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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Inflight fuel tank temperature survey data

Statistical summaries of the fuel and air temperature data for twelve different routes and for different aircraft models (B747, B707, DC-10 and DC-8), are given. The minimum fuel, total air and static air temperature expected for a 0.3% probability were summarized in table form. Minimum fuel temperature extremes agreed with calculated predictions and the minimum fuel temperature did not necessarily equal the minimum total air temperature even for extreme weather, long range flights.

Pasion, A. J.↗
NASA NTRS2000

BOREAS AFM-06 Mean Temperature Profile Data

The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-6 team from the National Oceanic and Atmospheric Adminsitration/Environment Technology Laboratory (NOAA/ETL) operated a 915-MHz wind/Radio Acoustic Sounding System (RASS) profiler system in the Southern Study Area (SSA) near the Old Jack Pine (OJP) tower from 21 May 1994 to 20 Sep 1994. The data set provides temperature profiles at 15 heights, containing the variables of virtual temperature, vertical velocity, the speed of sound, and w-bar. The data are stored in tabular ASCII files. The mean temperature profile data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Wilczak, James↗
DOE OSTI2022

JHU Baltimore iButton data

Temperature and Relative Humidity data from a low cost sensor ("iButton") network deployed in Baltimore in summer 2015, 2016, 2017, 2021, and 2022. Initial deployment described in Scott, A., Zaitchik, B., Waugh, D., O'Meara, K. 2017. Intra-Urban temperature variability in Baltimore. Journal of Applied Meteorology and Climatology, 56(1): 159-171. doi: 10.1175/JAMC-D-16-0232.1

applied meteorology↗
NASA NTRS1980

Statistical Analysis of daily mean temperatures

Data of daily mean temperatures recorded at the Kennedy Center during the period of 1957-1977 were analyzed to forecast daily mean temperatures and their thirty-day moving averages for a period of ten to fifteen days in a given month. Since it is found that the standard deviation is linear in the mean, a logarithmic transformation of the data is used for finding an integrated moving average process IMA by the Box-Jenkins aproach. The first differences of the transformed data seem to fit a moving average model with parameter value 2, MA(2). The consideration of seasonality factor makes the fit worse.

Ross, D. C.↗
DOE OSTI2015

Uncertainty quantification of calculated temperatures for advanced gas reactor fuel irradiation experiments

This paper presents the quantification of uncertainty of the calculated temperature data for the Advanced Gas Reactor (AGR) fuel irradiation experiments conducted in the Advanced Test Reactor at Idaho National Laboratory in support of the Advanced Reactor Technology Research and Development program. Recognizing uncertainties inherent in physics and thermal simulations of the AGR tests, the results of the numerical simulations are used in combination with statistical analysis methods to improve qualification of measured data. The temperature simulation data for AGR tests are also used for validation of the fission product transport and fuel performance simulation models. These crucial roles of the calculated fuel temperatures in ensuring achievement of the AGR experimental program objectives require accurate determination of the model temperature uncertainties. To quantify the uncertainty of AGR calculated temperatures, this study identifies and analyzes ABAQUS model parameters of potential importance to the AGR predicted fuel temperatures. The selection of input parameters for uncertainty quantification of the AGR calculated temperatures is based on the ranking of their influences on variation of temperature predictions. Thus, selected input parameters include those with high sensitivity and those with large uncertainty. Propagation of model parameter uncertainty and sensitivity is then used to quantify the overall uncertainty of AGR calculated temperatures. Expert judgment is used as the basis to specify the uncertainty range for selected input parameters. The input uncertainties are dynamic accounting for the effect of unplanned events and changes in thermal properties of capsule components over extended exposure to high temperature and fast neutron irradiation. The sensitivity analysis performed in this work went beyond the traditional local sensitivity. Using experimental design, analysis of pairwise interactions of model parameters was performed to establish sufficiency of the first-order (linear) expansion terms in constructing the response surface. To achieve completeness, uncertainty propagation made use of pairwise noise correlations of model parameters. Furthermore, time-dependent sensitivity over the test campaign duration was obtained using an interpolation scheme over the input parameter domain. This allows computation of uncertainty for the predicted peak fuel temperatures and the predicted graphite temperatures at TC locations over the whole AGR irradiation period.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1975

The thermal structure of Jupiter. I - Implications of Pioneer 10 infrared radiometer data

Temperature profiles for low latitude regions of Jupiter in the 1.0-0.1 bar pressure regime are recovered from Pioneer 10 infrared radiometer data. The temperature near 0.1 bar is 108-117 K, depending on the overlying thermal structure assumed. For the South Equatorial Belt (SEB), the temperature at 1.0 bar is 170 K, assuming an adiabatic lapse rate in the deep atmosphere. The South Tropical Zone temperature at this level is 155 K if pure gaseous absorption is assumed. The temperature is much closer to that in the SEB, assuming the presence of an optically opaque cloud near the 0.6 atm (145 K) level. Such a cloud presence in the STrZ may be correlated with the visible and 5 micron appearance of the planet and with NH3 saturation just below this position. The molar fraction of H2 most consistent with the data is 0.91 + or - 0.08. The effective temperatures of the SEB and STrZ are 127.6 and 124.2 K, respectively. A discrepancy with the preliminary neutral atmosphere inversion of Pioneer 10 radio occultation data remains unexplained.

Orton, G. S.↗
DOE OSTI2018

Utah FORGE: Observation Well Data

This archive contains temperature data for Roosevelt Hot Springs observation wells OH-1, OH-4, OH-5 and OH-7. There are also mud logs for OH-4. These are old datasets obtained from Rocky Mountain Power for use in the Utah FORGE project. Temperature data were collected in the 1970s and 1980s.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Soil Temperature Sensor Data, May - December 2024, Five sites in Knoxville, Tennessee

This dataset contains surface soil temperature measurements from five urban parks in Knoxville: Cumberland Estates Park (CE), Socially Equal Energy Efficient Development (SD), West View Park (WV), Victor Ashe Park (VA), and West Hills Park (WH). The dataset comprises 29 Excel (.xlsx) and Comma-Separated Values (.csv) files documenting soil temperature recorded by six HOBO Pendant MX Water Temperature Data Loggers at each site, except for CE, which has five sensors. Each logger was installed at a depth of 10 inches and positioned approximately 3 to 6 feet from the weather station at each site. To open both csv and xlsx files, users can utilize spreadsheet applications such as Microsoft Excel, Google Sheets, LibreOffice Calc, and Apple Numbers. This dataset is part of a broader study examining the effects of soil moisture and plant evapotranspiration on ambient temperature and relative humidity across multiple urban parks in Knoxville, Tennessee.

EARTH SCIENCE > LAND SURFACE > SOILS↗
NASA NTRS1993

Synthesis of passive microwave and radar altimeter data for estimating accumulation rates of polar snow

In this paper, we compare dry-snow extinction coefficients derived from radar altimeter data with brightness temperature data from passive microwave measurements over a portion of the East Antarctic plateau. The comparison between the extinction coefficients and the brightness temperatures shows a strong negative correlation, where the correlation coefficients ranged from -0.87 to -0.95. The extinction coefficient of the dry polar snow decreases with increasing surface elevation, while the average brightness temperature increases with surface elevation. Our analysis shows that the observed trends are related to geographic variations in scattering coefficient of snow, which in turn are controlled by variations in surface temperature and snow accumulation rate. By combining information present in the extinction coefficient and brightness temperature data sets, we develop a model that can be used to obtain quantitative estimates of the accumulation rate of dry polar snow.

Davis, Curt H.↗
DOE OSTI2016

Data center thermal management

Historical high-spatial-resolution temperature data and dynamic temperature sensor measurement data may be used to predict temperature. A first formulation may be derived based on the historical high-spatial-resolution temperature data for determining a temperature at any point in 3-dimensional space. The dynamic temperature sensor measurement data may be calibrated based on the historical high-spatial-resolution temperature data at a corresponding historical time. Sensor temperature data at a plurality of sensor locations may be predicted for a future time based on the calibrated dynamic temperature sensor measurement data. A three-dimensional temperature spatial distribution associated with the future time may be generated based on the forecasted sensor temperature data and the first formulation. The three-dimensional temperature spatial distribution associated with the future time may be projected to a two-dimensional temperature distribution, and temperature in the future time for a selected space location may be forecasted dynamically based on said two-dimensional temperature distribution.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Carbon flux estimates are sensitive to data source: a comparison of field and lab temperature sensitivity data

Abstract A large literature exists on mechanisms driving soil production of the greenhouse gases CO 2 and CH 4 . Although it is common knowledge that measurements obtained through field studies vs. laboratory incubations can diverge because of the vastly different conditions of these environments, few studies have systematically examined these patterns. These data are used to parameterize and benchmark ecosystem- to global-scale models, which are then susceptible to the biases of the source data. Here, we examine how greenhouse gas measurements may be influenced by whether the measurement/incubation was conducted in the field vs. laboratory, focusing on CO 2 and CH 4 measurements. We use Q 10 of greenhouse gas flux (temperature sensitivity) for our analyses because this metric is commonly used in biological and Earth system sciences and is an important parameter in many modeling frameworks. We predicted that laboratory measurements would be less variable, but also less representative of true field conditions. However, there was greater variability in the Q 10 values calculated from lab-based measurements of CO 2 fluxes, because lab experiments explore extremes rarely seen in situ , and reflect the physical and chemical disturbances occurring during sampling, transport, and incubation. Overall, respiration Q 10 values were significantly greater in laboratory incubations (mean = 4.19) than field measurements (mean = 3.05), with strong influences of incubation temperature and climate region/biome. However, this was in part because field measurements typically represent total respiration (Rs), whereas lab incubations typically represent heterotrophic respiration (Rh), making direct comparisons difficult to interpret. Focusing only on Rh-derived Q 10 , these values showed almost identical distributions across laboratory ( n = 1110) and field ( n = 581) experiments, providing strong support for using the former as an experimental proxy for the latter, although we caution that geographic biases in the extant data make this conclusion tentative. Due to a smaller sample size of CH 4 Q 10 data, we were unable to perform a comparable robust analysis, but we expect similar interactions with soil temperature, moisture, and environmental/climatic variables. Our results here suggest the need for more concerted efforts to document and standardize these data, including sample and site metadata.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Temperature sensitivity of soil organic carbon decomposition increased with mean carbon residence time: Field incubation and data assimilation

Abstract Temperature sensitivity of soil organic carbon ( SOC ) decomposition is one of the major uncertainties in predicting climate‐carbon (C) cycle feedback. Results from previous studies are highly contradictory with old soil C decomposition being more, similarly, or less sensitive to temperature than decomposition of young fractions. The contradictory results are partly from difficulties in distinguishing old from young SOC and their changes over time in the experiments with or without isotopic techniques. In this study, we have conducted a long‐term field incubation experiment with deep soil collars (0–70 cm in depth, 10 cm in diameter of PVC tubes) for excluding root C input to examine apparent temperature sensitivity of SOC decomposition under ambient and warming treatments from 2002 to 2008. The data from the experiment were infused into a multi‐pool soil C model to estimate intrinsic temperature sensitivity of SOC decomposition and C residence times of three SOC fractions (i.e., active, slow, and passive) using a data assimilation ( DA ) technique. As active SOC with the short C residence time was progressively depleted in the deep soil collars under both ambient and warming treatments, the residences times of the whole SOC became longer over time. Concomitantly, the estimated apparent and intrinsic temperature sensitivity of SOC decomposition also became gradually higher over time as more than 50% of active SOC was depleted. Thus, the temperature sensitivity of soil C decomposition in deep soil collars was positively correlated with the mean C residence times. However, the regression slope of the temperature sensitivity against the residence time was lower under the warming treatment than under ambient temperature, indicating that other processes also regulated temperature sensitivity of SOC decomposition. These results indicate that old SOC decomposition is more sensitive to temperature than young components, making the old C more vulnerable to future warmer climate.

Zhou, Xuhui↗
DOE OSTI2024

Faraday: A High-temperature Electrolysis Data Explorer

Faraday is a high-temperature electrolysis data visualization tool, which reveals the performance of various button cells under test conditions. These tests and the resulting analytics on their data constitute a state of the industry as the US Department of Energy pushes for the production of hydrogen. Faraday leverages the Idaho National Laboratory's DeepLynx data warehouse to standardize and query button cell data. Faraday programmatically accesses this data in DeepLynx by traversing the schema, represented by a custom ontology. The user interface queries DeepLynx for timeseries data associated with specific button cells in the warehouse, and renders them using JavaScript charts. Additional charting and data analysis techniques are made possible by an auxiliary Python server.

Woodruff, Nathan↗
DOE OSTI2018

Utah FORGE: Roosevelt Hot Springs Analytical Well-Based Temperature Model Data

This submission contains a cumulative record of one-dimensional temperature modeling based off of well data in the vicinity of the Utah FORGE site. Temperature log data from wells used, and in some cases were extrapolated below the bottom of a number of wells. The data were corrected for elevation and location using the Utah FORGE earth model. These data locations correspond to well locations provided in GDR Submission 1111 (linked below). All data are georeferenced to UTM, zone 12N, NAD 83, NAVD 88.

15 GEOTHERMAL ENERGY↗
NASA NTRS1980

Tropical cyclone outer surface winds derived from satellite microwave sounder data

Upper tropospheric temperature anomalies are detected in brightness temperature data from the Nimbus 6 Scanning Microwave Spectrometer (SCAMS). Brightness temperature anomalies are related to surface pressure anomalies through the radiative transfer and hydrostatic equation. Surface wind speeds at outer radii are then estimated using the gradient wind equation and a shearing parameter. The method is first tested using simulated satellite data constructed from temperature, pressure and height data recorded by aircraft reconnaissance of four hurricanes. Wind speeds in the 80-95 kPa region are estimated with 2-3 m/sec accuracy. Next, 55.45 GHz SCAMS data over eight typhoons during 1975 are used to estimate the radii of 15.4 m/sec (30 kt) and 27.5 m/sec (50 kt) winds. Accuracies of about + or - 80 and + or - 70 km, respectively, are found. It is suggested that the technique be further tested using data from the Microwave Sounding Unit on board the TIROS-N and NOAA 6 satellites.

Kidder, S. Q.↗
DOE OSTI2025

Advanced Model Development for Large Eddy Simulation of Oxy-Combustion and Supercritical Carbon Dioxide Power Cycles

A joint experimental and numerical study is performed to observe the characteristics of a supercritical carbon dioxide turbulent mixing layer in the presence of strong nonlinearities in the thermodynamic and transport properties. A bespoke experimental setup is designed and employed for this purpose and provides insight into macroscopic mixing behavior. The mixing is experimentally observed using two techniques: shadowgraphy and spontaneous Raman scattering. Qualitative and quantitative intensity fields obtained via these techniques yield instantaneous and mean density data. Spanwise temperature data is also collected using analogue resistance temperature detectors. These measurements are used to quantify the level of mixed material within the field. The experimental data are supplemented by a companion high-fidelity numerical study. The numerical results are obtained through fully resolved, three-dimensional direct numerical simulation. The numerical dataset permits observation of the near-field mixing characteristics, which are difficult to measure experimentally due to the rapid dynamics and sharp thermophysical gradients in this area. Qualitative field visualizations are presented, followed by quantitative mixed material results and observations regarding thermodynamic property trends at select locations within the field. One-dimensional spectra of the turbulent kinetic energy and solenoidal dissipation are provided to observe the spectral characteristics of the flow. Reynolds stress anisotropy is analyzed graphically through anisotropy invariance maps (Lumley triangles). The mixing quantification, spectral data and anisotropy analysis of a flow at these thermodynamic conditions represent the main outcomes of the work.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Using pyrometry to identify porosity in additively manufactured structures

A method and apparatus for identifying porosity in a structure made by an additive manufacturing process in which a laser is scanned across layers of material to form the structure. Pyrometry data comprising images of the layers acquired during additive manufacturing of the structure is received. The pyrometry data is used to generate temperature data comprising estimated temperatures of points in the layers in the images of the layers. The temperature data is used to identify shapes fit to high temperature areas in the images of the layers. Conditions of the shapes fit to the high temperature areas in the images of the layers are identified. Outlier shapes are identified in the shapes fit to the high temperature areas in the images of the layers using the conditions of the shapes.

Mitchell, John A.↗
DOE OSTI2022

2-D Surface Temperature Simulation Data and Matlab Scripts

SAND2023-07249O The 2-D Surface Temperature Simulation Data and Matlab software can estimate 2D temperature fields from electrical measurements along the edge of the 2D domain. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Sjoberg, Carl Magnus↗