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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

How does humidity data impact land surface modeling of hydrothermal regimes at a permafrost site in Utqia$\mathrm{\dot{g}}$vik, Alaska?

Humidity is a basic and crucial meteorological indicator commonly measured in several forms, including specific humidity, relative humidity, and absolute humidity. These different forms can be inter-derived based on the saturation vapor pressure (SVP). In past decades, dozens of formulae have been developed to calculate the SVP with respect to, and in equilibrium with, liquid water and solid ice surfaces, but many prior studies use a single function for all temperature ranges, without considering the distinction between over the liquid water and ice surfaces. These different approaches can result in humidity estimates that may impact our understanding of surface-subsurface thermal-hydrological dynamics in cold regions. In this study, we compared the relative humidity (RH) downloaded and calculated from four data sources in Alaska based on five commonly used SVP formulas. These RHs, along with other meteorological indicators, were then used to drive physics-rich land surface models at a permafrost-affected site. Here, we found that higher values of RH (up to 40%) were obtained if the SVP was calculated with the over-ice formulation when air temperatures were below freezing, which could lead to a 30% maximum difference in snow depths. The choice of whether to separately calculate the SVP over an ice surface in winter also produced a significant range (up to 0.2 m) in simulated annual maximum thaw depths. The sensitivity of seasonal thaw depth to the formulation of SVP increases with the rainfall rate and the height of above-ground ponded water, while it diminishes with warmer air temperatures. These results show that RH variations based on the calculation of SVP with or without over-ice calculation meaningfully impact physically-based predictions of snow depth, sublimation, soil temperature, and active layer thickness. Under particular conditions, when severe flooding (inundation) and cool air temperatures are present, care should be taken to evaluate how humidity data is estimated for land surface and earth system modeling.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1982

Calculation of composition distribution of ultrafine ion-H2O-H2SO4 clusters using a modified binary ion nucleation theory

Thomson's ion nucleation theory was modified to include the effects of curvature dependence of the microscopic surface tension of field dependent, nonlinear, dielectric properties of the liquid; and of sulfuric acid hydrate formation in binary mixtures of water and sulfuric acid vapors. The modified theory leads to a broadening of the ion cluster spectrum, and shifts it towards larger numbers of H2O and H2SO4 molecules. Whether there is more shifting towards larger numbers of H2O or H2SO4 molecules depends on the relative humidity and relative acidity of the mixture. Usually, a broadening of the spectrum is accompanied by a lowering of the mean cluster intensity. For fixed values of relative humidity and relative acidity, a similar broadening pattern is observed when the temperature is lowered. These features of the modified theory illustrate that a trace of sulfuric acid can facilitate the formation of ultrafine, stable, prenucleation ion clusters as well as the growth of the prenucleation ion clusters towards the critical saddle point conditions, even with low values of relative humidity and relative acidity.

Singh, J. J.↗
DOE OSTI2024

A Global Increase in Nearshore Tropical Cyclone Intensification

Abstract Tropical Cyclones (TCs) inflict substantial coastal damages, making it pertinent to understand changing storm characteristics in the important nearshore region. Past work examined several aspects of TCs relevant for impacts in coastal regions. However, few studies explored nearshore storm intensification and its response to climate change at the global scale. Here, we address this using a suite of observations and numerical model simulations. Over the historical period 1979–2020, observations reveal a global mean TC intensification rate increase of about 3 kt per 24‐hr in regions close to the coast. Analysis of the observed large‐scale environment shows that stronger decreases in vertical wind shear and larger increases in relative humidity relative to the open oceans are responsible. Further, high‐resolution climate model simulations suggest that nearshore TC intensification will continue to rise under global warming. Idealized numerical experiments with an intermediate complexity model reveal that decreasing shear near coastlines, driven by amplified warming in the upper troposphere and changes in heating patterns, is the major pathway for these projected increases in nearshore TC intensification.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

NLR HPC Facility Power Usage Effectiveness (PUE) Data

Timeseries of Energy Systems Integration Facility (ESIF) Data Center Power Usage Effectiveness (PUE) Data provided in Parquet and compressed CSV formats Power Metrics Timeseries Fields: ts: Timestamp cooling_kw: Cooling (kilowatts) - Captures the power used by fans and pipe trace heaters associated with outdoor cooling equipment. The dedicated tower filter pump power is also captured as cooling load. energy_reuse: Energy Reuse Effectiveness hvac_kw: Heating, ventilation, and air conditioning (kilowatts) - Captures fan walls, fan coils that support the data center electrical rooms, and the make-up air unit. it_power_kw: IT equipment (kilowatts) - Captures power used by the IT equipment on the data center floor. plug_and_light_kw: Lights and utility plugs (kilowatts) - Captures power associated with the data center and dedicated mechanical room. The crank-case heater for the emergency standby generator is also captured as light and plug load. pue: Power Usage Effectiveness pump_kw: Pumps (kilowatts) - Captures power from pumps that move water in the data center Energy Recover Water loop and the Tower Water loops, and also captures power used by the boost pumps that circulate water through the fan walls. Note: The tower filter pump runs constantly to filter water from the data center cooling tower system, so 2.67 kilowatts are attributed to this pump and that is not reflected in this data field. day: Day of month Outside Weather Station Timeseries Fields: ts: Timestamp outside_air_humidity: Outside air humidity - Relative humidity percent outside_air_temp: Outside air temperature - Degrees Fahrenheit day: Day of month More detail: High-Performance Computing Data Center Power Usage Effectiveness

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Combined Mesonet and Tracker

Title: Combined Mesonet and Trackers (UNL Mobile Mesonets) Authors University of Nebraska PI: Adam Houston, UNL Professor (ahouston2@unl.edu) Mailing Address: 126 Bessey Hall P.O. Box 880340 Lincoln, NE 68588-0340 CoMeT Overview The University of Nebraska-Lincoln operates three Combined Mesonet and Tracker (CoMeTs). CoMeTs are Ford Explorers (model years 2015, 2017, and 2019) with forward-mounted suites of meteorological sensors and dual moonroofs, combining the capability of a mobile mesonet to collect near-surface observations with the capability of an unmanned aircraft systems (UAS) tracker vehicle, which enables an observer in the second row of seats to see the aircraft and maintain compliance with Federal Aviation Administration policies on UAS operation. The CoMeTs collect observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155A, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, and vehicle heading using a KVH Industries C-100 fluxgate compass (Barbieri et al. 2019). The HMP155A and 109SS-L thermistor are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). This list of sensors is also included in the CoMeT data file metadata. Manufacturer specifications for these instruments are given in Table 1 of Hanft and Houston (2018). The reported measured quantities are summarized below.CoMeT-3 was funded through an equipment allocation included in the NSF TORUS award (AGS-1824649). Instrument Description The specific sensors included on each CoMeT are summarized in the table at the end of this section. In general each CoMeT collects observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210 barometer with a Gill pressure port, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, position using a Garmin 19x HVS receiver, and vehicle heading using a KVH Industries C-100 fluxgate compass. The HMP155 and 109SS are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). Fast temperature and corrected RH measurements (using sensors housed within the U-tube) have a time constant of 10-12 s based on data collected across a temperature and RH shock during the CLOUD-MAP 2017 calibration/validation tests on June 26, 2017. Vehicle speed was < 10 kts for this test. CoMeT-1 CoMeT-2 CoMeT-3 Slow Temperature Slow RH Vaisala HMP155A-L20-PT Part #: 22280-7 Vaisala HMP155E Part #: E1AA11A0B1A1A0A Vaisala HMP155E Part #: E1AA11A0B1A1A0A Fast temperature Campbell Scientific 109SS-L20-PT Part #: 21448-3 Campbell Scientific 109SS-L12-PW Part #: 21448-109 Campbell Scientific 109SS-L12-PW Part #: 21448-150 Pressure Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Wind RM Young 05103-L20-PT Part #: 18435-310 RM Young 05103-L20-PW Part #: 18435-244 RM Young 05103-L20-PW Part #: 18435-244 GPS Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Compass KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 Logger Campbell Scientific CR6-NA-XT-SW Part #: 28385-9 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Data Collection and Real-Time Processing The reported measured quantities are summarized in the table below. Quantity Units Source Epoch time Seconds GPS Latitude and longitude Degrees GPS Altitude m GPS Pressure hPa PTB210 Temperature (fast) deg C 109SS-L Temperature (slow) deg C HMP155 RH (slow) % HMP155 Vehicle speed m/s GPS Vehicle heading deg C-100 and GPS In addition to the measured variables, several derived variables are calculated. Corrected/fast relative humidity (%) Relative humidity is adjusted to the fast temperature following Richardson et al. (1998) and Houston et al. (2016). Water vapor mixing ratio (g/kg) Dew point temperature (&deg;C) Potential temperature (Kelvin) Virtual potential temperature (Kelvin) Equivalent potential temperature (Kelvin) Regular intercomparisons between all three CoMeTs were performed during TORUS 2019. Comparisons were also conducted between CoMeT-1 and CoMeT-2 during LAPSE-RATE (2018) on 14 July. In these intercomparisons, the vehicles were parked adjacent to each other aligned perpendicular to (and facing into) the wind. To minimize engine heating effects, intercomparisons were only conducted when the wind speed was >10 kts. Data Format Original data files for each deployment are saved as text files and then converted to NetCDF. NetCDF versions have units that are CF compliant and may not match the original units in the txt files. The naming convention for the NetCDF files is as follows: UNL.CoMeT3.{deployment date YYYYMMDD}.{start time of observation collection in UTC HHMM}.L2.{post-processing codes}.cdf example: UNL.CoMeT3.20190627.1931.L2.g1.f1.cdf Post-processing codes are included to track modifications to the raw data. These codes are closely connected to error flags associated with each record. Each letter corresponds to a particular instrument: g: GPS p: Barometer tf: Fast temperature ts: Slow temperature rh: Relative humidity f: Compass w: Wind monitor a: All instruments Each number corresponds to a particular post-processing action described more below. Measured and derived variables are included in the following table. Variable Heading Standard Name Units time Time seconds since 00:00:00, 01-01-1970 Alt Altitude meters lat Latitude degrees north lon Longitude degrees east fast_temp Air Temperature kelvin slow_temp Air Temperature kelvin pressure Air Pressure pascals logger_RH Relative Humidity percent calc_corr_RH Relative Humidity percent wind_speed Wind Speed meters per second wind_dir Wind From Direction degrees vehicle_dir Vehicle Direction degrees dewpoint Dew Point Temperature kelvin mixing_ratio Humidity Mixing Ratio g/g theta Air Potential Temperature kelvin theta_v Virtual Potential Temperature kelvin theta_e Equivalent Potential Temperature Kelvin error_flag The error_flag variable is a string that matches the post-processing codes listed above. All instruments will have an associated code, but will have a &ldquo;0&rdquo; if the datum is unchanged from the initial processed value. Error Codes The following table summarizes the error codes for data collected before 2020: Error Code Relevant CoMeT Description g1 1,2,3 Exact correction. GPS position and time reprocessed from raw data g2 1 As far as we can tell this is an exact correction to an error in the GPS time. During the correct time periods the time suddenly went backwards ~250s and stayed at this offset for 750s when it corrected itself. The offset was applied to the &ldquo;time warp&rdquo; period. p1 2 Approximate correction. Hole in the pressure tube connecting the pressure port to the barometer. Resulted in erroneously low air pressure measurements when the vehicle was in motion. Derived variables recalculated (dew point temperature [e depends on qv and p], water vapor mixing ratio, potential temperature, virtual potential temperature, equivalent potential temperature) a1 3 Exact correction. Missing data reprocessed from raw data a2 1 Bug fix to bias correction for ts1, ts2, and rh1: water vapor mixing ratio was off by a factor of 10 and virtual potential temperature was wrong because of this. f1 3 No correction, missing data. Fluxgate compass inoperable. Wind speed and direction calculated using GPS-derived vehicle heading instead. rh1 1 Approximate correction. Constant bias of +1.7% removed from relative humidity. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts1 1 Approximate correction. Constant bias of +0.6 K removed from slow temperature. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts2 1 Approximate correction. Constant bias of +1.0 K removed. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) References Bolton, D., 1980: The Computation of Equivalent Potential Temperature. Mon. Wea. Rev., 108, 1046&ndash;1053, https://doi.org/10.1175/1520-0493(1980)108<1046:TCOEPT>2.0.CO;2. Hanft, W., and A. L. Houston, 2018: An Observational and Modeling Study of Mesoscale Air Masses with High Theta-E. Mon. Wea. Rev., 146, 2503&ndash;2524, https://doi.org/10.1175/MWR-D-17-0389.1.Wexler Houston, A. L., R. J. Laurence III, T. W. Nichols, S. Waugh, B. Argrow, and C. L. Ziegler, 2016: Intercomparison of unmanned aircraft-borne and mobile mesonet atmospheric sensors. Journal of Atmospheric and Oceanic Technology. 33, 1569-1582, doi: 10.1175/JTECH-D-15-0178.1. Lowe, P. R., 1977: An Approximating Polynomial for the Computation of Saturation Vapor Pressure. J. Applied Meteorology, 16, 100&ndash;103. Richardson, S. J., S. E. Frederickson, F. V. Brock, and J. A. Brotzge, 1998: Combination temperature and relative humidity probes: Avoiding large air temperature errors and associated relative humidity errors. Preprints, 10th Symp. On Meteorological Observations and Instrumentation, Phoenix, AZ, Amer. Meteor. Soc., 278&ndash;283. Waugh, S., and S. E. Frederickson, 2010: An improved aspirated temperature system for mobile meteorological observations, especially in severe weather. 25th Conf. on Severe Local Storms, Denver, CO, Amer. Meteor. Soc., P5.2. [Available online at https://ams.confex.com/ams/25SLS/techprogram/paper_176205.htm.]

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Friction and Wear Properties of Selected Solid Lubricating Films: Magnetron-Sputtered and Plasma-Assisted, Chemical-Vapor-Deposited Diamondlike Carbon Films - Part 3

To evaluate commercially developed dry solid film lubricants for aerospace bearing applications, an investigation was conducted to examine the friction and wear behavior of magnetron-sputtered diamondlike carbon (MS DLC) and plasma-assisted, chemical-vapor-deposited diamondlike carbon (PACVD DLC) films in sliding contact with 6-mm-diameter American Iron and Steel Institute (AISI) 440C stainless steel balls. Unidirectional sliding friction experiments were conducted with a load of 5.9 N (600 g), a mean Hertzian contact pressure of 0.79 GPa (maximum Hertzian contact pressure of L-2 GPa), and a sliding velocity of 0.2 m/s. The experiments were conducted at room temperature in three environments: ultrahigh vacuum (vacuum pressure, 7x10(exp -7) Pa), humid air (relative humidity, approx.20 percent), and dry nitrogen (relative humidity, <1 percent). The resultant films were characterized by scanning electron microscopy, energy-dispersive x-ray spectroscopy, and surface profilometry. Marked differences in the friction and wear of the DLC films investigated herein resulted from the environmental conditions. The main criteria for judging the performance of the DLC films were coefficient of friction and wear rate, which had to be less than 0.3 and on the order of 10(exp -6) cu mm/N-m or less, respectively. MS DLC films and PACVD DLC films met the criteria in humid air and dry nitrogen but failed in ultrahigh vacuum, where the coefficients of friction were greater than the criterion, 0.3. In sliding contact with 440C stainless steel balls in all three environments the PACVD DLC films exhibited better tribological performance (i.e., lower friction and wear) than the MS DLC films. All sliding involved adhesive transfer of wear materials: transfer of DLC wear debris to the counterpart 440C stainless steel and transfer of 440C stainless steel wear debris to the counterpart DLC film.

Miyoshi, Kazuhisa↗
NASA NTRS2000

Friction and Wear Properties of Selected Solid Lubricating Films: Ion-Plated Lead Films - Part 2

To evaluate commercially developed dry solid film lubricants for aerospace bearing applications, an investigation was conducted to examine the friction and wear behavior of ion-plated lead films in sliding contact with 6-mm-diameter American Iron and Steel Institute (AISI) 440C stainless steel balls. Unidirectional sliding friction experiments were conducted with a load of 5.9 N (600 g), a mean Hertzian contact pressure of 0.79 GPa (maximum Hertzian contact pressure of 1.2 GPa), and a sliding velocity of 0.2 m/s. The experiments were conducted at room temperature in three environments: ultrahigh vacuum (vacuum pressure, 7 x 10(exp -7 Pa), humid air (relative humidity, approx. 20 percent), and dry nitrogen (relative humidity, less then 1 percent). The resultant films were characterized by scanning electron microscopy, energy-dispersive X-ray spectroscopy, and surface profilometry. Marked differences in the friction and wear of the ion-plated lead films investigated herein resulted from the environmental conditions. The main criteria for judging the performance of the ion-plated lead films were coefficient of friction and wear rate, which had to be less than 0.3 and on the order of 1(exp -6) cu mm/N.m or less, respectively. The ion-plated lead films met both criteria only in ultrahigh vacuum but failed in humid air and in dry nitrogen, where the coefficient of friction was higher than the criterion. Both the lead film wear rate and the ball wear rate met that criterion in all three environments. Adhesion and plastic deformation played important roles in the friction and wear of the ion-plated lead films in contact with 440C stainless steel balls in the three environments. All sliding involved adhesive transfer of materials: transfer of lead wear debris to the counterpart 440C stainless steel and transfer of 440C stainless steel wear debris to the counterpart lead.

Miyoshi, Kazuhisa↗
NASA NTRS2001

Evaluation of Selected Solid Lubricating Films

An investigation was conducted to examine the friction and wear properties of bonded molybdenum disulfide (MoS2), magnetron-sputtered MoS2, ion-plated silver, ion-plated lead, magnetron-sputtered diamondlike carbon (MS DLC), and plasma-assisted, chemical-vapor-deposited DLC (PACVD DLC) films in sliding contact with 6-mm-diameter AISI 440C stainless steel balls. Unidirectional ball-on-disk sliding friction experiments were conducted with a load of 5.9 N and a sliding velocity of 0.2 m/s at room temperature in three environments: ultrahigh vacuum (vacuum pressure, 7 x 10(exp -7) Pa), humid air (relative humidity, approx. 20 percent), and dry nitrogen (relative humidity, less than 1 percent). The main criteria for judging the performance of the solid lubricating films were coefficient of friction and wear rate, which had to be less than 0.3 and on the order of 10(exp -6) cubic mm/N(dot)m or less, respectively. The bonded MoS2 and magnetron-sputtered MoS2 films met the criteria in all three environments. The ion-plated lead and silver films met the criteria only in ultrahigh vacuum but failed in humid air and in dry nitrogen. The MS DLC and PACVD DLC films met the requirements in humid air and dry nitrogen but failed in ultrahigh vacuum.

Miyoshi, Kazuhisa↗
NASA NTRS2001

Durability Evaluation of Selected Solid Lubricating Films

An investigation was conducted to examine the coefficients of friction, wear rates, and durability of bonded molybdenum disulfide (MoS2), magnetron-sputtered MoS2, ion-plated silver, ion-plated lead, magnetron-sputtered diamondlike carbon (MS DLC), and plasma-assisted, chemical-vapor-deposited DLC (PACVD DLC) films in sliding contact with 6-mm-diameter AISI 440C stainless steel balls. Unidirectional ball-on-disk sliding friction experiments were conducted with a load of 5.9 N and a sliding velocity of 0.2 m/s at room temperature in three environments: ultrahigh vacuum (vacuum pressure, 7 x 10(exp -7) Pa), humid air (relative humidity, approx. 20 percent), and dry nitrogen (relative humidity, less than 1 percent). The main criteria for judging the performance of the solid lubricating films were coefficient of friction and wear rate, which had to be less than 0.3 and on the order of 10(exp -6) cu mm/N.m or less, respectively. The bonded MoS2 and magnetron-sputtered MoS2 films met the criteria in all three environments. The ion-plated lead and silver films met the criteria only in ultrahigh vacuum but failed in humid air and in dry nitrogen. The MS DLC and PACVD DLC films met the requirements in humid air and dry nitrogen but failed in ultrahigh vacuum.

Miyoshi, Kazuhisa↗