. Magnetometry of both compositions indicates ferrimagnetic behavior at low temperatures.

36 MATERIALS SCIENCE↗

The thermal history of interplanetary dust particles collected in the Earth's stratosphere

Fragments of 24 individual interplanetary dust particles (IDPs) collected in the Earth's stratosphere were obtained from NASA's Johnson Space Center collection and subjected to pulse-heating sequences to extract He and Ne and to learn about the thermal history of the particles. A motivation for the investigation was to see if the procedure would help distinguish between IDPs of asteroidal and cometary origin. The use of a sequence of short-duration heat pulses to perform the extractions is an improvement over the employment of a step-heating sequence, as was used in a previous investigation. The particles studied were fragments of larger parent IDPs, other fragments of which, in coordinated experiments, are undergoing studies of elemental and mineralogical composition in other laboratories. While the present investigation will provide useful temperature history data for the particles, the relatively large size of the parent IDPs (approximately 40 micrometers in diameter) resulted in high entry deceleration temperatures. This limited the usefulness of the study for distinguishing between particles of asteroidal and cometary origin.

Nier, A. O.↗

Global Summary MGS TES Data and Mars-Gram Validation

Mars Global Reference Atmospheric Model (Mars-GRAM 2001) is an engineering-level Mars atmosphere model widely used for many Mars mission applications. From 0-80 km, it is based on NASA Ames Mars General Circulation Model (MGCM), while above 80 km it is based on University of Arizona Mars Thermospheric General Circulation Model. Mars-GRAM 2001 and MGCM use surface topograph$ from Mars Global Surveyor Mars Orbiting Laser Altimeter (MOLA). Validation studies are described comparing Mars-GRAM with a global summary data set of Mars Global Surveyor Thermal Emission Spectrometer (TES) data. TES averages and standard deviations were assembled from binned TES data which covered surface to approx. 40 km, over more than a full Mars year (February, 1999 - June, 2001, just before start of a Mars global dust storm). TES data were binned in 10-by-10 degree latitude-longitude bins (i.e. 36 longitude bins by 19 latitude bins), 12 seasonal bins (based on 30 degree increments of Ls angle). Bin averages and standard deviations were assembled at 23 data levels (temperature at 21 pressure levels, plus surface temperature and surface pressure). Two time-of day bins were used: local time near 2 or 14 hours local time). Two dust optical depth bins wereused: infrared optical depth either less than or greater than 0.25 (which corresponds to visible optical depth either less than or greater than about 0.5). For interests in aerocapture and precision entry and landing, comparisons focused on atmospheric density. TES densities versus height were computed from TES temperature versus pressure, using assumptions of perfect gas law and hydrostatics. Mars-GRAM validation studies used density ratio (TES/Mars-GRAM) evaluated at data bin center points in space and time. Observed average TES/Mars-GRAM density ratios were generally 1+/-0.05, except at high altitudes (15-30 km, depending on season) and high latitudes (> 45 deg N), or at most altitudes in the southern hemisphere at Ls approx. 90 and 180deg). Compared to TES averages for a given latitude and season, TES data had average density standard deviation about the mean of approx. 65-10.5% (varying with height) for all data, or approx. 5-12%, depending on time of day and dust optical depth. Average standard deviation of TES/Mars-GRAM density ratio was 8.9% for local time 2 hours and 7.1% for local time 14 hours. Thus standard deviation of observed TES/Mars-GRAM density ratio, evaluated at matching positions and times, is about the same as the standard deviation of TES data about the TES mean value at a given position and season.

Justus, C.↗

An analysis of the hybrid internal mass modeling approach in EnergyPlus

Accurate simulation of building system dynamics is particularly important for understanding building energy flexibility. Among all dynamics in a building, a zone temperature’s variation is especially important, as it significantly affects a building’s electricity load profile when its heating, ventilating, and air conditioning (HVAC) system is controlled with on/off cycles or setpoint reset strategies. To accurately simulate a zone temperature’s dynamics, internal mass needs to be modeled carefully. In this paper, we compare the two internal mass modeling approaches provided by EnergyPlus, i.e., internal mass object and zone air capacitance multiplier, to better understand their impacts on zone temperature simulation. Real building zone temperature dynamic data from small- and medium-sized office buildings are analyzed and compared with simulated data. In particular, we illustrate the effectiveness of a hybrid method of the two EnergyPlus modeling approaches, which yields more realistic zone temperature dynamics, especially when the zone is conditioned with heat pump systems with on/off cycling.

Chen, Zhelun↗

The crystal structure of TlMgCl 3 from 290 K to 725 K

The title compound, thallium magnesium trichloride, has been identified as a scintillator with both moderate gamma-stopping power and moderate light yield. Knowledge of its crystal structure is needed for further development. This work determines the crystal structure of TlMgCl 3 to be hexa­gonal P6 3 /mmc (No. 194) and isostructural with RbMgCl 3 , contrary to previously reported data. This structure was obtained by single-crystal X-ray diffraction and was further confirmed by neutron diffraction measurements. Extending neutron diffraction measurements to high temperature, the data show that TlMgCl 3 maintains this crystal structure from 290 K up through 725 K, approaching the melting point of 770 K. Anisotropic thermal expansion coefficients increase over this temperature range, from 31 to 38 × 10 –6 K –1 along the a axis and from 19 to 34 × 10 –6 K –1 along the c axis.

36 MATERIALS SCIENCE↗

Land surface temperature measurements from EOS MODIS data

A significant progress has been made in TIR instrumentation which is required to establish the spectral BRDF/emissivity knowledge base of land-surface materials and to validate the land-surface temperature (LST) algorithms. The SIBRE (spectral Infrared Bidirectional Reflectance and Emissivity) system and a TIR system for measuring spectral directional-hemispherical emissivity have been completed and tested successfully. Optical properties and performance features of key components (including spectrometer, and TIR source) of these systems have been characterized by integrated use of local standards (blackbody and reference plates). The stabilization of the spectrometer performance was improved by a custom designed and built liquid cooling system. Methods and procedures for measuring spectral TIR BRDF and directional-hemispheric emissivity with these two systems have been verified in sample measurements. These TIR instruments have been used in the laboratory and the field, giving very promising results. The measured spectral emissivities of water surface are very close to the calculated values based on well established water refractive index values in published papers. Preliminary results show that the TIR instruments can be used for validation of the MODIS LST algorithm in homogeneous test sites. The beta-3 version of the MODIS LST software is being prepared for its delivery scheduled in the early second half of this year.

Wan, Zhengming↗

Surface Temperature Anomalies Derived from Night Time ASTER Data Corrected for Solar and Topographic Effects, San Miguel County, Colorado

This map shows areas of anomalous surface temperature in Alamosa and Saguache Counties identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled "very warm modeled surface temperature" are shown in red on the map. Areas that had temperatures between 1o and 2o were considered ASTER modeled "warm modeled surface temperature" are shown in yellow on the map. This map also includes the locations of shallow temperature survey points, locations of springs or wells with favorable geochemistry, faults, transmission lines, and areas of modeled basement weakness "fairways." Note: 'o' is used in this description to represent lowercase sigma.

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