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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Stomatal conductance and leaf temperature raw data from Aug 2016-Nov 2017 at the B34 tower in Manaus, Brazil

This data package contains raw data from stomatal conductance and leaf temperature measurements from the B34 tower in Manaus, Brazil. The attached zip file contains two data files and two metadata files. Additional metadata, such as site information and equipment manuals, are included in the data package listed under Dataset Reference(s). Contact israelmdt@gmail.com if you need to use this dataset for additional information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Brady's Geothermal Field Distributed Temperature Sensing Data

This submission is an 8 day time history of vertical temperature measurements in Brady observation well 56-1 collected during the PoroTomo field experiment. The data was collected with a fiber-optic DTS system installed to a depth of 372 m below wellhead. DTS installation uses a double-loop set up. Data includes forward length and backward length temperature measurements.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Stomatal conductance and leaf temperature raw data from Aug 2016-Nov 2017 at the K34 tower in Manaus, Brazil

These are raw data from stomatal conductance and leaf temperature measurements from the NGEE-Tropics K34 tower in Manaus, Brazil. The attached zip file contains two data files and two metadata files. Related data packages, including additional metadata such as site information and equipment manuals, are included in the data package listed under Dataset Reference(s). Contact israelmdt@gmail.com if you need to use this dataset for additional information.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1982

Comparison of Orbiter STS-2 development flight instrumentation data with thermal math model predictions

Thermal performance verification of Reusable Surface Insulation (RSI) has been accomplished by comparisons of STS-2 Orbiter Flight Test (OFT) data with Thermal Math Model (TMM) predictions. The OFT data was obtained from Development Flight Instrumentation RSI plug and gap thermocouples. Quartertile RSI TMMs were developed using measured flight data for surface temperature and pressure environments. Reference surface heating rates, derived from surface temperature data, were multiplied by gap heating ratios to obtain tile sidewall heating rates. This TMM analysis resulted in good agreement of predicted temperatures with flight data for thermocouples located in the RSI, Strain Isolation Pad, filler bar and structure.

Norman, I.↗
NASA NTRS2013

The Relation Between Atmospheric Humidity and Temperature Trends for Stratospheric Water

We analyze the relation between atmospheric temperature and water vapor-a fundamental component of the global climate system-for stratospheric water vapor (SWV). We compare measurements of SWV (and methane where available) over the period 1980-2011 from NOAA balloon-borne frostpoint hygrometer (NOAA-FPH), SAGE II, Halogen Occultation Experiment (HALOE), Microwave Limb Sounder (MLS)/Aura, and Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) to model predictions based on troposphere-to-stratosphere transport from ERA-Interim, and temperatures from ERA-Interim, Modern Era Retrospective-Analysis (MERRA), Climate Forecast System Reanalysis (CFSR), Radiosonde Atmospheric Temperature Products for Assessing Climate (RATPAC), HadAT2, and RICHv1.5. All model predictions are dry biased. The interannual anomalies of the model predictions show periods of fairly regular oscillations, alternating with more quiescent periods and a few large-amplitude oscillations. They all agree well (correlation coefficients 0.9 and larger) with observations for higherfrequency variations (periods up to 2-3 years). Differences between SWV observations, and temperature data, respectively, render analysis of the model minus observation residual difficult. However, we find fairly well-defined periods of drifts in the residuals. For the 1980s, model predictions differ most, and only the calculation with ERA-Interim temperatures is roughly within observational uncertainties. All model predictions show a drying relative to HALOE in the 1990s, followed by a moistening in the early 2000s. Drifts to NOAA-FPH are similar (but stronger), whereas no drift is present against SAGE II. As a result, the model calculations have a less pronounced drop in SWV in 2000 than HALOE. From the mid-2000s onward, models and observations agree reasonably, and some differences can be traced to problems in the temperature data. These results indicate that both SWV and temperature data may still suffer from artifacts that need to be resolved in order to answer the question whether the large-scale flow and temperature field is sufficient to explain water entering the stratosphere.

Fueglistaler, S.↗
DOE OSTI2025

High temperature nuclear data measurements of SiC, ZrC, and MgO [Slides]

Performed temperature dependent measurements of SiC and ZrC at ARCS instrument at SNS. Performed temperature dependent measurements of SiC, ZrC, and MgO at VISION instrument at SNS. Performed initial atomistic modeling of these materials using various techniques, including machine learned potentials. Future work includes temperature dependent transmission measurements of these materials, as well as improving the machine learned potentials with more training data and different machine learned frameworks.

ARCS↗
NASA NTRS1972

Comparison of heat-transfer test data for a chordwise-finned, impingement-cooled turbine vane tested in a four-vane cascade and a research engine

The heat-transfer characteristics of a chordwise-finned, impingement-cooled vane were investigated in both a modified J-57 research engine and a four-vane cascade. The data were compared by a correlation of temperature difference ratio with coolant- to gas-flow ratio and also by two modifications of this correlation. The results indicated that the cascade vane temperature data can generally be used to represent the engine vane temperature data. A discussion of engine and cascade gas-side heat-transfer coefficients is also presented. A redesign of the vane leading edge could significantly increase the potential turbine-inlet temperature operating limit.

Gladden, H. J.↗
DOE OSTI2024

Machine learning snow depth predictions at sites in Alaska, Norway, Siberia, Colorado and New Mexico

Temporally continuous snow depth estimates are vital for understanding changing snow patterns in the Arctic and impacts on permafrost. We trained random forest machine learning models to predict snow depth from temperature data recorded at or just below the ground surface. Training data was collected at the Teller 27 Watershed and Kougarok 64 Hillslope during the 2021 - 2022 water year on the Seward Peninsula, Alaska using distributed temperature profiling (DTP) systems. We then applied this model to other sites where ground surface or shallow soil temperature data was available for at least one water year (see Related Datasets). Many of these temperature measurements were collocated with snow depth observations. Ground surface temperature (i.e. snow-ground interface temperature) is easy to measure using small, cheap and easy-to-deploy temperature sensors such as iButtons and TinyTags, and such measurements have previously been used to calculate a variety of snow metrics (e.g. snow onset date). However, this is the first study to estimate snow depth directly from ground surface temperature data. The present dataset contains one *.csv file which includes machine learning snow depth predictions at sites in Alaska, Norway, Siberia, Colorado, and New Mexico and one *.kml file including the locations of sites with snow depth predictions. No training data predictions are included in the *.csv 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 NTRS2018

An Initial Validation of Landsat 5 and 7 Derived Surface Water Temperature for U.S. Lakes, Reservoirs, and Estuaries

The United States Harmful Algal Bloom and Hypoxia Research Control Act of 2014 identified the need for forecasting and monitoring harmful algal blooms (HAB) in lakes, reservoirs, and estuaries across the nation. Temperature is a driver in HAB forecasting models that affects both HAB growth rates and toxin production. Therefore, temperature data derived from the U.S. Geological Survey Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper Plus thermal band products were validated across 35 lakes and reservoirs, and 24 estuaries. In situ data from the Water Quality Portal (WQP) were used for validation. The WQP serves data collected by state, federal, and tribal groups. Discrete in situ temperature data included measurements at 11,910 U.S. lakes and reservoirs from 1980 through 2015. Landsat temperature measurements could include 170,240 lakes and reservoirs once an operational product is achieved. The Landsat-derived temperature mean absolute error was 1.34 C in lake pixels (is) greater than180 m from land, 4.89 C at the land-water boundary, and 1.11 C in estuaries based on comparison against discrete surface in situ measurements. This is the first study to quantify Landsat resolvable U.S. lakes and reservoirs, and large-scale validation of an operational satellite provisional temperature climate data record algorithm. Due to the high performance of open water pixels, Landsat satellite data may supplement traditional in situ sampling by providing data for most U.S. lakes, reservoirs, and estuaries over consistent seasonal intervals (even with cloud cover) for an extended period of record of more than 35 years.

Schaeffer, Blake A.↗
DOE OSTI2018

An Updated Global Grid Point Surface Air Temperature Anomaly Data Set: 1851-1990 (revised 1991) (NDP-020)

This NDP presents land-based monthly surface-air-temperature anomalies (departures from a 1951-1970 reference period mean) on a 5° latitude by 10° longitude global grid. Monthly surface-air-temperature anomalies (departures from a 1957-1975 reference period mean) for the Antarctic (grid points from 65°S to 85°S) are presented in a similar way as a separate data set. The data were derived primarily from the World Weather Records and from the archives of the United Kingdom Meteorological Office. This long-term record of temperature anomalies may be used in studies addressing possible greenhouse-gas-induced climate changes. To date, the data have been employed in producing regional, hemispheric, and global time series for determining whether recent (i.e., post-1900) warming trends have taken place. The present updated version of this data set is identical to the earlier version for all records from 1851-1978 except for the addition of the Antarctic surface-air-temperature anomalies beginning in 1957. Beginning with the 1979 data, this package differs from the earlier version in several ways. Erroneous data for some sites have been corrected after a review of the actual station temperature data, and inconsistencies in the representation of missing values have been removed. For some grid locations, data have been added from stations that had not contributed to the original set. Data from satellites have also been used to correct station records where large discrepancies were evident. The present package also extends the record by adding monthly surface-air-temperature anomalies for the Northern (grid points from 85°N to 0°) and Southern (grid points from 5°S to 60°S) Hemispheres for 1985-1990. In addition, this updated package presents the monthly-mean-temperature records for the individual stations that were used to produce the set of gridded anomalies. The periods of record vary by station. Northern Hemisphere data have been corrected for inhomogeneities, while Southern Hemisphere data are presented in uncorrected form.For access to the data files, click this link to the CDIAC data transition website: http://cdiac.ess-dive.lbl.gov/ndps/ndp020.html

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Interpreting Temperature Strain Data from Meso-Scale Clathrate Experiments

Gas hydrates are important in global climate change, carbon sequestra- tion, and seafloor stability. Currently, formation and dissociation pathways are poorly defined. We present a new approach for processing large amounts of data from meso-scale experiments, such as the LUNA distributed sensing system (DSS) in the seafloor process simulator (SPS) at Oak Ridge National Laboratory. The DSS provides a proxy for temperature measurement with a high spatial resolution allowing the heat of reaction during gas hydrate formation/dissociation to aid in locating clathrates in the vessel. The DSS fibers are placed in the sediment following an Archimedean spiral design and then the position of each sensor is solved by iterating over the arc length formula with Newtons method. The data is then gridded with 1 a natural neighbor interpolation algorithm to allow contouring of the data. The solution of the sensor locations is verified with hot and cold stimulus in known locations. An experiment was preformed with a vertically split column of sand and silt. The DSS system clearly showed hydrate forming in the sand first, then slowly creeping into the silt. Similar systems and data processing techniques could be used for monitoring of hydrates in natural environments or in any situation where a hybrid temperature/strain index is useful. Further ad- vances in fiber technology allow the fiber to be applied in any configuration and the position of each sensor to be precisely determined making practical applications easier.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Utility of Bromide and Heat Tracers for Aquifer Characterization Affected by Highly Transient Flow Conditions

A tracer test using both bromide and heat tracers conducted at the Integrated Field Research Challenge site in Hanford 300 Area (300A), Washington, provided an instrument for evaluating the utility of bromide and heat tracers for aquifer characterization. The bromide tracer data were critical to improving the calibration of the flow model complicated by the highly dynamic nature of the flow field. However, most bromide concentrations were obtained from fully screened observation wells, lacking depth-specific resolution for vertical characterization. On the other hand, depth-specific temperature data were relatively simple and inexpensive to acquire. However, temperature-driven fluid density effects influenced heat plume movement. Moreover, the temperature data contained “noise” caused by heating during fluid injection and sampling events. Using the hydraulic conductivity distribution obtained from the calibration of the bromide transport model, the temperature depth profiles and arrival times of temperature peaks simulated by the heat transport model were in reasonable agreement with observations. This suggested that heat can be used as a cost-effective proxy for solute tracers for calibration of the hydraulic conductivity distribution, especially in the vertical direction. However, a heat tracer test must be carefully designed and executed to minimize fluid density effects and sources of noise in temperature data. A sensitivity analysis also revealed that heat transport was most sensitive to hydraulic conductivity and porosity, less sensitive to thermal distribution factor, and least sensitive to thermal dispersion and heat conduction. This indicated that the hydraulic conductivity remains the primary calibration parameter for heat transport.

Ma, Rui↗
NASA NTRS1990

Long duration exposure facility post-flight thermal analysis: Orbital/thermal environment data package

A post flight mission thermal environment for the Long Duration Exposure Facility was created as part of the thermal analysis data reduction effort. The data included herein is the thermal parameter data used in the calculation of boundary temperatures. This boundary temperature data is to be released in the near future for use by the LDEF principal investigators in the final analysis of their particular experiment temperatures. Also included is the flight temperature data as recorded by the LDEF Thermal Measurements System (THERM) for the first 90 days of flight.

Berrios, William M.↗
DOE OSTI2022

Low-Power, Flexible Sensor Arrays with Solderless Board-to-Board Connectors for Monitoring Soil Deformation and Temperature: Supporting Data

This dataset was used to assess the potential of a Soil Deformation and Temperature Monitoring System developed and presented in the article named "Low-Power, Flexible Sensor Arrays with Solderless Board-to-Board Connectors for Monitoring Soil Deformation and Temperature" and published in Sensors. There are 21 comma-delimited data files (.csv). 14 files contain current measurements performed in a lab setting, enabling the electrical evaluation of the sensor probe. These files are generated by the Keithley DMM6500 multimeter, and list the measured supply current (first column) as a function of time (3rd column). Another set of 6 files is also acquired in lab experiments, but contain soil temperature an deformation measurements, enabling an assessment of the developed device's accuracy. 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 5 seconds. Another .csv file contains field data in a similar format (time, temperature, acceleration) collected at the Teller road (mile 27) site near Nome, Alaska with one probe. 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↗
DOE OSTI2015

Using Bayesian Inference Framework towards Identifying Gas Species and Concentration from High Temperature Resistive Sensor Array Data

High temperature gas sensors have been highly demanded for combustion process optimization and toxic emissions control, which usually suffer from poor selectivity. In order to solve this selectivity issue and identify unknown reducing gas species (CO, CH 4 , and CH 8 ) and concentrations, a high temperature resistive sensor array data set was built in this study based on 5 reported sensors. As each sensor showed specific responses towards different types of reducing gas with certain concentrations, based on which calibration curves were fitted, providing benchmark sensor array response database, then Bayesian inference framework was utilized to process the sensor array data and build a sample selection program to simultaneously identify gas species and concentration, by formulating proper likelihood between input measured sensor array response pattern of an unknown gas and each sampled sensor array response pattern in benchmark database. This algorithm shows good robustness which can accurately identify gas species and predict gas concentration with a small error of less than 10% based on limited amount of experiment data. These features indicate that Bayesian probabilistic approach is a simple and efficient way to process sensor array data, which can significantly reduce the required computational overhead and training data.

Liu, Yixin↗
NASA NTRS2000

Long-term Global Morphology of Gravity Wave Activity Using UARS Data

This quarter was largely devoted to a detailed study of temperature data acquired by the Cryogenic Limb Array Etalon Spectrometer (CLAES) on UARS. Our analysis used the same sequence of methods that have been developed, tested and refined on a more limited subset of temperature data acquired by the CRISTA instrument. We focused on a limited subset of our reasoning that geographical and vertical trends in the small-scale temperature variability could be compared with similar trends observed in November 1994 by the CRISTA-SPAS satellite. Results, backed up with hindcasts from the Mountain Wave Forecast Model (MWFM), reveal strong evidence of mountain waves, most persuasively in the Himalayas on 16-17 November, 1992. These CLAES results are coherent over the 30-50 km range and compare well with MWFM hindcasts for the same period. This constitutes, we believe, the first clear evidence that CLAES explicitly resolved long wavelength gravity waves in its CO2 temperature channel. A series of other tasks, related to mesoscale modeling of mountain waves in CRISTA data and fitting of ground-based and HRDI data on global scales, were seen through to publication stage in peer-reviewed journals.

Eckermann, Stephen D.↗