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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 1,225 records · Page 68

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NASA NTRS2005

The Vapor Pressure of Palladium at Temperatures up to 1973K

Understanding high-temperature processes is imperative for modeling the formation of the solar system. It is unfortunate that since the 1950 s little has been done in the area of thermodynamics to continue gaining information on metals such as iron (Fe), nickel (Ni), cobalt (Co), palladium (Pd) and many others. Although the vapor pressures of these metals can be extrapolated to higher temperatures, the data is often limited to temperature ranges too low to be applicable to processes that occur during the formation of the solar system (T approx. 2000K). Experimental techniques inhibited the data in the past by restricting the testing of metals to temperatures below their melting point. Today, higher temperature testing is possible by using a Thermo- Cahn Thermogravimetric system that is able to reach temperatures up to 1973K in vacuo and measure a 10 gram change in a sample with mass of up to 100 grams.

Gardner, K. G.↗

DOE OSTI2022

Thermal measurement apparatus and methods for anisotropic thermal materials

A system for characterizing thermal properties of thermally anisotropic heterogeneous samples includes a heating element, a first temperature sensing device, a second temperature sensing device, and a computing system. The heating element is positioned at a first location within a sample and heats the sample. The first temperature sensing device outputs data indicative of temperatures of the first location to the computing device. The second temperature sensing device outputs data indicative of temperatures of the second location to the computing device. The computing device computes a thermal conductivity of the sample based upon the temperatures of the first location. The computing device further outputs an indication of a portion of the sample to which the thermal conductivity pertains based upon the second temperatures.

Reyes, Karla Rosa↗

DOE OSTI2023

Thermal measurement apparatus and methods for anisotropic thermal materials

Reyes, Karla Rosa↗

NASA NTRS1995

Estimating the urban bias of surface shelter temperatures using upper-air and satellite data. Part 1: Development of models predicting surface shelter temperatures

Multiple regression techniques were used to predict surface shelter temperatures based on the time period 1986-89 using upper-air data from the European Centre for Medium-Range Weather Forecasts (ECMWF) to represent the background climate and site-specific data to represent the local landscape. Global monthly mean temperature models were developed using data from over 5000 stations available in the Global Historical Climate Network (GHCN). Monthly maximum, mean, and minimum temperature models for the United States were also developed using data from over 1000 stations available in the U.S. Cooperative (COOP) Network and comparative monthly mean temperature models were developed using over 1150 U.S. stations in the GHCN. Three-, six-, and full-variable models were developed for comparative purposes. Inferences about the variables selected for the various models were easier for the GHCN models, which displayed month-to-month consistency in which variables were selected, than for the COOP models, which were assigned a different list of variables for nearly every month. These and other results suggest that global calibration is preferred because data from the global spectrum of physical processes that control surface temperatures are incorporated in a global model. All of the models that were developed in this study validated relatively well, especially the global models. Recalibration of the models with validation data resulted in only slightly poorer regression statistics, indicating that the calibration list of variables was valid. Predictions using data from the validation dataset in the calibrated equation were better for the GHCN models, and the globally calibrated GHCN models generally provided better U.S. predictions than the U.S.-calibrated COOP models. Overall, the GHCN and COOP models explained approximately 64%-95% of the total variance of surface shelter temperatures, depending on the month and the number of model variables. In addition, root-mean-square errors (rmse's) were over 3 C for GHCN models and over 2 C for COOP models for winter months, and near 2 C for GHCN models and near 1.5 C for COOP models for summer months.

Epperson, David L.↗

DOE OSTI2026

Ecological Insights from Transferable Plant Biomass Mapping across the Arctic using High-resolution Structure-from-Motion and LiDAR Data

Warmer temperatures, permafrost thaw, and increased wildfire activity are driving rapid ecological change across the Arctic, significantly altering plant productivity and aboveground biomass (AGB). These rapid changes highlight the urgent need to improve monitoring of vegetation dynamics in the Earth’s northern ecosystems, where high spatiotemporal heterogeneity occurs at scales finer than those captured by traditional satellite observations. The growing use of Unoccupied Aerial Systems (UASs) presents an opportunity to overcome this limitation. Yet, the diversity of UAS platforms, sensors, and data collection and processing workflows presents challenges for developing standardized, generalizable approaches. To address this challenge, we compiled 672 AGB plots co-located with 183 UAS-based Structure-from-Motion (SfM) or Light Detection and Ranging (LiDAR) surveys collected across the Arctic. Here, we: (1) evaluated the generalizability of UAS-derived canopy structure derived from high-resolution SfM and LiDAR for estimating AGB, (2) assessed scaling errors and their sources in two recent satellite-based AGB products derived from Landsat and MODIS, and (3) demonstrated the use of high-resolution AGB maps to quantify biomass variation across tundra plant functional types (PFTs) and to monitor post-fire recovery. Our results show that both SfM and LiDAR accurately captured AGB and its variability across tundra PFTs using a Random Forest (RF) model (overall RMSE: 0.336 kg/m2), with mapping performance varying slightly by region and data source. Using UAS-derived AGB maps as a benchmark, we identified systematic biases in satellite-derived AGB products, largely attributable to the magnitude of AGB and structural heterogeneity within coarse-resolution pixels. Applying our model to repeat UAS surveys following a tundra fire on Seward Peninsula, we observed rapid AGB recovery in non-shrub patches, with biomass recovering to pre-fire levels within 2 years. In contrast, shrub patches recovered more slowly, with AGB gains continuing over 2–4 years through both in-patch growth and lateral expansion (via dispersal) into remaining burned areas. Overall, these findings demonstrate the generalizability of UAS-based SfM and LiDAR data for estimating tundra AGB and highlight the potential of our approach to be broadly applied to generate high-quality AGB data for ecological monitoring and model benchmarking across the Arctic.

Yang, Daryl [ORNL] (ORCID:0000000317057823)↗

DOE OSTI2017

Tularosa Basin Play Fairway Analysis: Temperature, Geochemistry, and Gravity Data

This submission contains multiple excel spreadsheets and associated written reports. The datasets area are representative of shallow temperature, geochemistry, and other well logging observations made across WSMR (white sands missile range); located to the west of the Tularosa Basin but still within the study area. Written reports accompany some of the datasets, and they provide ample description of the methodology and results obtained from these studies. Gravity data is also included, as point data in a shapefile, along with a written report describing that particular study.

15 GEOTHERMAL ENERGY↗

DOE OSTI2019

Appalachian Basin Temperature-Depth Maps and Structured Data in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy

This dataset contains shapefiles and rasters that summarize the results of a stochastic analysis of temperatures at depth in the Appalachian Basin states of New York, Pennsylvania, and West Virginia. This analysis provides an update to the temperature-at-depth maps provided in the Geothermal Play Fairway Analysis of the Appalachian Basin (GPFA-AB) Thermal Quality Analysis (GDR repository 879: https://gdr.openei.org/submissions/879). This dataset improves upon the GPFA-AB dataset by considering several additional uncertainties in the temperature-at-depth calculations, including geologic properties and thermal properties. A Monte Carlo analysis of these uncertain properties and the GPFA-AB estimated surface heat flow was used to predict temperatures at depth using a 1-D heat conduction model. In this data submission, temperatures are provided for depths from 1-5 km in 0.5 km increments. The mean, standard deviation, and selected quantiles of temperatures at these depths are provided as shapefiles with attribute tables that contain the data. Rasters are provided for the mean and standard deviation data. Figures and maps that summarize the data are also provided. For the pixel corresponding to Cornell University, Ithaca, NY, a .csv file containing the 10,000 temperature-depth profiles estimated from the Monte Carlo analysis is provided. These data are summarized in a figure containing violin plots that illustrate the probability of obtaining certain temperatures at depths below Cornell.

15 GEOTHERMAL ENERGY↗

NASA NTRS1979

Estimating tropical cyclone outer surface winds from satellite microwave data

Warm temperature anomalies over tropical cyclones are sensed by the 55.45 GHz channel of the Nimbus 6 Scanning Microwave Spectrometer. Radial brightness temperature gradients are related to radial surface pressure gradients through the hydrostatic and radiative transfer equations. Surface wind speeds outside of the radius of maximum wind are calculated from the pressure gradients and compared with observations.

Kidder, S. Q.↗

NASA NTRS1975

Low altitude temperature and humidity profile data for application to aircraft noise propagation

A data search of the weather statistics from 11 widely dispersed geographical locations within the continental United States was conducted. The sites, located long both sea-coasts and in the interior, span the northern, southern, and middle latitudes. The weather statistics, retrieved from the records of these 11 sites, consist of two daily observations taken over a 10-year period. The data were sorted with respect to precipitation and surface winds and classified into temperature intervals of 5 C and relative humidity intervals of 10 percent for the lower 1400 meters of the atmosphere. These data were assembled in a statistical format and further classified into altitude increments of 200 meters. The data are presented as sets of tables for each site by season of the year and include both daily observations.

Connor, A. B.↗

DOE OSTI2025

Five Years of Dissolved Oxygen, Temperature, Salinity, Depth, Weather Data from a Transitioning Wetland at Beaver Creek, Washington, USA

Groundwater dissolved oxygen (DO) variability in coastal system remains poorly understood despite its importance for biogeochemical cycling and ecosystem modeling. Here we investigate the temporal variability in groundwater DO and its hydro-climatic drivers across hourly to seasonal timescales in a transitioning wetland at Beaver Creek, Washington, USA. The site is transitioning from a freshwater forest to a brackish tidal wetland following removal of a barrier in 2014 that prevented tides from accessing the freshwater creek. By utilizing novel optical dissolved oxygen instrumentation (Opti O2, LLC) we obtained continuous, high-frequency (5-minute), in-situ measurements of DO from the flood-plain from June 26th, 2019 through September 30th, 2024. This 63 month dataset is comprised of groundwater dissolved oxygen, temperature, water level and salinity timeseries from the floodplain. This dataset also includes rainfall, air pressure, air temperature, and solar radiation data collected with a co-located Campbell ClimaVUE50 weather sensor. All data is contained within a single csv (2019-06-26 to 2024-09-30 Beaver Creek DO, saln, BGS, temp, weather.csv) that can easily be viewed either using software such as Excel or using any text editor.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Inflationary features and shifts in cosmological parameters from Planck 2015 data

We explore the relationship between features in the Planck 2015 temperature and polarization data, shifts in the cosmological parameters, and features from inflation. Residuals in the temperature data at low multipole &ell;, which are responsible for the high H 0 ≈ 70 km s –1 Mpc –1 and low σ 8 $Ω^{1/2}_{m}$ values from &ell; < 1000 in power-law ΛCDM models, are better fit to inflationary features with a 1.9σ preference for running of the running of the tilt or a stronger 99% CL local significance preference for a sharp drop in power around k = 0.004 Mpc –1 in generalized slow roll and a lower H 0 ≈ 67km s –1 Mpc –1 . The same in-phase acoustic residuals at &ell; >1000 that drive the global H 0 constraints and appear as a lensing anomaly also favor running parameters which allow even lower H 0 , but not once lensing reconstruction is considered. Polarization spectra are intrinsically highly sensitive to these parameter shifts, and even more so in the Planck 2015 TE data due to an outlier at &ell; ≈ 165,which disfavors the best fit H 0 ΛCDM solution by more than 2σ, and high H 0 value at almost 3σ. Current polarization data also slightly enhance the significance of a sharp suppression of large-scale power but leave room for large improvements in the future with cosmic variance limited E-mode measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2019

Application of a Temperature-Dependent Load Prediction Method to a RUAG Six-Component Block-Type Balance

Temperature-dependent data of a RUAG six-component block-type balance was analyzed to assess the accuracy of two load prediction methods for temperature-dependent balance data. The supplied data was prepared for the analysis by splitting it into calibration and check load data subsets. The first calibration data subset was obtained at a temperature of 294 Kelvin. The second calibration data subset was obtained at a temperature of 315 Kelvin. A subset of 38 points was extracted from the second data set and used as check loads so that the accuracy of the two load prediction methods could be tested. First, the Iterative Method in combination with an extended independent and dependent variable set was used for the balance load prediction. This approach fits electrical outputs as a function of loads and the temperature and, afterwards, constructs a load iteration scheme from the regression coefficients so that loads can be predicted from outputs and the temperature during a wind tunnel test. The Non-Iterative Method was also used for the load prediction. This alternate method can more easily be implemented in a data system as loads are directly fitted as a function of electrical outputs and the temperature. Analysis results for the axial force are only discussed in the paper as similar results were obtained for the other five load components. Results for both methods clearly show that the cross-product term constructed from either a primary gage load or a primary gage output and the temperature explains the majority of the temperature-dependent part of the predicted balance load. This term models the temperature dependent nature of the gage sensitivity. Therefore, it is recommended to apply primary gage loadings at different temperatures during a balance calibration whenever temperature effects need to be described. These loadings will contain information about the temperature-dependent nature of the gage sensitivities that can be quantified by related cross-product terms in regression models of the data.

strain-gage balance↗

NASA NTRS1977

Preliminary studies of autoignition and flashback in a premixing-prevaporizing flame tube using Jet-A fuel at lean equivalence ratios

Lean equivalence ratios from 0.3 to 0.7 were observed. Combustor inlet air pressures were varied from 0.54 to 2.5 MPa, combustor inlet air temperatures from 550 to 700 K, and reference velocities from 8 to 35 meters per second. Autoignition delay times ranged from 15 to 100 milliseconds and varied inversely with pressure. The Arrhenius activation energy was 41,840 joules per mole. Temperature rise data were obtained in a long premixing-prevaporizing tube at a pressure of 0.56 MPa. Preflame temperature rise data were a function of equivalence ratio, inlet air temperature, and tube residence time. Significant temperature rise occurred above temperatures of 760 K, with autoignition occurring at 775 K for equivalence ratios greater than 0.47. The reactions were similar to cool-flame phenomena. Flashback velocities were measured at temperatures of 610 and 700 K, pressure of 0.56 MPa, and equivalence ratios from 0.6 to 1. Flashback velocities varied from 30 to 65 meters per second.

Marek, C. J.↗

NASA NTRS1982

Delineation of soil temperature regimes from HCMM data

The subsetting of HCMM data into ORSER format was completed for four dates using a modified SUBSET program. Large areas (approximately 2500 scan lines, 1680 elements) were selected to increase the occurrence of suitable control points for registration. Average daily temperatures (ADT) were calculated for each date. The MERGE program combined registered daytime temperature (DAY-IR) with nighttime temperature (NIGHT-IR) to form a separate two-channel data set. The SUBTRAN program averaged the DAY-IR and NIGHT-IR creating a third ADT channel. Registration equations for the four ADT data sets were generated. A one dimensional soil heat flow equation was modified to allow for mean annual soil temperature predictions using merged ADT data sets.

Day, R. L.↗

NASA NTRS1981

Satellite-derived ice data sets no. 1: Antarctic monthly average microwave brightness temperatures and sea-ice concentrations, 1973 - 1976

A summary data set concerning 4 years of Antarctic sea-ice conditions was created and is available on magnetic tape. The data were derived from electrically scanning microwave radiometer brightness temperatures and were mapped into a polar stereographic grid enclosing the 50 deg S latitude circle. The grid size varies from about 32 by 32 sq km at the poles to about 28 by 28 sq km at 50 deg S. The microwave brightness temperatures of Antarctic sea ice are predominantly characteristic of first-year ice with an emissivity of 0.92 at 19 GHz frequency. Sea ice concentrations were calculated from the brightness temperature data for each grid element with an algorithm that uses an emissivity value of 0.92 and an ice physical temperature estimate from climatological surface air temperatures. Monthly, multiyear monthly, and yearly maps of brightness temperatures and sea ice concentrations were created for the 4 years, except for 7 months for which useable data were insufficient.

Zwally, H. J.↗

NASA NTRS1985

Moessbauer studies on LaNi(4.7)Sn(0.3) and its hydride

Moessbauer measurements were made on LaNi(4.7)Sn(0.3) at room and liquid nitrogen temperatures. Experimental data yielded a singlet at room temperature and a doublet at liquid-nitrogen temperature. Spectra of the hydrided sample yielded a doublet at liquid-nitrogen temperature with an increase in the quadrupole splitting compared to the unhydrided spectra, but no change in the isomer shift. These data indicate that there is no significant interaction between the tin and the hydrogen. The magnetic character remained the same down to liquid-nitrogen temperature as evidenced by the Moessbauer data. X-ray diffraction measurements on the hydride showed an expanded lattice with the same structure as found for the unhydrided sample. A decrease in particle size was observed upon hydriding.

Oliver, F. W.↗

NASA NTRS2015

Viking GCMS Data Restoral and Perceiving Temperature on Other Worlds: Astrobiology Projects at NASA Ames

The primary task for the summer was to procure the GCMS data from the National Space Science Data Coordinated Archive (NSSDCA) and to assess the current state of the data set for possible reanalysis opportunities. After procurement of the Viking GCMS data set and analysis of its current state, the internship focus shifted to preparing a plan for restoral and archiving of the GCMS data set. A proposal was prepared and submitted to NASA Headquarters to restore and make available the 8000 mass chromatographs that are the basic data generated by the Viking GCMS instrument. The relevance of this restoral and the methodology we propose for restoral is presented. The secondary task for the summer is to develop a thermal model for the perceived temperature of a human standing on Mars, Titan, or Europa. Traditionally, an equation called "Fanger's comfort equation" is used to measure the perceived temperature by a human in a given reference environment. However, there are limitations to this model when applied to other planets. Therefore, the approach for this project has been to derive energy balance equations from first principles and then develop a methodology for correlating "comfort" to energy balance. Using the -20 C walk-in freezer in the Space Sciences building at NASA Ames, energy loss of a human subject is measured. Energy loss for a human being on Mars, Titan and Europa are calculated from first principles. These calculations are compared to the freezer measurements, e.g. for 1 minute on Titan, a human loses as much energy as x minutes in a -20 C freezer. This gives a numerical comparison between the environments. These energy calculations are used to consider the physiological comfort of a human based on the calculated energy losses.

FangeraEuro(TM)s comfort equation↗

DOE OSTI2023

Determining biomolecular structures near room temperature using X-ray crystallography: concepts, methods and future optimization

For roughly two decades, cryocrystallography has been the overwhelmingly dominant method for determining high-resolution biomolecular structures. Competition from single-particle cryo-electron microscopy and micro-electron diffraction, increased interest in functionally relevant information that may be missing or corrupted in structures determined at cryogenic temperature, and interest in time-resolved studies of the biomolecular response to chemical and optical stimuli have driven renewed interest in data collection at room temperature and, more generally, at temperatures from the protein–solvent glass transition near 200 K to ∼350 K. Fischer has recently reviewed practical methods for room-temperature data collection and analysis [Fischer (2021), Q. Rev. Biophys. 54 , e1]. Here, the key advantages and physical principles of, and methods for, crystallographic data collection at noncryogenic temperatures and some factors relevant to interpreting the resulting data are discussed. For room-temperature data collection to realize its potential within the structural biology toolkit, streamlined and standardized methods for delivering crystals prepared in the home laboratory to the synchrotron and for automated handling and data collection, similar to those for cryocrystallography, should be implemented.

59 BASIC BIOLOGICAL SCIENCES↗