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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 (°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 “0” 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 “time warp” 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, 1046–1053, 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, 2503–2524, 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, 100–103. 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., 278–283. 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 NTRS1998

Model Engine Performance Measurement From Force Balance Instrumentation

A large scale model representative of a low-noise, high bypass ratio turbofan engine was tested for acoustics and performance in the NASA Lewis 9- by 15-Foot Low-Speed Wind Tunnel. This test was part of NASA's continuing Advanced Subsonic Technology Noise Reduction Program. The low tip speed fan, nacelle, and an un-powered core passage (with core inlet guide vanes) were simulated. The fan blades and hub are mounted on a rotating thrust and torque balance. The nacelle, bypass duct stators, and core passage are attached to a six component force balance. The two balance forces, when corrected for internal pressure tares, measure the total thrust-minus-drag of the engine simulator. Corrected for scaling and other effects, it is basically the same force that the engine supports would feel, operating at similar conditions. A control volume is shown and discussed, identifying the various force components of the engine simulator thrust and definitions of net thrust. Several wind tunnel runs with nearly the same hardware installed are compared, to identify the repeatability of the measured thrust-minus-drag. Other wind tunnel runs, with hardware changes that affected fan performance, are compared to the baseline configuration, and the thrust and torque effects are shown. Finally, a thrust comparison between the force balance and nozzle gross thrust methods is shown, and both yield very similar results.

Jeracki, Robert J.↗

DOE OSTI2021

Where Is the Water? Jupiter-like C/H Ratio but Strong H{sub 2}O Depletion Found on τ Boötis b Using SPIRou

The present-day envelope of gaseous planets is a relic of how these giant planets originated and evolved. Measuring their elemental composition therefore presents a powerful opportunity to answer long-standing questions regarding planet formation. Obtaining precise observational constraints on the elemental inventory of giant exoplanets has, however, remained challenging owing to the limited simultaneous wavelength coverage of current space-based instruments. Here, we present thermal emission observations of the nontransiting hot Jupiter τ Boo b using the new wide wavelength coverage (0.95–2.50 μm) and high spectral resolution (R = 70,000) CFHT/SPIRou spectrograph. By combining a total of 20 hr of SPIRou data obtained over five nights in a full atmospheric retrieval framework designed for high-resolution data, we constrain the abundances of all the major oxygen- and carbon-bearing molecules and recover a noninverted temperature structure using a new free-shape, nonparametric temperature–pressure profile retrieval approach. We find a volume mixing ratio of log(CO) = -2.46{sub -0.29}{sup +0.25} and a highly depleted water abundance of less than 0.0072 times the expected value for a solar composition envelope. Combined with upper limits on the abundances of CH{sub 4}, CO{sub 2}, HCN, TiO, and C{sub 2}H{sub 2}, this results in a gas-phase C/H ratio of 5.85{sub -2.82}{sup +4.44} × solar, consistent with the value of Jupiter, and an envelope C/O ratio robustly greater than 0.60, even when taking into account the oxygen that may be sequestered out of the gas phase. Combined, the inferred supersolar C/H, O/H, and C/O ratios on τ Boo b support a formation scenario beyond the water snowline in a disk enriched in CO owing to pebble drift.

74 ATOMIC AND MOLECULAR PHYSICS↗

NASA NTRS1962

NASA Scout ST-1 Flight-Test Results and Analyses, Launch Operations, and Test Vehicle Description

The first of a series of flight tests for the development of the four-stage, solid-propellant Scout vehicle was conducted at the NASA Wallops Station under the direction of the Langley Research Center. Vehicle designation for the test was NASA Scout ST-1. Performance characteristics of the vehicle and components were recorded during a high-altitude probe mission. Flight-simulation studies are presented and show that the accuracy of the guidance system during the flight was within control-system design specifications. The control system functioned normally during the flight with the exception of an overpowering of the reaction-control roll jets near burnout of the third-stage rocket motor. The resulting roll displacement of the vehicle is shown to have caused the monitor tracking radar which had been erroneously tracking a radar beacon in the vehicle on a side lobe to reorient to the major lobe of the receiving antenna. This tracking switch falsely indicated a violent turning maneuver on the monitor plot board and resulted in a hold-fire decision for the fourth-stage rocket motor. Although data for the final thrusting and coast phase of the flight were not obtained, the majority of the test objectives were achieved. In-flight thrust misalignment angles for the second- and third-stage rocket motors derived from control-system error data and for the first-stage motor determined from flight-simulation studies are presented. All rocket-motor thrust misalignment angles were well within the tolerances used for control-system design. Rocket-motor flight performance is presented, and velocity increments attained from the first three stages substantiated the predicted nominal performance. Operation of the rocket motors was satisfactory with the exception of high-level vibrations which were encountered during third-stage motor burning. Rolling moments which overpowered the reaction-control jets are also attributed to the burning characteristics of the third-stage motor. A discussion of the premature loss of the third-stage heat shield is given and shows that the heat-shield latching mechanism failed from pressure loads as the vehicle entered the transonic speed range. Although venting was provided to relieve the high negative pressures known to exist on the heat shield at these speeds, a field modification of the wiring tunnel had the same effect as opening the inside of the heat shield to ambient pressures. Consequently, the latching mechanism failed from pressure loads which were of about the same magnitude as the latching-mechanism yield loads. Skin temperatures were recorded at several locations on the vehicle and were generally in good agreement with theoretical values. Aerodynamic heating presented no problem during the flight since the maximum temperatures recorded during the flight were only about half the design values because of the high-launch-angle trajectory. Environmental vibrations recorded in the vicinity of the guidance package showed that no significant continuous amplitude levels above the general instrumentation noise level were present during first- and second-stage burning. Large vibration amplitudes were recorded during third-stage burning which coincided with the large roll disturbance experienced by the vehicle near burnout of the third-stage motor.

Scout Launch Vehicle↗

NASA NTRS1990

A model for the Space Shuttle Main Engine High Pressure Oxidizer Turbopump shaft seal system

A model of the High Pressure Oxidizer Turbopump (HPOTP) shaft seal system on the Space Shuttle Main Engine (SSME) is described. The model predicts the fluid properties and flow rates throughout this system for a number of conditions simulating failed seals. The results agree well with qualitative expectations and redline values but cannot be verified with actual data due to the lack thereof. The results indicate that each failure mode results in a unique distribution of properties throughout the seal system and can therefore be individually identified given the proper instrumentation. Furthermore, the detection process can be built on the principle of qualitative reasoning without the use of exact fluid property values. A simplified implementation of the model which does not include the slinger/labyrinth seal combination has been developed and will be useful for inclusion in a real-time diagnostic system.

Paxson, Daniel E.↗

NASA NTRS2001

Central Elemental Abundance Ratios In the Perseus Cluster: Resonant Scattering or SN Ia Enrichment?

We have determined abundance ratios in the core of the Perseus Cluster for several elements. These ratios indicate a central dominance of Type 1a supernova (SN Ia) ejects similar to that found for A496, A2199 and A3571. Simultaneous analysis of ASCA spectra from SIS1, GIS2, and GIS3 shows that the ratio of Ni to Fe abundances is approx. 3.4 +/- 1.1 times solar within the central 4'. This ratio is consistent with (and more precise than) that observed in other clusters whose central regions are dominated by SN Ia ejecta. Such a large Ni overabundance is predicted by "convective deflagration" explosion models for SNe Ia such as W7 but is inconsistent with delayed detonation models. We note that with current instrumentation the Ni K(alpha) line is confused with Fe K(beta) and that the Ni overabundance we observe has been interpreted by others as an anomalously large ratio of Fe K(beta) to Fe K(alpha) caused by resonant scattering in the Fe K(alpha) line. We argue that a central enhancement of SN Ia ejecta and hence a high ratio of Ni to Fe abundances are naturally explained by scenarios that include the generation of chemical gradients by suppressed SN Ia winds or ram pressure stripping of cluster galaxies. It is not necessary to suppose that the intracluster gas is optically thick to resonant scattering of the Fe K(alpha) line.

Dupke, Renato A.↗

NASA NTRS2012

Real-Time, Non-Intrusive Detection of Liquid Nitrogen in Liquid Oxygen at High Pressure and High Flow

An integrated fiber-optic Raman sensor has been designed for real-time, nonintrusive detection of liquid nitrogen in liquid oxygen (LOX) at high pressures and high flow rates in order to monitor the quality of LOX used during rocket engine ground testing. The integrated sensor employs a high-power (3-W) Melles Griot diode-pumped, solid-state (DPSS), frequency-doubled Nd:YAG 532- nm laser; a modified Raman probe that has built-in Raman signal filter optics; two high-resolution spectrometers; and photomultiplier tubes (PMTs) with selected bandpass filters to collect both N2 and O2 Raman signals. The PMT detection units are interfaced with National Instruments Lab- VIEW for fast data acquisition. Studies of sensor performance with different detection systems (i.e., spectrometer and PMT) were carried out. The concentration ratio of N2 and O2 can be inferred by comparing the intensities of the N2 and O2 Raman signals. The final system was fabricated to measure N2 and O2 gas mixtures as well as mixtures of liquid N2 and LOX

Singh, Jagdish P.↗

NASA NTRS2019

Ice-Crystal Icing Accretion Studies at the NASA Propulsion Systems Laboratory

This paper describes an ice-crystal icing experiment conducted at the NASA Propulsion System Laboratory during June 2018. This test produced ice shape data on an airfoil for different test conditions similar to those inside the compressor region of a turbo-fan jet engine. Mixed-phase icing conditions were generated by partially freezing out a water spray using the relative humidity of flow as the primary parameter to control freeze-out. The paper presents the ice shape data and associated conditions which include pressure, velocity, temperature, humidity, total water content, melt ratio, and particle size distribution. The test featured a new instrument traversing system which allowed surveys of the flow and cloud. The purpose of this work was to provide experimental ice shape data and associated conditions to help develop and validate ice-crystal icing accretion models. The results support previous experimental observations of a minimum melt-ratio threshold for accretion to occur as well as the existence of a plateau region where the icing severity is high for a range of melt ratios. However, a maximum limit for melt ratio, which is suggested in the ice crystal icing literature, was not observed perhaps complicated by the potential for some supercooling of the water at these conditions.

Engine Icing↗

NASA NTRSDate not supplied

A Case Study on the Challenges and Opportunities for the Deployment of PHM Capabilities in Existing Engineering Systems

The field of Prognostics and Health Management (PHM) of engineering systems has experienced considerable growth over the last decade. From benefits associated with faster and more powerful hardware in the form of wireless sensors, edge devices, and general computing capabilities (GPU’s and cloud computing), to development of powerful algorithms for anomaly detection and remaining useful life (RUL) estimation, the number of engineering systems featuring advanced diagnostics and prognostics capabilities continues to grow at an increasingly faster pace. However, the deployment of PHM capabilities as part of the upgrade of existing engineering systems presents multiple challenges to the PHM practitioner charged with retrofitting such systems. Issues include a lack of specific instrumentation needed to capture the signals of interest; insufficient data and sampling rates required for fault detection and diagnosis, and for detection of failure/degradation indicators; and difficulties in the identification of a system’s nominal behavior as a result of age induced degradation. Today’s PHM practitioner must be able to quickly identify and assess these types of issues to effectively evaluate and select the optimal PHM strategies required to achieve the desired results. This paper presents results from the preliminary evaluation of the High-Pressure Gas Facility (HPGF) infrastructure at NASA’s Stennis Space Center in Hancock County, Mississippi. This evaluation is part of a feasibility study conducted prior to the deployment of prognostics and diagnostics capabilities in the pumps skids of the liquid nitrogen (LN2) system of the HPGF.

Condition Based Maintenance↗

DOE OSTI2023

Two-Dimensional Thomson Scattering in Laser-Produced Plasmas

We present two-dimensional (2D) optical Thomson scattering measurements of electron density and temperature in laser-produced plasmas. The novel instrument directly measures ne(x,y) and Te(x,y) in two dimensions over large spatial regions (cm2) with sub-mm spatial resolution, by automatically translating the scattering volume while the plasma is produced repeatedly by irradiating a solid target with a high-repetition-rate laser beam (10 J, ∼1012 W/cm2, 1 Hz). In this paper, we describe the design and motorized auto-alignment of the instrument and the computerized algorithm that autonomously fits the spectral distribution function to the tens-of-thousands of measured scattering spectra, and captures the transition from the collective to the non-collective regime with distance from the target. As an example, we present the first 2D scattering measurements in laser-driven shock waves in ambient nitrogen gas at a pressure of 0.13 mbar.

Zhang, Haiping (ORCID:0009000228133852)↗

NASA NTRS1976

Ozone spectroscopy with a CO2 waveguide laser

Ozone spectral measurements were conducted with a waveguide CO2 laser, which was continuously tunable over a + or - 450-MHz region, about several lines in the P-branch of the band near the 9.5-micron wavelength region. A passively stabilized low-pressure CO2 laser was also used to provide reference CO2 frequencies. The frequencies of several ozone lines were determined in the nu-3 band, which are near CO2 laser line frequencies in the 9.5-micron wavelength region. The absolute measurement accuracy is estimated to be + or - 6 MHz, and the measurements indicate that the ozone line frequencies listed in currently available spectral compilations are 0.003-0.006 per cm too high. The size of this error is small by conventional IR standards, but extremely important when CO2 laser instruments are used to monitor stratospheric ozone, where line widths in this spectral region are typically 0.001/cm. Empirically determined absorption curves must be constructed in order to calibrate laser differential absorption instrument properly when low-altitude ozone measurements are conducted.

Menzies, R. T.↗

NASA NTRS1983

Flutter and steady/unsteady aerodynamic characteristics of supercritical and conventional transport wings

This paper presents the technical details and results of a high-speed wind-tunnel test program of an aeroelastic cantilevered transport type wing with two pylon-mounted engines. The tests were conducted in the NASA-Langley 16-foot Transonic Dynamic tunnel (TDT) during December 1981. Flutter of identical planforms, mass properties, and stiffness. The test parameters included different values of model stiffness and wing loading at various angles of attack. The models were instrumented at span-wise wing stations to determine bending and torsion deflections and vertical accelerations. At two model wing stations, pressure transducers were distributed along the chord to record static and unsteady oscillatory pressures during the approach to and onset of flutter. This paper presents the test program with results of the flutter characteristics and selected steady and unsteady aerodynamic data for both airfoils at different angles of attack for various Mach numbers and dynamic pressures.

Grosser, W. F.↗

NASA NTRS1993

In situ detection of tropospheric OH, HO2, NO2, and NO by laser-induced fluorescence in detection chambers at reduced pressures

This report is a brief summary of the status of work on the grant entitled 'In situ detection of tropospheric OH, HO2, NO2, and NO by laser induced fluorescence in detection chambers at low pressures.' The basic instrument characteristics have been established, and have been reported in a manuscript, included as an appendix to this report, that has been accepted by the Journal of Geophysical Research. Currently, two efforts are under way. First, instrument tests and calibrations are continuing. These efforts include field measurements and an informal inter comparison in Colorado last August and September. Second, new technologies in lasers and detectors are being implemented to make the instrument smaller, lighter, and more energy efficient. Such instrument modifications are essential for measurements from aircraft, high scaffolding in forests, and ships.

Brune, William H.↗

NASA NTRS2003

Gas Scintillation Proportional Counters for High-Energy X-ray Astronomy

A focal plane array of high-pressure gas scintillation proportional counters (GSPC) for a balloon-borne hard-x-ray telescope is under development at the Marshall Space Flight Center. These detectors have an active area of approx. 20 sq cm, and are filled with a high pressure (10(exp 6) Pa) xenon-helium mixture. Imaging is via crossed-grid position-sensitive phototubes sensitive in the UV region. The performance of the GSPC is well matched to that of the telescopes x-ray optics which have response to 75 keV and a focal spot size of approx. 500 microns. The detector s energy resolution, 4% FWHM at 60 keV, is adequate for resolving the broad spectral lines of astrophysical importance and for accurate continuum measurements. Full details of the instrument and its performance will be provided.

Gubarev, Mikhail↗

NASA NTRS2004

Microphysical Characterization of Ice in Hurricane Erin for Wideband Passive Microwave Comparisons

In order to better understand the characteristics of frozen hydrometeors in hurricane systems, computed brightness temperatures were compared with observations of Hurricane Erin from CAMEX-4 radiometers on the ER-2 aircraft. These wideband observations ranged from 10.7 to 183 plus or minus 10 GHz. In order to initialize the cloud profiles used in the radiative transfer calculations, radar reflectivities from an ER-2 instrument were converted to mass contents at specified height levels. Dropsonde data from the ER-2 and modeled Hurricane Andrew data were used to generate profiles of temperature, pressure, and relative humidity and to provide surface wind speed and ocean temperature. Four different ice (size and density) parameterizations were used to compute brightness temperature values. The comparisons between the calculated and observed brightness temperatures show that in general the Grenfell and Warren particle size distribution does the best job of matching the observations for most of the high frequencies. These high frequencies (greater than or equal to 85 GHz) are particularly sensitive to frozen particles. The Sehkon and Srivastava particle size distribution produced brightness temperatures that were too cold in most cases. On the other hand, the fluffy snow particle parameterizations with and without a melting layer produced brightness temperatures that were much warmer than the observations at these high frequencies. All low frequency calculations track the observations well except in the eye of Hurricane Erin where the surface wind speed and/or near surface temperatures were not properly adjusted to warm the brightness temperature calculations to values closer to the observations. Overall, this work shows that selecting a proper ice particle parameterization can be difficult and additional in situ measurements are needed to define appropriate parameterizations.

Skofronick-Jackson, G.↗

NASA NTRS2009

Compact Reconnaissance Imaging Spectrometer Observations of Water Vapor and Carbon Monoxide

The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) onboard the Mars Reconnaissance Orbiter (MRO) spacecraft began taking observations in September 2006 and has now collected more than a full Martian year of data. Retrievals performed using the near-infrared spectra obtained by CRISM are used to characterize the seasonal and spatial variation of the column abundance of water vapor and the column-averaged mixing ratio of carbon monoxide. CRISM retrievals show nominal behavior in water vapor during northern hemisphere spring and summer with maximum abundance reaching 50 precipitable micrometers. Water vapor abundance during the southern hemisphere spring and summer appears significantly reduced compared to observations by other instruments taken during previous years. The CRISM retrievals show the seasonally and globally averaged carbon monoxide mixing ratio to be 700 ppm, but with strong seasonal variations at high latitudes. The summertime near-polar carbon monoxide mixing ratio falls to 200 ppm in the south and 400 ppm in the north as carbon dioxide sublimates from the seasonal polar ice caps and dilutes noncondensable species including carbon monoxide. At low latitudes, the carbon monoxide mixing ratio varies in response to the mean seasonal cycle of surface pressure.

Smith, Michael D.↗

DOE OSTI2025

Bridging material models across scales: An integrated approach to equation of state and molecular dynamics modeling of copper

New uncertainty-aware equation of state (EOS) and electrical conductivity (EC) models for copper have been developed. The multiphase EOS/EC models are fit to experimental solid/liquid EC isobar measurements as well as density-functional theory molecular dynamics (DFT-MD) EC calculations in both expanded and compressed regimes (0.1–16 g/ cm 3 ⁠). The liquid and solid EOS phases were fit to available experimental data along with additional DFT-MD data over the same range as the EC. Leveraging the DFT-MD data, a corresponding machine-learned interatomic potential (MLIAP) for copper was trained using genetic-algorithm optimization. The copper MLIAP was constrained by EOS shock points at high compressions. The final EOS bounded MLIAP proves to be stable over a large density range (approximately 0.1–20 g/ cm 3 ) with good agreement to an isothermal compression curve, shock Hugoniot, and liquid speed of sound measurements at high pressures (100s of GPa).

Acoustic measurements and instrumentation↗

DOE OSTI2024

Executive summary of error sources in dynamic surface temperature measurements

Obtaining bulk T requires measuring apparent sample interface T surface , knowledge of any window conditions T window , and knowledge of thermal transport from the sample to the window. To obtain bulk T with uncertainties below 5% requires relatively small uncertainties in each of these areas, and large uncertainties in one area require smaller uncertainties in others to maintain the error budget. For example, if T window is known to 10%, a 5% total uncertainty can be obtained if T surface is known to 1% and combined transport uncertainties are known to 20%. If T surface can only be measured to 2%, combined transport uncertainties must be 17% to reach the same overall uncertainty. As the form of transport is unknown at high pressure, and window temperatures are difficult to measure by their very nature, reducing surface T uncertainties is the practical first step. Here we will discuss various error sources in the measurement of apparent T surface , and which ones must be correctly obtained prior to the experiment.

36 MATERIALS SCIENCE↗