Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Virtual temperature”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Quantification and Mitigation of Long-Term Impacts of Urbanization and Climate Change in the Tropical Coastal City of San Juan, Puerto Rico

Urbanization, along with other cases of land cover and land use changes, has significant climate impacts in tropical regions with the added complexity of occurring within the context of global warming. The individual and combined effects of these two factors on the surface energy balance of a tropical city are investigated by use of an integrated atmospheric modeling approach, taking the San Juan Metropolitan Area (SJMA), Puerto Rico as the test case. To achieve this goal, an ensemble of climate and weather simulations is performed, with the climate scenarios combining urban development and sprawl with regional climate change over the past 50 years, and the short-term simulations designed to test the sensitivity to different urban vegetation configurations as mitigating alternatives. As indicator of change, we use the thermal response number (TRN), which is a measure of the sensible heating to the thermal storage of a surface or region, and the Bowen ratio, which is defined as the ratio of sensible to latent heat fluxes. The TRN of the area occupied by the SJMA has decreased as a consequence of replacing the low land coastal plain vegetation with man made materials, indicating that it takes less energy to raise the surface temperature of the urban area, whereas the TRN of forested regions has remained virtually unchanged. The global warming signal also has effects on the thermal response of the SJMA, where dryer current conditions generate lower TRN values. Differences due to global warming are more evident in the Bowen ratio pattern, mostly associated with the drier present conditions observed and its effects on sensible and latent heat fluxes. In terms of testing different mitigation strategies, the short-term simulations show that the urban area is more efficient in partitioning surface energy balance terms when green roofs are specified, as opposed to including vegetation inside the urban core.

Comarazamy, Daniel↗
NASA NTRS1993

A technique for computation of noise temperature due to a beam waveguide shroud

Direct analytical computation of the noise temperature of real beam waveguide (BWG) systems, including all mirrors and the surrounding shroud, is an extremely complex problem and virtually impossible to achieve. Yet the DSN antennas are required to be ultra low-noise in order to be effective, and a reasonably accurate prediction is essential. This article presents a relatively simple technique to compute a real BWG system noise temperature by combining analytical techniques with data from experimental tests. Specific expressions and parameters for X-band (8.45-GHz) BWG noise computation are obtained for DSS 13 and DSS 24, now under construction. These expressions are also valid for various conditions of the BWG feed systems, including horn sizes and positions, and mirror sizes, curvatures, and positions. Parameters for S- and Ka-bands (2.3 and 32.0 GHz) have not been determined; however, those can be obtained following the same procedure as for X-band.

Veruttipong, W.↗
NASA NTRS2014

A Revised Calibration Function and Results for the Phoenix Mission TECP Relative Humidity Sensor

The original calibration function of the R(sub H) sensor on the Phoenix Thermal and Electrical Conductivity Sensor (TECP) has been revised in order to extend the range of the valid calibration, and to improve accuracy. The original function returned non-physical R(sub H) values at the lowest temperatures. To resolve this, and because the original calibration was performed against a pair of hygrometers that measured frost point (T(sub f)), the revised calibration equation is also cast in terms of frost point. Because of the complexity of maintaining very low temperatures and high R(sub H) in the laboratory, no calibration data exists at T is greater than 203K. However, sensor response during the mission was smooth and continuous down to 181 K. Therefore we have opted to include flight data in the calibration data set; selection was limited to data acquired during periods when the atmosphere is known to have been saturated. T(sub f) remained below 210 K throughout the mission(P is greater than 0.75 Pa). R(sub H), conversely, ranged from 1 to well under 0.01 diurnally, due to approximately 50 K temperature variations. To first order, both vapor pressure and its variance are greater during daylight hours. Variance in overnight humidity is almost entirely explained by temperature, while atmospheric turbulence contributes substantial variance to daytime humidity. Likewise, data gathered with the TECP aloft reflect higher H2O abundances than at the surface, as well as greater variance. There is evidence for saturation of the atmosphere overnight throughout much of the mission. In virtually every overnight observation, once the atmosphere cooled to T(sub f), water vapor begins to decrease, and tracks air temperature. There is no evidence for substantial decreases in water vapor prior to saturation, as expected for adsorptive exchange. Likewise, there is no evidence of local control of vapor by phases such as perchlorate hydrates hydrated minerals. The daytime average H2O pressure does not change substantially over the course of the mission, although the H2O column abundance varies by a factor of 2. Column abundances calculated from TECP data are lower than orbital measurements if one assumes that H2O is uniformly mixed through a single scale height. These results argue that the vertical distribution of H2O begins to change well in advance of surface concentrations as northern autumn approaches.

Phoenix Thermal and Electrical Conductivity Sensor↗
NASA NTRS1972

Microbial degradation of parathion

An organism capable of utilizing parathion as the sole carbon and energy source was isolated by enrichment culture techniques. The bacterium was characterized and tentatively classified as Pseudomonas aeruginosa. A pH of 7.0 - 7.5 and temperature of 30 C were found to be optimum for the consumption of parathion. Virtually no oxygen utilization was observed with resting cell suspensions when nonsolubilized parathion was employed. The use of ethanol as solvent for parathion in resting cell studies or preincubation of cells in ethanol obviated this problem and rapid parathion oxidation was demonstrable. Approximately 80% of the parathion consumed by resting cells was present terminally as carbon dioxide. Permeability of the cell to parathion or its metabolites was contingent upon the use of ethanol as either solvent or denaturant. Metabolites were tentatively identified by thin layer chromatography.

Gibson, W. L.↗
NASA NTRS1974

Ion heating and containment in the NASA Lewis bumpy torus plasma

Experimental observations have been made during steady state operation of a torus experiment at input powers up to 150 kilowatts in deuterium and helium gas. The steady state ion heating method utilizes a modified Penning discharge operated in a bumpy torus confinement geometry. The bumpy torus plasma is acted upon by a combination of strong electric and magnetic fields. In a deuterium plasma, electron temperatures from 14 to 140 electron volts and ion kinetic temperatures from 160 to 1785 electron volts were observed. At least two distinct operating regimes exist, each of which is associated with a characteristic range of background gas pressure and electron temperature. Experimental data show that the average ion residence time in the plasma is virtually independent of magnetic field strength.

Roth, J. R.↗
NASA NTRS1976

Characteristics of the NASA Lewis Bumpy Torus plasma generated with positive applied potentials

Experimental observations have been made during steady-state operation of the NASA Lewis Bumpy Torus experiment at input powers up to 150 kW in deuterium and helium gas, and with positive potentials applied to the midplane electrodes. This steady-state ion heating method utilizes a modified Penning discharge operated in a bumpy torus confinement geometry such that the plasma is acted upon by a combination of strong electric and magnetic fields. Experimental investigation of a deuterium plasma revealed electron temperatures from 14 to 140 eV and ion kinetic temperatures from 160 to 1785 eV. At least two distinct modes of operation exist, each of which is associated with a characteristic range of background pressure and electron temperature. Experimental data show that the average ion residence time in the plasma is virtually independent of the magnetic field strength.

Roth, J. R.↗
NASA NTRS1982

Low noise buffer amplifiers and buffered phase comparators for precise time and frequency measurement and distribution

Extremely low noise, high performance, wideband buffer amplifiers and buffered phase comparators were developed. These buffer amplifiers are designed to distribute reference frequencies from 30 KHz to 45 MHz from a hydrogen maser without degrading the hydrogen maser's performance. The buffered phase comparators are designed to intercompare the phase of state of the art hydrogen masers without adding any significant measurement system noise. These devices have a 27 femtosecond phase stability floor and are stable to better than one picosecond for long periods of time. Their temperature coefficient is less than one picosecond per degree C, and they have shown virtually no voltage coefficients.

Eichinger, R. A.↗
NASA NTRS1987

On requirements for a satellite mission to measure tropical rainfall

Tropical rainfall data are crucial in determining the role of tropical latent heating in driving the circulation of the global atmosphere. Also, the data are particularly important for testing the realism of climate models, and their ability to simulate and predict climate accurately on the seasonal time scale. Other scientific issues such as the effects of El Nino on climate could be addressed with a reliable, extended time series of tropical rainfall observations. A passive microwave sensor is planned to provide information on the integrated column precipitation content, its areal distribution, and its intensity. An active microwave sensor (radar) will define the layer depth of the precipitation and provide information about the intensity of rain reaching the surface, the key to determining the latent heat input to the atmosphere. A visible/infrared sensor will provide very high resolution information on cloud coverage, type, and top temperatures and also serve as the link between these data and the long and virtually continuous coverage by the geosynchronous meteorological satellites. The unique combination of sensor wavelengths, coverages, and resolving capabilities together with the low-altitude, non-Sun synchronous orbit provide a sampling capability that should yield monthly precipitation amounts to a reasonable accuracy over a 500- by 500-km grid.

Thiele, Otto W.↗
NASA NTRS1990

Extensional and compressional instabilities in icy satellite lithospheres

The plausibility of invoking a lithospheric instability mechanism to account for the grooved terrains on Ganymede, Encedalus, and Miranda is presently evaluated in light of the combination of a simple mechanical model of planetary lithospheres and asthenospheres with recent experimental data for the brittle and ductile deformation of ice. For Ganymede, high surface gravity and warm temperatures render the achievement of an instability sufficiently great for the observed topographic relief virtually impossible; an instability of sufficient strength, however, may be able to develop on such smaller, colder bodies as Encedalus and Miranda.

Herrick, David L.↗
NASA NTRSDate not supplied

GeoNEX-ML: A Machine Learning System for Geostationary Satellite Imagery

Improved capabilities of earth monitoring satellites are enabling a wide range of studies on the environmental effects of climate change, often leveraging the recent advancements in machine learning. At the same time, the new capabilities, including higher spatial resolution and temporal frequency, are expanding the amount of data generated at exponential rates. Further, a large majority of archived datasets generated by scientific processing is never used. This motivates the development of an efficient machine learning system for end-to-end processing of multi-level satellite datasets, from level 1 top of atmosphere observations to user friendly environmental variables of interest. Using current generation geostationary satellites GOES-16/17 (NOAA/NASA), Himawari-8/9 (JAXA), and GK-2A (Korea), we present an interchangeable set of machine models to perform spectral adjustment, physical model emulation, LEO-GEO emulation, and optical flow in a high performance computing environment. We use these tools to generate consistent virtual observations across sensors, perform atmospheric correction and cloud detection, and estimate land surface temperature and atmospheric winds. This approach aims to improve the robustness of remotely sensed data processing by learning from diverse sets of observations while enabling near real-time and on-demand capabilities.

Geostationary satellites↗
NASA NTRSDate not supplied

GeoNEX-ML: A Machine Learning System for Earth Observations

Improved capabilities of earth monitoring satellites are enabling a wide range of studies on the environmental effects of climate change, often leveraging the recent advancements in machine learning. At the same time, the new capabilities, including higher spatial resolution and temporal frequency, are expanding the amount of data generated at exponential rates. At the NASA Earth eXchange (NEX), we build deep learning methods to learn from cross sensor satellite-based Earth observations for generating new datasets with efficient processing techniques. Using current generation geostationary satellites on NEX, we present an interchangeable set of machine models to perform spectral adjustment, physical model emulation, LEO-GEO emulation, and optical flow. These tools are used to generate consistent virtual observations across sensors, perform atmospheric correction and cloud detection, and estimate land surface temperature and atmospheric winds. This approach aims to improve the robustness of remotely sensed data processing by learning from diverse sets of observations while enabling near real-time and on-demand capabilities.

Geostationary↗
NASA NTRSDate not supplied

Process Modeling of Woven Textiles

Woven polymer matrix composites offer numerous advantages over traditional unidirectional laminates. Processing conditions affect residual stress that builds up during manufacturing. This work proposes the analysis of three curing parameters on the local residual stress distribution of a plain weave textile architecture, including chemical shrinkage, the temperature cool down, and the evolution of matrix properties as a function of curing. Virtual curing is applied to the inter-tow matrix material of the plain weave Repeating Unit Cell (RUC) modeled in TexGen. Curing is implemented through user-written subroutines within the commercial software suite Abaqus. Results from process modeling are compared with a linear-elastic thermal cool down in Abaqus. A boundary conditions study is also conducted to compare the residual stress build up predicted by Flat(FBCs) and Periodic Boundary Conditions (PBCs). Preliminary results indicate that a thermal cool down over-estimates the end-of-cure stresses in the matrix. Process modeling is conducted with and without chemical shrinkage, then compared with a thermal cool down. Results show that 11.32% of the final stress state is due to chemical shrinkage. Material property evolution during curing also has a non-negligible effect on the end stress.

woven composites↗
NASA NTRSDate not supplied

Atmospheric winds with deep optical flow

Improved capabilities of earth monitoring satellites are enabling a wide range of studies on the environmental effects of climate change, often leveraging the recent advancements in machine learning. At the same time, the new capabilities, including higher spatial resolution and temporal frequency, are expanding the amount of data generated at exponential rates. At the NASA Earth eXchange (NEX), we build deep learning methods to learn from cross sensor satellite-based Earth observations for generating new datasets with efficient processing techniques. Using current generation geostationary satellites on NEX, we present an interchangeable set of machine models to perform spectral adjustment, physical model emulation, LEO-GEO emulation, and optical flow. These tools are used to generate consistent virtual observations across sensors, perform atmospheric correction and cloud detection, and estimate land surface temperature and atmospheric winds. This approach aims to improve the robustness of remotely sensed data processing by learning from diverse sets of observations while enabling near real-time and on-demand capabilities.

Atmospheric winds↗
DOE OSTI2026

Recent advances in plasma control and physics research in the Large Helical Device

The Large Helical Device (LHD), the largest superconducting helical system in the world, is equipped with advanced heating and diagnostic tools, facilitating plasma control and physics research. Data assimilation was employed for electron temperature control using a real-time Thomson scattering system and real time prediction code. A virtual LHD environment enabled visualization of escaping high-energy tritium ions and demonstrated that these ions impact the rear side of the divertor plate. Pioneering results crucial to plasma control have also been achieved. Real-time wall conditioning using Lithium granule dropping improved bulk ion energy and particle transport while simultaneously enhancing the heavy impurity transport. Progress has also been made in the investigation of turbulence-driven transport. At the confinement bifurcation, ion-scale turbulence decreased, while electron-scale turbulence increased. A change in the anisotropy of turbulent eddies was also observed at the confinement bifurcation. Coexistence of local and non-local turbulence was identified in electron-scale turbulence. Non-local turbulence exhibited the rapid spatial propagation of perturbations throughout the plasma, while local turbulence followed the temperature gradient. A transition between drift-wave turbulence and magnetohydrodynamics (MHD) turbulence was observed with the turbulence minimized at the transition condition. Machine learning analysis was employed to evaluate the temperate and density conditions of this turbulence transition. Then, real-time control of fueling and heating was applied to maintain the turbulence transition condition, improving the energy confinement enhancement factor by 20%. In addition, evidence was obtained for collisionless ion heating by energetic-ion-driven geodesic acoustic modes and MHD bursts. These achievements represent unique contributions to the development of fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1994

Coronal temperatures of unusually active K-dwarf binary systems

We report the results of a ROSAT pointed study of 4 BY Dra systems. Good quality pulse-height spectra are available from all four systems. Except for a required interstellar absorption component in HD 319139, the four systems have remarkably similar x-ray spectra; the two systems BD +22deg.669 and BD +23deg.635 look virtually identical in x rays. Analysis of the 4 x-ray spectra reveals that, in all cases, a single-temperature hot plasma (RS or Mewe) spectra is inadequate to fit the data, and two temperatures are required. We present examples of fitted pulse-height spectra and chi squared contours in kT(sub 1)-kT(sub 2) space.

Stern, Robert A.↗
NASA NTRS2004

Virtual Sensors: Using Data Mining to Efficiently Estimate Spectra

Detecting clouds within a satellite image is essential for retrieving surface geophysical parameters, such as albedo and temperature, from optical and thermal imagery because the retrieval methods tend to be valid for clear skies only. Thus, routine satellite data processing requires reliable automated cloud detection algorithms that are applicable to many surface types. Unfortunately, cloud detection over snow and ice is difficult due to the lack of spectral contrast between clouds and snow. Snow and clouds are both highly reflective in the visible wavelen,ats and often show little contrast in the thermal Infrared. However, at 1.6 microns, the spectral signatures of snow and clouds differ enough to allow improved snow/ice/cloud discrimination. The recent Terra and Aqua Moderate Resolution Imaging Spectro-Radiometer (MODIS) sensors have a channel (channel 6) at 1.6 microns. Presently the most comprehensive, long-term information on surface albedo and temperature over snow- and ice-covered surfaces comes from the Advanced Very High Resolution Radiometer ( AVHRR) sensor that has been providing imagery since July 1981. The earlier AVHRR sensors (e.g. AVHRR/2) did not however have a channel designed for discriminating clouds from snow, such as the 1.6 micron channel available on the more recent AVHRR/3 or the MODIS sensors. In the absence of the 1.6 micron channel, the AVHRR Polar Pathfinder (APP) product performs cloud detection using a combination of time-series analysis and multispectral threshold tests based on the satellite's measuring channels to produce a cloud mask. The method has been found to work reasonably well over sea ice, but not so well over the ice sheets. Thus, improving the cloud mask in the APP dataset would be extremely helpful toward increasing the accuracy of the albedo and temperature retrievals, as well as extending the time-series of albedo and temperature retrievals from the more recent sensors to the historical ones. In this work, we use data mining methods to construct a model of MODIS channel 6 as a function of other channels that are common to both MODIS and AVHRR. The idea is to use the model to generate the equivalent of MODIS channel 6 for AVHRR as a function of the AVHRR equivalents to MODIS channels. We call this a Virtual Sensor because it predicts unmeasured spectra. The goal is to use this virtual channel 6. to yield a cloud mask superior to what is currently used in APP . Our results show that several data mining methods such as multilayer perceptrons (MLPs), ensemble methods (e.g., bagging), and kernel methods (e.g., support vector machines) generate channel 6 for unseen MODIS images with high accuracy. Because the true channel 6 is not available for AVHRR images, we qualitatively assess the virtual channel 6 for several AVHRR images.

Srivastava, Ashok↗
NASA NTRS2006

Diurnal Variability of Vertical Structure from a TRMM Passive Microwave "Virtual Radar" Retrieval

Robust description of the diurnal cycle from TRMM observations is complicated by the limitations of Low Earth Orbit (LEO) sampling; from a 'climatological' perspective, sufficient sampling must exist to control for both spatial and seasonal variability, before tackling an additional diurnal component (e.g., with 8 additional 3-hourly or 24 1-hourly bins). For documentation of vertical structure, the narrow sample swath of the TRMM Precipitation Radar limits the resolution of any of these components. A neural-network based 'virtual radar" retrieval has been trained and internally validated, using multifrequency / multipolarization passive microwave(TM1) brightness temperatures and textures parameters and lightning (LIS) observations, as inputs, and PR volumetric reflectivity as targets (outputs). By training the algorithms (essentially highly multivariate, nonlinear regressions) on a very large sample of high-quality co-located data from the center of the TRMM swath, 3D radar reflectivity and derived parameters (VIL, IWC, Echo Tops, etc.) can be retrieved across the entire TMI swath, good to 8-9% over the dynamic range of parameters. As a step in the retrieval (and as an output of the process), each TMI multifrequency pixel (at 85 GHz resolution) is classified into one of the 25 archetypal radar profile vertical structure "types", previously identified using cluster analysis. The dynamic range of retrieved vertical structure appears to have higher fidelity than the current (Version 6) experimental GPROF hydrometeor vertical structure retrievals. This is attributable to correct representation of the prior probabilities of vertical structure variability in the neural network training data, unlike the GPROF cloud-resolving model training dataset used in the V6 algorithms. The LIS lightning inputs are supplementary inputs, and a separate offline neural network has been trained to impute (predict) LIS lightning from passive-microwave-only data. The virtual radar retrieval is thus, in principle, extensible to Aqua/AMSR-E and NPOESS/CMIS passive microwave instruments. The virtual radar approach yields a threefold increase in effective sampling from the mission, albeit of lower-quality "retrieved" data, reducing the variance of local estimates by one third (or the standard deviation by-0.57). In this talk, the variance reduction is leveraged to more finely resolve global diurnal variability in both space and time (local hour).

Boccippio, Dennis J.↗
NASA NTRS1984

Recent developments in semiconductor research

Recent findings drawn from various laboratories focused toward a new understanding of the nature of crystal growth and how impurities are incorporated or excluded from the lattice were considered. From these findings a heuristic approach is given for improving the uniformity and charge carrier concentration of thin semiconductor films. Such improvement is considered essential to achieve respectable yield on large scale integrated circuits. A tentative conclusion is drawn which indicates that if the host compound crystal reactants are provided to the growing crystal surface in a reasonably stoichiometric manner, it is virtually impossible to include impurities into a growing crystal surface held at a sufficiently low temperature; impurities are incorporated into the crystal by gettering action of crystal defects located one and two monlayers beneath the growing surface. Devices in 3-5 semiconductors based on heterojunctions and two dimensional electron gases are noted and reliability concerns are voiced. Alternatives and novel device structures such as truly single crystal high quality silicon on insulator and beta silicon carbide devices are presented.

Yoder, M. N.↗