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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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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Velocity and Temperature Measurements in High-speed Flows with Naturally Present Dust Particles Using Rayleigh and Mie Scattering

Dust particles and occasional moisture condensations are unavoidable reality of all wind tunnels. On the path to pursue a goal of velocity and temperature measurements in high-speed wind tunnels we have created a tabletop, spectrally resolved, Rayleigh-Mie scattering setup around a small jet fed by ambient and air with different particle concentration to determine the accuracy of the technique. The other reality of a wind tunnel setup is the spurious reflection and scattering of the incident laser beam by solid surfaces (flare light), which contaminates the Rayleigh-Mie scattered light. This is simulated by backgrounds with different reflectivity towards the collection optics. Light from a CW laser is delivered via an optical fiber and the scattered light from a point on the laser path is spectrally resolved using a stabilized Fabry-Perot interferometer, followed by imaging on an EMCCD camera. A model of the combined background glare, Mie scattering, and the Rayleigh spectrum was fitted to the camera image using maximum likelihood estimation. It was observed that the present modeling approach can extract velocity and temperature with reasonable accuracy when the intensity of the Mie scattered light is less than or comparable to that of the Rayleigh scattered light; beyond that error in velocity measurement remains reasonable ±12m/s but the temperature measurement becomes progressively more inaccurate. Increasingly the flare light is found to cause a bias error in velocity. Similar trend is observed in the presence of both the flare light and the Mie scattered light. The setup has provided a set of data for the future improvement of the modeling procedure, and demonstrated that even in the case of large amount of dust particles and large flare light the present technique can provide measurement of velocity with reasonable accuracy.

Rayleigh scattering↗
NASA NTRS1986

Further development of the dynamic gas temperature measurement system. Volume 2: Computer program user's manual

The Dynamic Gas Temperature Measurement System compensation software accepts digitized data from two different diameter thermocouples and computes a compensated frequency response spectrum for one of the thermocouples. Detailed discussions of the physical system, analytical model, and computer software are presented in this volume and in Volume 1 of this report under Task 3. Computer program software restrictions and test cases are also presented. Compensated and uncompensated data may be presented in either the time or frequency domain. Time domain data are presented as instantaneous temperature vs time. Frequency domain data may be presented in several forms such as power spectral density vs frequency.

Stocks, Dana R.↗
NASA NTRS2001

Lidar Temperature Measurements During the SOLVE Campaign and the Absence of PSCs from Regions of Very Cold Air

NASA Goddard Space Flight Center's Airborne Raman Ozone, Temperature and Aerosol Lidar (AROTEL) measured extremely cold temperatures during all three deployments (December 1-16, 1999, January 14-29, 2000 and February 27-March 15, 2000) of the Sage III Ozone Loss and Validation Experiment (SOLVE). Temperatures were significantly below values observed in previous years with large regions regularly below 191 K and frequent temperature retrievals yielding values at or below 187 K. Temperatures well below the saturation point of type I polar stratospheric clouds (PSCs) were regularly encountered but their presence was not well correlated with PSCs observed by the NASA Langley Research Center's Aerosol Lidar co-located with AROTEL. Temperature measurements by meteorological sondes launched within areas traversed by the DC-8 showed minimum temperatures consistent in time and vertical extent with those derived from AROTEL data. Calculations to establish whether PSCs could exist at measured AROTEL temperatures and observed mixing ratios of nitric acid and water vapor showed large regions favorable to PSC formation. On several occasions measured AROTEL temperatures up to 10 K below the NAT saturation temperature were insufficient to produce PSCs even though measured values of nitric acid and water were sufficient for their formation.

Burris, John↗
DOE OSTI2024

iButton and Tinytag snow temperature measurements at Teller 27 and Kougarok 64, Seward Peninsula, Alaska, 2021-2022

Snow temperature measurements were collected at the NGEE Arctic Teller Road Site at mile marker 27 (TL_MM27) and at the Kougarok Road Site at mile marker 64 (KG_MM64) on the Seward Peninsula. Data were collected from October 1, 2021 to August 16, 2022 using iButton Link DS1926-F5# Thermochron miniature temperature sensors (https://www.ibuttonlink.com/products/ds1921g) and Tinytag TGP-4017 internal sensors (https://www.micronmeters.com/product/tgp-4017-internal-sensor-40-to-85-c-40-f-to-185-f) deployed across the Kougarok and Teller sites. These sensors are a cost-efficient way to collect snowpack temperatures at a higher spatial resolution than what is normally achieved. iButton data were collected every 4 hours beginning on October 1, 2021. Tinytag data collection began between October 9 and October 12, 2021 depending on sensor installation date. Tinytag data were collected every 30 minutes. In total, data were collected from 236 iButtons and 30 Tinytags. This dataset contains four *.csv files of near-ground surface temperatures at various locations throughout each study site and four *.shp files of sensor locations. Data were collected throughout the snow cover season so that snowpack characteristics could be derived using the temperature data. Sensors were placed both inside and outside of vegetation to better capture the spatial variability of snow properties across each domain. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), 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 OSTI2024

iButton snow temperature measurements at Teller 27 and Kougarok 64, Seward Peninsula, Alaska, 2019-2020

Snow temperature measurements were collected at the NGEE Arctic Teller Road Site at mile marker 27 (TL_MM27) and at the Kougarok Road Site at mile marker 64 (KG_MM64) on the Seward Peninsula. Data were collected from October 1, 2021 to August 16, 2022 using iButton Link DS1926-F5# Thermochron miniature temperature sensors (https://www.ibuttonlink.com/products/ds1921g) and Tinytag TGP-4017 internal sensors (https://www.micronmeters.com/product/tgp-4017-internal-sensor-40-to-85-c-40-f-to-185-f) deployed across the Kougarok and Teller sites. These sensors are a cost-efficient way to collect snowpack temperatures at a higher spatial resolution than what is normally achieved. iButton data were collected every 4 hours beginning on October 1, 2021. Tinytag data collection began between October 9, 2021 and October 12, 2021 depending on the specific Tinytag and data were collected every 30 minutes. In total, data were collected from 236 iButtons and 30 Tinytags. This dataset contains four *.csv files of near-ground surface temperatures at various locations throughout each study site and four *.shp files of sensor locations. Data were collected throughout the snow cover season so that snowpack characteristics could be derived using the temperature data. Sensors were placed both inside and outside of vegetation to better capture the spatial variability of snow properties across each domain.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) 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 NTRS1985

Further development of the dynamic gas temperature measurement system

Two experiments for verifying the frequency response of a previously-developed dynamic gas temperature measurement system were performed. In both experiments, fine-wire resistance temperature sensors were used as standards. The compensated dynamic temperature sensor data will be compared with the standards to verify the compensation method. The experiments are described in detail.

Elmore, D. L.↗
NASA NTRS1974

Atmospheric temperature measurements, using Raman lidar

The Raman-shifted return of a lidar system had been used to make atmospheric temperature measurements. The measurements were made along a horizontal path at temperatures ranging from -30 to 30 C and at ranges of about 100 meters. The temperature data were acquired by recording the intensity ratio of two portions of the rotational Raman spectrum, which were simultaneously sampled from a preset range. These tests verified that the theoretical predictions formulated in the design of the system were adequate. Measurements were made to an accuracy of + or - 4 C with 1-minute temporal resolution.

Salzman, J. A.↗
NASA NTRS1995

Apparatus Would Measure Temperatures Of Ball Bearings

Rig for testing ball bearings under radial and axial loads and measuring surface temperatures undergoing development. Includes extensible thermocouples: by means of bellows as longitudinal positioners, thermocouples driven into contact with bearing balls to sense temperatures immediately after test run. Not necessary to disassemble rig or to section balls to obtain indirect indications of maximum temperatures reached. Thermocouple measurements indicate temperatures better than temperature-sensitive paints.

Gibson, John C.↗
NASA NTRS1981

Calculation of atmospheric loss from microwave radiometric noise temperature measurements

Microwave propagation loss in the atmosphere can be inferred from microwave radiometric noise temperature measurements. The relevant equations are given and a derivation and calculation is made assuming various physical models. Comparison is made with the commonly used lumped element atmospheric model (isothermal and uniform loss) and the model with linear temperature and exponential loss distributions. The results are useful for estimating the integral inversion differences due to the model selection. This indicates that the commonly used lumped element atmospheric model is a very good approximation with judicious choice of the effective physical temperature. For the worst case comparison, the lumped element model agrees with the variable parameter model within 0.2 dB up to a propagation loss of 3 dB.

Stelzried, C.↗
NASA NTRS2000

Core Temperature Measurement During Submaximal Exercise: Esophageal, Rectal, and Intestinal Temperatures

The purpose of this study was to determine if intestinal temperature (Tin) might be in acceptable alternative to esophageal (Tes) and rectal temperature (Trec) to assess thermoregulation during supine exercise. We hypothesized that Tin would have values similar to Tes and a response time similar to Trec, but the rate of temperature change across time would not be different between measurement sites. Seven subjects completed a continuous supine protocol of 20 min of rest, 20 min of cycle exercise at 40% peak oxygen consumption (VO2pk), 20 min of cycle exercise at 65% V02pk, and 20 min of recovery. Tes, Trec, and Tin were recorded each min throughout the test. Temperatures were not different after 20 min of rest, but Trec was less than the Tes and Tin at the end of the 40% and 65% VO2pk stages. After 20 min of recovery, Tes was less than either Trec or Tin, which were not different from each other. Time to threshold for increased temperature from rest was greater for Trec than Tes but not different from Tin. Time to reach peak temperature was greater for Tin and Trec than Tes. Similarly, time to a decrease in temperature after exercise was greater for Trec than Tes, but not different from Tin. The rate of temperature change from threshold to the end of the 40% VO2pk stage was not different between measurement sites. However, the rate of change during recovery was more negative for Tes than Tin and Trec, which were different from each other. Measurement of Tin may he an acceptable alternative to Tes and Trec with an understanding of its limitations.

Lee, Stuart M. C.↗
NASA NTRS1987

How close are ground-based Fabry-Perot thermospheric wind and temperature measurements to exospheric values? A simulation study

A computer simulation model of the measurement process for a ground-based Fabry-Perot interferometer (FPI) has been developed and used to study how variations of wind and temperature along the instrument line-of-sight affect the Doppler shift and width of the observed nightglow O(1D) emission line at high spectral resolution. Ground-based-derived temperatures in the nighttime sector of the winter hemisphere are found to give values that are representative of the peak O(1D) emission altitude. However, when the vertical temperature gradients are large, the ground-based FPI temperature measurement may differ by as much as about 12 percent from the temperature at the peak emission height. Simulations of the FPI measurement of nighttime thermospheric temperatures show that ground-based-derived temperatures may be lower by about 10 percent than the corresponding exospheric temperatures in the winter hemisphere and by about 15 percent in the summer hemisphere.

Mccormac, F. G.↗
NASA NTRS2018

PIV and Rotational Raman-Based Temperature Measurements for CFD Validation in a Single Injector Cooling Flow

NASA's Turbulent Heat Flux (THX) task under the Transformational Tools & Technologies project is focused on acquiring benchmark temperature and velocity data in turbulent shear layers for validation of computational fluid dynamics (CFD) codes. Standard CFD turbulence models lack the ability to accurately calculate a number of fundamental flow phenomena, including the turbulent transport of heat. In nearly all production class Reynolds-averaged Navier-Stokes (RANS) CFD codes, a gradient-diffusion approximation is used whereby a constant turbulent Prantdl number, Prt, is used to relate an eddy viscosity calculated for the momentum terms, to the turbulent heat flux terms. The default in most CFD codes is Prt = 0.9, however this is not representative of all flows. As discussed in Yoder et al. (2015) and Reynolds (1974), Prt = 0.7 is felt to be more appropriate for jets. Recent work, as discussed in Yoder (2016a), has explored more complex formulations including variable turbulent Prantdl number models. PARTICLE IMAGE VELOCIMETRY; TEMPERATURE MEASURING INSTRUMENTS; FILM COOLING; HIGH TEMPERATURE GASES; COMPUTATIONAL FLUID DYNAMICS; PREDICTION ANALYSIS TECHNIQUES; TURBULENCE MODELS; RAMAN SPECTRA; VELOCITY; MACH NUMBER; GAS TURBINE ENGINES; NOZZLE FLOW; THERMOCOUPLES; LASER INDUCED FLUORESCENCE; COOLING FLOWS (ASTROPHYSICS); RAMAN SPECTROSCOPY; HEAT FLUX

Wernet, Mark P.↗