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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Millimeter-wave observations of Euclid Deep Field South using the South Pole Telescope: A data release of temperature maps and catalogs

Context. The South Pole Telescope third-generation camera (SPT-3G) has observed over 10,000 square degrees of sky at 95, 150, and 220 GHz (3.3, 2.0, 1.4 mm, respectively) and will significantly overlap the ongoing 14,000 square-degree Euclid Wide Survey. The Euclid collaboration recently released Euclid Deep Field South (EDF-S) observations of 23 square degrees at wide field depths in the first quick data release (Q1). Aims. With the goal of releasing complementary millimeter-wave data and encouraging legacy science, we performed dedicated observations of a 57-square-degree field overlapping the EDF-S. Methods. The observing time totaled 20 days, and we reached noise depths of 4.3, 3.8, and 13.2 $μ$K-arcmin at 95, 150, and 220 GHz, respectively. Results. In this work we present the temperature maps and two catalogs constructed from these data. The emissive source catalog contains 601 objects (334 inside EDF-S) with 54% synchrotron-dominated sources and 46% thermal dust emission-dominated sources. The 5$σ$ detection thresholds are 1.7, 2.0, and 6.5 mJy in the three bands. The cluster catalog contains 217 cluster candidates (121 inside EDF-S) with median mass $M_{500c}=2.12 \times 10^{14} M_{\odot}/h_{70}$ and median redshift $z$ = 0.70, corresponding to an order-of-magnitude improvement in cluster density over previous tSZ-selected catalogs in this region (3.81 clusters per square degree). Conclusions. The overlap between SPT and Euclid data will enable a range of multiwavelength studies of the aforementioned source populations. This work serves as the first step toward joint projects between SPT and Euclid and provides a rich dataset containing information on galaxies, clusters, and their environments.

Archipley, M. [Chicago U., Astron. Astrophys. Ctr.↗
NASA NTRS2023

Mesospheric and Upper Stratospheric Temperatures From OMPS-LP

We report the development of a temperature profile data set from the Ozone Mapping and Profiler Suite Limb Profiler (OMPS-LP) instrument on the Suomi NPP satellite. The data set covers a roughly 10 year period from 2012 to 2022, and temperatures are provided in the altitude range between 35 and 70 km. The algorithm uses daytime Rayleigh scattered radiation near 350 nm to estimate atmospheric density profiles, which are vertically integrated using the hydrostatic equation to estimate atmospheric pressure. Temperature profiles are then derived using the ideal gas law. Spectral structures in the OMPS-LP radiances are a source of systematic errors that limit the absolute accuracy to ±2 K. However, since the systematic errors do not change significantly over time, the relative accuracy is better than ±1 K. Our temperature data set has been designed to supplement global temperature maps produced by assimilation of data from traditional meteorological sensors, including GNSS radio occultation sensors, that provide high quality atmospheric temperature profiles up to 40–55 km. We show comparisons to other co-located temperature datasets to validate our product.

Observations of Mesospheric and Upper Stratospheri↗
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 OSTI2023

TDD LoRa and Delta Encoding in Low-Power Networks of Environmental Sensor Arrays for Temperature and Deformation Monitoring: Supporting Data

This dataset was used to assess the performance of a compression algorithm for Soil Deformation and Temperature Monitoring data. The development of this technology is presented in the article named time division duplex (TDD) "TDD LoRa and Delta Encoding in Low-Power Networks of Environmental Sensor Arrays for Temperature and Deformation Monitoring" and published in Springer's Journal on Signal Processing Systems. [Time Division Duplex (TDD); Long Range (LoRa)]Field experiment data includes: 1) soil temperature measurements, 2) snow temperature data, 3) soil temperature and deformation data. In these files, the first column contains the time (UTC), followed by the sensor's battery voltage and temperature and acceleration values (X, Y, Z) in subsequent columns. The measurements were acquired every 15 minutes. Lists included for probe, datalogger, and packaging components. The two temperature data sets were acquired at a site at the East River Watershed, Colorado, while the temperature/deformation data were collected at the Teller Road (mile 27) site near Nome, Alaska. The package includes 8 comma-separated files (.csv) and one .pdf file.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Composition-Temperature-Partial Pressures Data for Cd(sub 0.8)Zn(sub 0.2)Te by Optical Absorption Measurements

Known weights of Cd, Zn and Te were reacted in silica optical cells of known volume and the partial pressure of Te2 and Zn between 485 and 1160 C were determined by measuring the optical density of the vapor in the ultra-violet to visible range. The composition of the condensed phase or phases was calculated from the original weights and the amount of material in the vapor phase. The corresponding composition - temperature - partial pressures, x(sub Te)-T-P(sub Te2), data, including five Te-rich solidus points, were established. The solubility range for the Te-rich Cd(sub 0.8)Zn(sub 0.2)Te(s) is similar to that of CdTe(s) with x(sub Te) = 0.50005 at 809 C and an estimated maximum solubility of x(sub Te) = 0.50012 at about 1000 C. The partial pressure of Cd and Te(sub 2) measured over the Cd(sub 0.8)Zn(sub 0.2)Te melt at 1140 C were about 1.55 and 0.02 atm, respectively, and the corresponding P(Sub Zn) was estimated to be 0.05 atm. It was recommended that a Cd reservoir maintaining at 800 to 820 C should be used during directional solidification of Cd(sub o.8)Zn(sub 0.2)Te to prevent the preferential loss of Cd to the vapor phase.

Su, Ching-Hua↗
DOE OSTI2015

Fallon FORGE: GIS and Downhole Well Lithology Data

ArcGIS Map Package with MT Station Locations, 2D Seismic Lines, Well data, Known Regional Hydrothermal Systems, Regional Historic Earthquake Seismicity, Regional Temperature Gradient Data, Regional Heat Flow Data, Regional Radiogenic Heat Production, Local Geology, Land Status, Cultural Data, 2m Temperature Probe Data, and Gravity Data. Also a detailed down-hole lithology notes are provided.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

A Measurement of the Cosmic Microwave Background Lensing Potential and Power Spectrum from 500 deg 2 of SPTpol Temperature and Polarization Data

In this work, we present a measurement of the cosmic microwave background (CMB) lensing potential using 500 deg$^2$ of 150 GHz data from the SPTpol receiver on the South Pole Telescope. The lensing potential is reconstructed with signal-to-noise per mode greater than unity at lensing multipoles $L \lesssim 250$, using a quadratic estimator on a combination of CMB temperature and polarization maps. We report measurements of the lensing potential power spectrum in the multipole range of $100< L < 2000$ from sets of temperature-only, polarization-only, and minimum-variance estimators. We measure the lensing amplitude by taking the ratio of the measured spectrum to the expected spectrum from the best-fit $\Lambda$CDM model to the $\textit{Planck}$ 2015 TT+lowP+lensing dataset. For the minimum-variance estimator, we find $A_{\rm{MV}} = 0.944 \pm 0.058{\rm (Stat.)}\pm0.025{\rm (Sys.)}$; restricting to only polarization data, we find $A_{\rm{POL}} = 0.906 \pm 0.090 {\rm (Stat.)} \pm 0.040 {\rm (Sys.)}$. Considering statistical uncertainties alone, this is the most precise polarization-only lensing amplitude constraint to date (10.1 $\sigma$), and is more precise than our temperature-only constraint. We perform null tests and consistency checks and find no evidence for significant contamination.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

The use of polar-orbiting satellite sounding data to estimate rural maximum and minimum temperatures

Atmospheric sounding products from NOAA's polar-orbiting satellites were used to derive and test predictive equations of rural shelter-level maximum and minimum temperatures. Sounding data from both winter and summer months were combined with surface data from over 5300 cooperative weather stations in the continental United States to develop multiple linear regression equations. Separate equations were developed for both maximum and minimum temperature, using the three types of sounding retrievals (clear, partly cloudy, and cloudy). Clear retrieval models outperformed others, and maximum temperatures were more accurately predicted than minimums. Average standard deviations of observed rural shelter temperatures within sounding search areas were of similar magnitude to root-mean-square errors from satellite estimates for most clear and partly cloudy cases, but were significantly less for cloudy retrieval cases. Model validation for surrogate polar and tropical climatic regions showed success in application of the four clear retrieval models (maximum and minimum temperature, for both winter and summer). This indicates the potential adaptability of these models to estimates of rural shelter temperature in areas outside of the United States.

Johnson, Gregory L.↗
DOE OSTI2023

Reactor Network Analysis with Various Reaction Mechanisms to Investigate Hydrogen vs. Methane Fuel at Varying Flame Temperatures with Experimental Data

Emissions data were evaluated for a set of test hardware that adapts Collins Aerospace’s aeroengine liquid fueled injector technology to a ground-based turbine. The hardware was specifically developed to operate on 100% hydrogen; however it has the ability to operate on both pure methane and hydrogen and mixtures in between. 16 injector configurations and seven factors (air split, fuel and air swirl, pressure drop, preheat temperature, fuel composition, and flame temperature) were investigated based on a Box Behnken statistical model. Of the 16, configuration 3 was selected for further discussion being in the middle of the statistical design space. A chemical reactor network was developed based on the experimental data obtained and was assessed with three different mechanisms: GRI Mech 3.0, UCSD, and Galway. All factors were held constant except the fuel composition to directly compare chemical pathways for methane and hydrogen. This study was conducted across different flame temperatures of 1500K, 1675K, and 1850K for both hydrogen and methane. Additional lower flame temperatures of 1100K and 1300K were evaluated for hydrogen. Moreover, results for fully premixed and non-premixed results were compared to obtain information on the implications of mixedness on emissions. These results were compared with the Leonard and Stegmaier plot for methane and a similar plot was constructed for hydrogen.

08 HYDROGEN↗
DOE OSTI2021

Evaluation of cooling setpoint setback savings in commercial buildings using electricity and exterior temperature time series data

Commercial buildings account for a significant amount of total energy produced in the US, and the Heating Ventilation and Cooling (HVAC) systems are one of the most significant components of their overall consumption. In this study, we proposed a new data-driven approach to evaluate HVAC cooling systems in commercial buildings and identify savings opportunities. The focus is an investigation of the impact of thermostat setpoint setback but using only whole building, electricity data taken at 15-min intervals for the analysis. We conducted a comparative study of setpoint setback characteristics on 432 commercial buildings with 5 building usage types across the United States. To accomplish this, both piecewise and Random Forest regression algorithms were employed using electricity and exterior temperature datasets to identify operational characteristics and the effective setpoints in the building to determine the corresponding savings opportunities. Both occupied and unoccupied time periods were studied across cooling degree days (CDD), when air conditioning is typically operational. Here the results show that in commercial buildings, on average, cooling systems account for 9.5% of total consumption. When a one degree setback during the cooling season is applied, an average of approximately 1.1% of annual consumption is achieved; retail and office buildings demonstrate the highest potential for savings. Additionally, we identified that the number of cooling degree days and base to peak ratio (BPR) are the most important variables for predicting the magnitude of the consumption of cooling systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

High Temperature Material Property Data and Challenges to Thermal Process Model Predictions and In-Situ/Ex-Situ Measurements for Metallic Additive Manufacturing

Understanding and predicting performance properties of parts produced by metallic additive manufacturing has improved significantly over the past decade; however, difficult to measure material properties and process outcomes continue to be challenges. The qualification or certification of aerospace parts require extensive measures to quantify variable part properties in order to buy down the risk of component failure. The variability, inherent to the additive manufacturing, process adds unwanted uncertainty in the production of load critical structural components. Process modeling has proven valuable in providing predictions and context for understanding outcomes of the additive manufacturing process; however, these physically informed process models require material properties at temperatures that are difficult to measure and rarely available. Further, calibrating or validating such models is difficult because the process itself is challenging to measure. This talk will explore some of the challenges resulting from difficult to acquire input data by relating thermal process model predictions to in-situ and ex-situ optical microscopy measurements.

Process Model↗
NASA NTRS2002

Global Surface Temperature Change and Uncertainties Since 1861

The objective of this talk is to analyze the warming trend and its uncertainties of the global and hemi-spheric surface temperatures. By the method of statistical optimal averaging scheme, the land surface air temperature and sea surface temperature observational data are used to compute the spatial average annual mean surface air temperature. The optimal averaging method is derived from the minimization of the mean square error between the true and estimated averages and uses the empirical orthogonal functions. The method can accurately estimate the errors of the spatial average due to observational gaps and random measurement errors. In addition, quantified are three independent uncertainty factors: urbanization, change of the in situ observational practices and sea surface temperature data corrections. Based on these uncertainties, the best linear fit to annual global surface temperature gives an increase of 0.61 +/- 0.16 C between 1861 and 2000. This lecture will also touch the topics on the impact of global change on nature and environment. as well as the latest assessment methods for the attributions of global change.

Shen, Samuel S. P.↗
NASA NTRS2005

Effects of Variable Temperature on Mossbauer Data Acquisition: Laboratory-based and MER A Results

Mossbauer spectrometers on the Spirit and Opportunity rovers have played a valuable role in identifying mineralogy at both the Gusev and Meridiani landing sites. Key to the application of Mossbauer results is the issue of how accurately the peak positions, on which the mineral identifications are based, can be determined. Remote Mossbauer spectroscopy has by necessity some unusual experimental constraints that may influence the confidence with which peak positions can be fit. We present here an analysis of the effects of variable temperature and short duration run times on spectral resolution.

Rothstein, Y.↗
NASA NTRS1984

Sea surface temperatures from VAS MSI data

A procedure is developed for estimating sea surface temperatures from multispectral image data acquired from the VISSR atmospheric sounder on the geostationary GOES satellites. Theoretical regression equations for two and three infrared window channels are empirically tuned using clear field of view satellite radiances matched with reports of SST from NOAA fixed environmental buoys. The empirical regression equations are then used to produce daily regional analyses of SST. Monthly mean SST's for the western North Atlantic and the eastern equatorial Pacific during March and July 1982 were produced for use in the SST Intercomparison Workshop Series. Workshop results showed VAS SST's have a scatter of 0.8-1.0 C and a slight warm bias with respect to the other measurements of SST. The VAS SST's show no discernible bias in the region of El Chichon volcanic aerosol cloud.

Bates, J. J.↗
DOE OSTI2026

Raw soil carbon dioxide, moisture, temperature and micrometeorological data in the East River Watershed, Colorado June 2021-June 2024. (DE-SC0021139)

This dataset contains raw data from four tripod stations along an elevation gradient on Snodgrass Mountain in the East River Watershed, CO, USA. Each station contains a datalogger connected to 3 soil Carbon Dioxide CO2 gas probes, 3 soil temperature/moisture sensors and a micrometeorological station. Sensors are scanned every minute, and the 30 minute average is reported. The file snodgrass_soil_ESS.csv contains raw data, a row of column descriptors, and units of measurements. some data processing and QA/QC was done to filter out data from sensors that went bad and extreme outliers. CO2 sensors that went bad were replaced with new sensors as soon as possible. This research was performed to investigate the ecohydrological linkages of belowground carbon processes in the East River watershed forested communities to better understand how these ecosystems will respond to a changing cold-season moisture input. This is the second version of this data set and was modified on 10/01/2024. The primary change in the data was the addition of data from the fall of 2022 to June of 2024. In addition, minor QA/QC was done to filter out data from sensors that went bad and extreme outliers. THe filtered data are now NA's in this data frame and primarily the CO2 sensors. Limited to no QA/QC has been done on the other environmental data. This is now the third version of the data set, and was modified 03/25/2026. The primary change in the data was the addition of data from the June of 2024 to December 2025. Further r QA/QC was done with the new data to filter out bad data from faulty sensors and extreme outliers. The filtered data are now NA's in this data frame and primarily the CO2 sensors. Limited to no QA/QC has been done on the other environmental data. ##This additional data was funded under DE-SC0024218( Responses of Plant and Microbial Respiration Sources to Changing Cold Season Climate Drivers in the East River Watershed)

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1978

Feasibility of estimation of surface air temperature from meteorological satellite data test plan

A conceptual system designed to estimate daily surface air temperatures utilizing radiometric data obtained from polar orbiting meteorological satellites is discussed in this memorandum. The Surface Air Temperature Estimation System is an outgrowth of previous developmental and operational systems. The system represents an effort to integrate both satellite and surface meteorological observations into an operational framework which would be usable worldwide.

Phinney, D. E.↗