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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Improved Surface and Tropospheric Temperatures Determined Using Only Shortwave Channels: The AIRS Science Team Version-6 Retrieval Algorithm

The Goddard DISC has generated products derived from AIRS/AMSU-A observations, starting from September 2002 when the AIRS instrument became stable, using the AIRS Science Team Version-5 retrieval algorithm. The AIRS Science Team Version-6 retrieval algorithm will be finalized in September 2011. This paper describes some of the significant improvements contained in the Version-6 retrieval algorithm, compared to that used in Version-5, with an emphasis on the improvement of atmospheric temperature profiles, ocean and land surface skin temperatures, and ocean and land surface spectral emissivities. AIRS contains 2378 spectral channels covering portions of the spectral region 650 cm(sup -1) (15.38 micrometers) - 2665 cm(sup -1) (3.752 micrometers). These spectral regions contain significant absorption features from two CO2 absorption bands, the 15 micrometers (longwave) CO2 band, and the 4.3 micrometers (shortwave) CO2 absorption band. There are also two atmospheric window regions, the 12 micrometer - 8 micrometer (longwave) window, and the 4.17 micrometer - 3.75 micrometer (shortwave) window. Historically, determination of surface and atmospheric temperatures from satellite observations was performed using primarily observations in the longwave window and CO2 absorption regions. According to cloud clearing theory, more accurate soundings of both surface skin and atmospheric temperatures can be obtained under partial cloud cover conditions if one uses observations in longwave channels to determine coefficients which generate cloud cleared radiances R(sup ^)(sub i) for all channels, and uses R(sup ^)(sub i) only from shortwave channels in the determination of surface and atmospheric temperatures. This procedure is now being used in the AIRS Version-6 Retrieval Algorithm. Results are presented for both daytime and nighttime conditions showing improved Version-6 surface and atmospheric soundings under partial cloud cover.

Susskind, Joel↗
DOE OSTI2020

Multiplexable high-temperature stable and low-loss intrinsic Fabry-Perot in-fiber sensors through nanograting engineering

This paper presents a method of using femtosecond laser inscribed nanograting as low-loss– and high-temperature–stable in-fiber reflectors. By introducing a pair of nanograting inside the core of a single-mode optical fiber, an intrinsic Fabry-Perot interferometer can be created for high-temperature sensing applications. The morphology of the nanograting inscribed in fiber cores was engineered by tuning the fabrication conditions to achieve a high fringe visibility of 0.49 and low insertion loss of 0.002 dB per sensor. Using a white light interferometry demodulation algorithm, we demonstrate the temperature sensitivity, cross-talk, and spatial multiplexability of sensor arrays. Both the sensor performance and stability were studied from room temperature to 1000°C with cyclic heating and cooling. Our results demonstrate a femtosecond direct laser writing technique capable of producing highly multiplexable in-fiber intrinsic Fabry-Perot interferometer sensor devices with high fringe contrast, high sensitivity, and low-loss for application in harsh environmental conditions.

Wang, Mohan (ORCID:0000000166784993)↗
NASA NTRS1989

IUE spectra of HD 269665 (Sk -68 deg 110), a hot subdwarf in the direction of the Large Magellanic Cloud

Comparison of high- and low-resolution IUE spectra of HD 269665 (Sanduleak -68 deg 110) show that the star is a subdwarf with a temperature in the range 30,000-50,000 K. The visual spectrum shows Balmer lines and weak He II 4686 A lines. Balmer-line width and a fit of the UV-visual flux distribution using the Blackwell-Shallis (1977) algorithm yields an effective temperature between 30,000 and 38,000 K and log g = 5-6. A table is presented of photospheric UV spectral lines in HD 269665. The radial velocity of the star is found to be 5.8 + or - 0.5 km/s.

Hill, Robert S.↗
NASA NTRS2015

Comparison of Ozone Retrievals from the Pandora Spectrometer System and Dobson Spectrophotometer in Boulder, Colorado

A comparison of retrieved total column ozone (TCO) amounts between the Pandora #34 spectrometer system and the Dobson #061 spectrophotometer from direct-sun observations was performed on the roof of the Boulder, Colorado, NOAA building. This paper, part of an ongoing study, covers a 1-year period starting on 17 December 2013. Both the standard Dobson and Pandora TCO retrievals required a correction, TCO(sub corr) = TCO (1 + C(T)), using a monthly varying effective ozone temperature, T(sub E), derived from a temperature and ozone profile climatology. The correction is used to remove a seasonal difference caused by using a fixed temperature in each retrieval algorithm. The respective corrections C(T(sub E)) are C(sub Pandora) = 0.00333(T(sub E) - 225) and C(sub Dobson) = -0.0013(T(sub E) - 226.7) per degree K. After the applied corrections removed most of the seasonal retrieval dependence on ozone temperature, TCO agreement between the instruments was within 1% for clear-sky conditions. For clear-sky observations, both co-located instruments tracked the day-to-day variation in total column ozone amounts with a correlation of r(exp 2) = 0.97 and an average offset of 1.1 +/- 5.8 DU. In addition, the Pandora TCO data showed 0.3% annual average agreement with satellite overpass data from AURA/OMI (Ozone Monitoring Instrument) and 1% annual average offset with Suomi-NPP/OMPS (Suomi National Polar-orbiting Partnership, the nadir viewing portion of the Ozone Mapper Profiler Suite).

Herman, J.↗
NASA NTRS2021

Assessing Disaggregated SMAP Soil Moisture Products in the United States

A soil moisture (SM) disaggregation algorithm based on thermal inertia (TI) theory was implemented to downscale the Soil Moisture Active Passive (SMAP) Enhanced product(SPL2SMPE) from 9 km to 1 km over the continental United States. The algorithm applies land surface temperature and normalized difference vegetation index from Moderate Resolution Imaging Spectroradiometer (MODIS) at higher spatial resolution to estimate relative soil wetness within a coarse SMAP grid -this MODIS-derived relative wetness is then used to produce the downscaled SMAP SM. Results from the algorithm were evaluated in terms of their spatiotemporal coverage and accuracy using in situ measurements from SMAP Core Validation Sites (CVS), the US Department of Agriculture Soil Climate Analysis Network (USDA-SCAN), and the National Oceanic and Atmospheric Administration Climate Reference Network(NOAA-CRN). Results were also compared with the baselineSPL2SMPE and the SMAP/Sentinel-1 (SPL2SMAPS) 1kmproduct. Overall, the unbiased root mean square error (ubRMSE)of the disaggregated SM at the CVS using the TI approach is approximately 0.04 m3=m3, which is the SMAP mission requirement for the baseline products. The TI approach out performs the SMAP/Sentinel SL2SMAPS 1km product by approximately0.02 m3=m3. Over the agriculture/crop areas from SCAN and CRN sparse network stations, the TI approach exhibits better ubRMSE compared to SPL2SMPE andSPL2SMAPS byabout0.01 and 0.02 m3=m3, indicating its advantage in these areas. However, a drawback of this approach is that there are data gaps due to cloud cover as optical sensors cannot have a clear view of the land surface.

Soil moisture↗
DOE OSTI2024

Phase-Field Model Incorporating Large Inelastic Strain with Application to the Oxidation of High-Temperature Coating Systems

Structural metallic and ceramic materials at high temperatures often suffer from creep, fatigue and oxidation, which typically involves local large inelastic strain. The large strain is usually approached by Lagrangian-description-based finite deformation theory. Here we develop an efficient, Eulerian-description-based, Incremental Realization of Inelastic Deformation (IRID) algorithm to deal with large inelastic strain with small elastic strain. We apply this algorithm to simulate high temperature oxidation with severe volume expansion using a phase-field approach. The oxidation and deformation of bond coat can lead to spallation and failure of the thermal barrier coatings (TBC) and environmental barrier coatings (EBC), which is a critical concern in design of these coatings. We simulate the growth of thermally grown oxide (TGO) in these coating systems, with phase transformations and microstructure evolution incorporated. The simulation results are compared with relevant experimental reports in the literature.

Cheng, Tianle↗
NASA NTRS2023

Integrating NASA Aqua AIRS in a Real-Time NUCAPS Science-to-Applications System to Support Severe Weather Forecasting

In recent years, National Oceanic and Atmospheric Administration (NOAA) Unique Combined Atmospheric Processing System (NUCAPS) hyperspectral infrared satellite sounding retrievals derived from Joint Polar Satellite System (JPSS) polar-orbiting satellites have been documented as observations that add value to weather forecasting applications. NUCAPS is currently the operational algorithm delivering JPSS satellite sounding retrievals to the NOAA National Weather Service (NWS) and is based on the heritage Atmospheric Infrared Sounder (AIRS) Science Team algorithm for processing vertical temperature, moisture, and trace gas retrievals. For the Special Collection on “Twenty Years of Observations from AIRS,” we highlight the methodology we implemented to develop a prototype science-to-applications system to enable real-time processing of AIRS satellite sounding retrievals through the NUCAPS algorithm (i.e., NUCAPS-Aqua) to support weather forecasting applications. The addition of NUCAPS-Aqua to experimental real-time pathways alongside operational JPSS NUCAPS soundings, facilitated assessment of NUCAPS-Aqua at the 2022 Hazardous Weather Testbed (HWT) Spring Experiment. Development of NUCAPS-Aqua described in this technical report includes preservation of microwave observations and calculation of a-priori regression coefficients. Additionally, the real-time processing and challenges with implementing a science-to-applications system are discussed. Two illustrative pre-convective forecasting examples analyzed by NWS forecasters during the 2022 HWT Spring Experiment are highlighted to demonstrate the benefit of NUCAPS-Aqua as (a) special afternoon soundings, (b) an additional observation to assess temporal trends using multiple satellites, and (c) a complement to observational and model analysis.

remote sensing↗
NASA NTRS1986

Remote sensing of land-surface temperature from HIRS/MSU data

A relaxation algorithm which permits meteorological parameters to be obtained from satellite data, without a priori assumptions about the properties of the other unknowns in the field of view, was developed. Atmospheric temperature profiles, atmospheric humidity, cloud cover, cloud top height, cloud top temperature, sea-surface temperature, land-surface temperature, snow cover, and ice cover are derived. Simultaneous determination of atmospheric and surface thermal structure and the cloud distribution provides information on heat sources and sinks, storage rates, and transport phenomena in the atmosphere. Such information is critical in determining the driving mechanisms for motions in the atmosphere and oceans and in improving numerical weather prediction.

Chahine, M. T.↗
DOE OSTI2022

Occupancy-Based Controls for an All-Electric Residential Community in a Cold Climate

In residential buildings, rapid improvements in sensors, communication, and information technology have enabled occupancy-based building controls. These controls utilize occupancy information and modify the operation of the heating, ventilation, and air-conditioning (HVAC) system to minimize excess HVAC energy use, especially when the building is unoccupied. This reduces the total building energy consumption and utility bills while maintaining thermal comfort. In this paper, we present two novel occupancy-driven controls - reactive control and predictive control - and compare their performance. We model an all-electric residential community based on a 27- home community in Basalt, Colorado, in the United States. We simulated various scenarios, considering different temperature setback and control algorithms, to analyze the community-scale impact of these occupancy-based controls. The results show that total HVAC energy savings in a building ranges from 1%- 20% compared to the baseline scenario without occupancy-based controls. The energy-saving potential is highly correlated with the occupancy pattern and temperature setback in the building.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2022

Occupancy-Based Controls for an All-Electric Residential Community in a Cold Climate: Preprint

In residential buildings, rapid improvements in sensors, communication, and information technology have enabled occupancy-based building controls. These controls utilize occupancy information and modify the operation of the heating, ventilation, and air-conditioning (HVAC) system to minimize excess HVAC energy use, especially when the building is unoccupied. This reduces the total building energy consumption and utility bills while maintaining thermal comfort. In this paper, we present two novel occupancy-driven controls - reactive control and predictive control - and compare their performance. We model an all-electric residential community based on a 27- home community in Basalt, Colorado, in the United States. We simulated various scenarios, considering different temperature setback and control algorithms, to analyze the community-scale impact of these occupancy-based controls. The results show that total HVAC energy savings in a building ranges from 1%- 20% compared to the baseline scenario without occupancy-based controls. The energy-saving potential is highly correlated with the occupancy pattern and temperature setback in the building.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2025

Autonomous Aerosol and Plasma Co‐Jet Printing of Metallic Devices at Ambient Temperature

Abstract Additive manufacturing of metallic materials holds the potential to revolutionize the fabrication of functional devices unattainable via traditional methods. Despite recent advancements, printing metallic materials typically requires thermal processing at elevated temperatures to form dense structures with desired properties, which presents a major challenge for direct printing and integration with temperature‐sensitive materials. Herein, a unique co‐jet printing (CJP) method is reported integrating an aerosol jet and a non‐thermal, atmospheric pressure plasma jet to enable concurrent aerosol deposition of metal nanoparticle inks and in situ sintering at ambient temperature. A machine learning algorithm is integrated with the CJP to perform real‐time defect detection and autonomous correction, enhancing the yield of printed films with high electrical conductivity from 44% to 94%. Concurrent printing and sintering eliminate the need for post‐printing processing, reducing the overall manufacturing time by multiple folds depending on product size. CJP enables direct printing of functional devices on a variety of temperature‐sensitive materials including biological materials. Direct printing of hydration sensors on living plant leaves is demonstrated for long‐duration monitoring of hydration level in the plant. The versatile CJP method opens tremendous opportunities to harmoniously integrate abiotic and biotic materials for emerging applications in wearable/implantable devices and biohybrid systems.

Du, Yipu [Department of Aerospace and Mechanical E↗
DOE OSTI2026

Virtual refrigerant charge sensor for variable-speed heat pumps based on feature selection

The refrigerant charge level in heat pump systems significantly impacts their energy efficiency. Virtual refrigerant charge (VRC) sensing technology has been comprehensively investigated and well-established due to its lower cost compared to physical sensors. However, the previous VRC research often relied on expert judgment and physical reasoning for their variable selection, which can potentially select redundant (or highly correlated) or insignificant features, and it is also primarily focused on single-speed systems. To address these challenges, this study proposes a VRC algorithm for variable-speed heat pumps that selects features through a rigorous feature selection method in combination with physical insights. We also propose a piecewise linear model structure segmented by subcooling temperature to accurately predict charge levels, particularly when subcooling temperatures are substantially low. The proposed algorithm was evaluated using experimental data of a residential R410A heat pump, and the performance was compared with two baseline VRC algorithms. The results are: (1) The proposed algorithm outperforms for the case with subcooling temperature less than 1 °C. (2) The proposed algorithm achieves a tested mean absolute percentage error (MAPE) of 4.23%, and improves the overall accuracy for cooling conditions by approximately 60%, compared with the two baseline algorithms. (3) The proposed algorithm uses two fewer features and improves the accuracy for undercharge cooling conditions by 68.0%, compared with baseline algorithm 2. These improvements enhance prediction accuracy and prevent overfitting, providing a more reliable refrigerant charge level prediction and helping improve the heat pump energy efficiency.

Liang, Chenjiyu↗
NASA NTRS1994

Surface-induced brightness temperature variations and their effects on detecting thin cirrus clouds using IR emission channels in the 8-12 microns region

A method for detecting cirrus clouds in terms of brightness temperature differences between narrowbands at 8, 11, and 12 microns has been proposed by Ackerman et al. In this method, the variation of emissivity with wavelength for different surface targets was not taken into consideration. Based on state-of-the-art laboratory measurements of reflectance spectra of terrestrial materials by Salisbury and D'Aria, it is found that the brightness temperature differences between the 8- and 11-microns bands for soils, rocks, and minerals, and dry vegetation can vary between approximately -8 and +8 K due solely to surface emissivity variations. The large brightness temperature differences are sufficient to cause false detection of cirrus clouds from remote sensing data acquired over certain surface targets using the 8-11-12-microns method directly. It is suggested that the 8-11-12-microns method should be improved to include the surface emissivity effects. In addition, it is recommended that in the future the variation of surface emissivity with wavelength should be taken into account in algorithms for retrieving surface temperatures and low-level atmospheric temperature and water vapor profiles.

Gao, Bo-Cai↗
NASA NTRS1986

Preliminary assessment of soil moisture over vegetation

Modeling of surface energy fluxes was combined with in-situ measurement of surface parameters, specifically the surface sensible heat flux and the substrate soil moisture. A vegetation component was incorporated in the atmospheric/substrate model and subsequently showed that fluxes over vegetation can be very much different than those over bare soil for a given surface-air temperature difference. The temperature signatures measured by a satellite or airborne radiometer should be interpreted in conjunction with surface measurements of modeled parameters. Paradoxically, analyses of the large-scale distribution of soil moisture availability shows that there is a very high correlation between antecedent precipitation and inferred surface moisture availability, even when no specific vegetation parameterization is used in the boundary layer model. Preparatory work was begun in streamlining the present boundary layer model, developing better algorithms for relating surface temperatures to substrate moisture, preparing for participation in the French HAPEX experiment, and analyzing aircraft microwave and radiometric surface temperature data for the 1983 French Beauce experiments.

Carlson, T. N.↗
NASA NTRS2007

Cloudy Sounding and Cloud-Top Height Retrieval From AIRS Alone Single Field-of-View Radiance Measurements

High-spectral resolution measurements from the Atmospheric Infrared Sounder (AIRS) onboard the EOS (Earth Observing System) Aqua satellite provide unique information about atmospheric state, surface and cloud properties. This paper presents an AIRS alone single field-of-view (SFOV) retrieval algorithm to simultaneously retrieve temperature, humidity and ozone profiles under all weather conditions, as well as cloud top pressure (CTP) and cloud optical thickness (COT) under cloudy skies. For optically thick cloud conditions the above-cloud soundings are derived, whereas for clear skies and optically thin cloud conditions the profiles are retrieved from 0.005 hPa down to the earth's surface. Initial validation has been conducted by using the operational MODIS (Moderate Resolution Imaging Spectroradiometer) product, ECMWF (European Center of Medium range Weather Forecasts) analysis fields and radiosonde observations (RAOBs). These inter-comparisons clearly demonstrate the potential of this algorithm to process data from 38 high-spectral infrared (IR) sounder instruments.

Weisz, Elisabeth↗
NASA NTRS1993

Surface-induced brightness temperature variations and their effects on detecting thin cirrus clouds using IR emission channels in the 8-12 micrometer region

A method for detecting cirrus clouds in terms of brightness temperature differences between narrow bands at 8, 11, and 12 mu m has been proposed by Ackerman et al. (1990). In this method, the variation of emissivity with wavelength for different surface targets was not taken into consideration. Based on state-of-the-art laboratory measurements of reflectance spectra of terrestrial materials by Salisbury and D'Aria (1992), we have found that the brightness temperature differences between the 8 and 11 mu m bands for soils, rocks and minerals, and dry vegetation can vary between approximately -8 K and +8 K due solely to surface emissivity variations. We conclude that although the method of Ackerman et al. is useful for detecting cirrus clouds over areas covered by green vegetation, water, and ice, it is less effective for detecting cirrus clouds over areas covered by bare soils, rocks and minerals, and dry vegetation. In addition, we recommend that in future the variation of surface emissivity with wavelength should be taken into account in algorithms for retrieving surface temperatures and low-level atmospheric temperature and water vapor profiles.

Gao, Bo-Cai↗
DOE OSTI2021

HyPerPy (Hydrogen Extraction and Parabolic Trough Plant Performance Models using Python) [SWR-21-53]

The HyPerPy package consists of three scripts: 1) Model for Hydrogen Tracking in Parabolic Trough Power Plants, 2) Model for Receiver Performance, and 3) Model for Hydrogen Extraction Process. The power plant model (1) tracks hydrogen generation and transport within the circulating heat transfer fluid (HTF) of the power plant. This script is a transient, initial value simulation, in which the hydrogen concentration in the circulating HTF is 0 moles per cubic meter everywhere at time 0 seconds. Hydrogen concentration is calculated at discrete locations within the circulating HTF with 4-second time resolution. During each time step, the change in hydrogen concentration due to hydrogen generation and permeation is calculated for each location according to the local HTF temperature, vessel or piping properties, hydrogen concentration and partial pressure. This model predicts hourly hydrogen concentrations for typical operating days in the spring, summer, fall, and winter seasons. Data is used to create hourly mappings of hydrogen concentrations for a typical operating year. The receiver model (2) uses a 1-hour time step to estimate getter loading and annulus pressure. For each time step, the model uses HTF and ambient temperature data to estimate absorber tube, bellows, and getter temperatures for the time step. In addition, the model uses hourly HTF hydrogen concentrations that are generated by the power plant model (1), and annulus hydrogen pressure from the previous time step. With these data, the model calculates the moles of hydrogen permeating across the absorber tube and bellows during the time step. The net change in moles hydrogen is added or subtracted from the getter loading for the previous time step, and the hydrogen pressure is re-calculated based on getter loading and temperature. The model uses this algorithm to simulate hydrogen permeation and loading 24 hours per day, 365 days per year using seasonal temperature data. The model repeats these calculations for 25 years to create a mapping of receiver getter loading and annulus hydrogen pressure for four seasons of each year. The model for hydrogen extraction (3) estimates hydrogen extraction rates for a specific separation module configuration. The rate depends primarily on membrane area, vacuum pump performance, headspace gas flowrate to the membrane, and headspace gas hydrogen partial pressure. This model has two versions. The steady-state version predicts hydrogen extraction rates when the module is operating in separation mode. The dynamic version predicts hydrogen transfer through the membrane when the module is operating in sensor mode. The steady-state version is used with the plant model (1) to predict hydrogen partial pressures in the power plant when the extraction process is operating.

Glatzmaier, Gregory↗
NASA NTRS1993

Mars atmospheric dust properties: A synthesis of Mariner 9, Viking, and Phobos observations

We have modified a doubling-and-adding code to reanalyze the Mariner 9 IRIS spectra of Mars atmospheric dust as well as Viking IRTM EPF sequences in the 7, 9, and 20 micron channels. The code is capable of accurate emission/ absorption/scattering radiative transfer calculations over the 5-30 micron wavelength region for variable dust composition and particle size inputs, and incorporates both the Viking IRTM channel weightings and the Mariner 9 IRIS wavelength resolution for direct comparisons to these datasets. We adopt atmospheric temperature profiles according to the algorithm of Martin (1986) in the case of the Viking IRTM comparisons, and obtained Mariner 9 IRIS temperature retrievals from the 15 micron CO2 band for the case of the IRIS comparisons. We consider palagonite as the primary alternative to the montmorillonite composition of Mars atmospheric dust, based on several considerations. Palagonite absorbs in the ultraviolet and visible wavelength region due to its Fe content. Palagonite is also, in principal, consistent with the observed lack of clays on the Mars surface. Furthermore, palagonite does not display strong, structured absorption near 20 microns as does montmorillonite (in conflict with the IRIS observations). We propose that a palagonite composition with particle sizes roughly one-half that of the Toon et al. (1977) determination provide a much improved model to Mars atmospheric dust. Since palagonite is a common weathering product of terrrestrial basalts, it would not be unreasonable for palagonite to be a major surface component for Mars. The lack of even a minor component of Al-rich clays on the surface of Mars could be consistent with a palagonite composition for Mars dust if the conditions for basalt weathering on Mars were sufficiently anhydrous. Variations in palagonite composition could also lead to the inability of the modeled palagonite to fit the details of the 9 micron absorbtion indicated by the IRIS observations.

Clancy, R. T.↗