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NASA NTRS1975

Data management for Large Space Telescope

The data management system for the Large Space Telescope (LST) must be capable of meeting requirements of 160 million bits per 95 min orbit with a bit error rate of less than 0.00001 for data. The system will be supported by the Tracking and Data Relay Satellite System of the Space Tracking and Data Network. The on-board system includes a general purpose computer that controls the vehicle as a stable observation platform and the array of instruments used for data collection. The ground-based system comprises a Mission Operations Center (MOC), a Science Institute where instrument data is processed, and a communications service for the space and point-to-point data flow. The allocation of hardware and software between on-board and ground-based components to achieve design objectives of maximum flexibility at minimum cost is discussed.

Hope, G. R., Jr.↗

NASA NTRS1987

Non-equilibrium effects in high temperature chemical reactions

Reaction rate data were collected for chemical reactions occurring at high temperatures during reentry of space vehicles. The principle of detailed balancing is used in modeling kinetics of chemical reactions at high temperatures. Although this principle does not hold for certain transient or incubation times in the initial phase of the reaction, it does seem to be valid for the rates of internal energy transitions that occur within molecules and atoms. That is, for every rate of transition within the internal energy states of atoms or molecules, there is an inverse rate that is related through an equilibrium expression involving the energy difference of the transition.

Johnson, Richard E.↗

NASA NTRS2006

Mars Exploration Rover Surface Mission: Thermal Performance for More Than an Entire Martian Year

This viewgraph presentation reviews the thermal performance of the Mars Exploration Rovers. The Mars Exploration Rover (MER) project landed two identical roving science vehicles on Mars in January 2004; they have continued to perform geological science data collection well beyond their surface design lifetime of 90 sols. The design of the thermal system is described. Pictures from the rovers are also included,

flight performance↗

NASA NTRS2010

Crash Test of an MD-500 Helicopter with a Deployable Energy Absorber Concept

On December 2, 2009, a full scale crash test was successfully conducted of a MD-500 helicopter at the NASA Langley Research Center Landing and Impact Research Facility . The purpose of this test was to evaluate a novel composite honeycomb deployable energy absorbing (DEA) concept for attenuation of structural and crew loads during helicopter crashes under realistic crash conditions. The DEA concept is an alternative to external airbags, and absorbs impact energy through crushing. In the test, the helicopter impacted the concrete surface with 11.83 m/s (38.8 ft/s) horizontal, 7.80 m/s (25.6 ft/s) vertical and 0.15 m/s (0.5 ft/s) lateral velocities; corresponding to a resultant velocity of 14.2 m/s (46.5 ft/s). The airframe and skid gear were instrumented with accelerometers and strain gages to determine structural integrity and load attenuation, while the skin of the airframe was covered with targets for use by photogrammetry to record gross vehicle motion before, during, and after the impact. Along with the collection of airframe data, one Hybrid III 50th percentile anthropomorphic test device (ATD), two Hybrid II 50th percentile ATDs and a specialized human surrogate torso model (HSTM) occupant were seated in the airframe and instrumented for the collection of occupant loads. Resultant occupant data showed that by using the DEA, the loads on the Hybrid II and Hybrid III ATDs were in the Low Risk regime for the injury criteria, while structural data showed the airframe retained its structural integrity post crash. Preliminary results show that the DEA is a viable concept for the attenuation of impact loads.

Littell, Justin D.↗

NASA NTRS2010

Spinoff 2010

Topics covered include: Burnishing Techniques Strengthen Hip Implants; Signal Processing Methods Monitor Cranial Pressure; Ultraviolet-Blocking Lenses Protect, Enhance Vision; Hyperspectral Systems Increase Imaging Capabilities; Programs Model the Future of Air Traffic Management; Tail Rotor Airfoils Stabilize Helicopters, Reduce Noise; Personal Aircraft Point to the Future of Transportation; Ducted Fan Designs Lead to Potential New Vehicles; Winglets Save Billions of Dollars in Fuel Costs; Sensor Systems Collect Critical Aerodynamics Data; Coatings Extend Life of Engines and Infrastructure; Radiometers Optimize Local Weather Prediction; Energy-Efficient Systems Eliminate Icing Danger for UAVs; Rocket-Powered Parachutes Rescue Entire Planes; Technologies Advance UAVs for Science, Military; Inflatable Antennas Support Emergency Communication; Smart Sensors Assess Structural Health; Hand-Held Devices Detect Explosives and Chemical Agents; Terahertz Tools Advance Imaging for Security, Industry; LED Systems Target Plant Growth; Aerogels Insulate Against Extreme Temperatures; Image Sensors Enhance Camera Technologies; Lightweight Material Patches Allow for Quick Repairs; Nanomaterials Transform Hairstyling Tools; Do-It-Yourself Additives Recharge Auto Air Conditioning; Systems Analyze Water Quality in Real Time; Compact Radiometers Expand Climate Knowledge; Energy Servers Deliver Clean, Affordable Power; Solutions Remediate Contaminated Groundwater; Bacteria Provide Cleanup of Oil Spills, Wastewater; Reflective Coatings Protect People and Animals; Innovative Techniques Simplify Vibration Analysis; Modeling Tools Predict Flow in Fluid Dynamics; Verification Tools Secure Online Shopping, Banking; Toolsets Maintain Health of Complex Systems; Framework Resources Multiply Computing Power; Tools Automate Spacecraft Testing, Operation; GPS Software Packages Deliver Positioning Solutions; Solid-State Recorders Enhance Scientific Data Collection; Computer Models Simulate Fine Particle Dispersion; Composite Sandwich Technologies Lighten Components; Cameras Reveal Elements in the Short Wave Infrared; Deformable Mirrors Correct Optical Distortions; Stitching Techniques Advance Optics Manufacturing; Compact, Robust Chips Integrate Optical Functions; Fuel Cell Stations Automate Processes, Catalyst Testing; Onboard Systems Record Unique Videos of Space Missions; Space Research Results Purify Semiconductor Materials; and Toolkits Control Motion of Complex Robotics.

Source record↗

NASA NTRS2015

Risk of Impaired Control of Spacecraft/Associated Systems and Decreased Mobility Due to Vestibular/Sensorimotor Alterations Associated with Space flight

Control of vehicles and other complex systems is a high-level integrative function of the central nervous system (CNS). It requires well-functioning subsystem performance, including good visual acuity, eye-hand coordination, spatial and geographic orientation perception, and cognitive function. Evidence from space flight research demonstrates that the function of each of these subsystems is altered by removing gravity, a fundamental orientation reference, which is sensed by vestibular, proprioceptive, and haptic receptors and used by the CNS for spatial orientation, posture, navigation, and coordination of movements. The available evidence also shows that the degree of alteration of each subsystem depends on a number of crew- and mission-related factors. There is only limited operational evidence that these alterations cause functional impacts on mission-critical vehicle (or complex system) control capabilities. Furthermore, while much of the operational performance data collected during space flight has not been available for independent analysis, those that have been reviewed are somewhat equivocal owing to uncontrolled (and/or unmeasured) environmental and/or engineering factors. Whether this can be improved by further analysis of previously inaccessible operational data or by development of new operational research protocols remains to be seen. The true operational risks will be estimable only after we have filled the knowledge gaps and when we can accurately assess integrated performance in off-nominal operational settings (Paloski et al. 2008). Thus, our current understanding of the Risk of Impaired Control of Spacecraft/Associated Systems and Decreased Mobility Due to Vestibular/Sensorimotor Alterations Associated with Space flight is limited primarily to extrapolation of scientific research findings, and, since there are limited ground-based analogs of the sensorimotor and vestibular changes associated with space flight, observation of their functional impacts is limited to studies performed in the space flight environment. Fortunately, many sensorimotor and vestibular experiments have been performed during and/or after space flight missions since 1959 (Reschke et al. 2007). While not all of these experiments were directly relevant to the question of vehicle/complex system control, most provide insight into changes in aspects of sensorimotor control that might bear on the physiological subsystems underlying this high-level integrated function.

Bloomberg, Jacob J.↗

NASA NTRSDate not supplied

Correlation of Canopy Distortion with Asymmetric Loading in Large Diameter Ringsail Parachutes

The second generation of the main parachutes for the Orion Capsule Parachute Assembly System (CPAS) were subjected to multiple flight tests. Three of the tests included were instrumented with the Tension Measuring System (TMS) to record main dispersion bridle loads. While these units were not able to resolve the individual suspension line loads, they were able to record a course representation of the asymmetric loading of the main parachutes during inflation. These tests were also equipped with upward looking cameras mounted on the test vehicles to collect detailed imagery of main deployment and inflation. When analyzed independently, both data sources exhibit similar features. These similarities provide evidence that the suspension line loads and the distortions in the canopy geometry are not independent. This paper will examine both data sources simultaneously to establish a correlation between asymmetric loading at the canopy skirt and the deformations of the canopy. This correlation will be used to build a model which can estimate individual suspension line loads from a measured riser load and detailed imagery.

Parachutes↗

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↗

DOE OSTI2022

Testing and Simulation of an Updated Cartridge Loop Vehicle

The Versatile Test Reactor (VTR) is a sodium-cooled, fast-spectrum test reactor that is being developed in the United States and will support a variety of irradiation test vehicle configurations, including cartridge loops. This work includes out-of-pile experimental results from a single-phase, natural circulation cartridge loop vehicle with geometry relevant to VTR irradiation sites, as well as comparisons between the experimental results and results predicted using the TRAC/RELAP Advanced Computational Engine (TRACE) modeling tool. The experiments were conducted in the thermosyphon test loop (TSTL) facility at Oak Ridge National Laboratory. Comparisons are also made between the current experimental data and results from natural circulation experiments previously conducted in the TSTL in a cartridge vehicle that is similar in design but has smaller flow areas. This cartridge vehicle and the experimental program were developed to add to the single-phase, natural circulation data collected in the previous iteration of the cartridge loop design, which supports future irradiation experiments and adds to a database that is useful for validating computer models. Comparisons of experimental results to TRACE model predictions is a pertinent step in validating the computational tool for supporting future irradiation experiment design and safety calculations, and comparisons to previous cartridge loop results highlight the impact of the design changes made to the test vehicle. The experiments conducted include several steady state tests and transients, including power ramp, loss of offsite power, and loss of external flow scenarios. This work shows that TRACE can accurately predict temperatures and flow conditions in the cartridge loop and the updated vehicle design achieves higher mass flow rates at the same steady state power levels.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2010

Ares I-X Flight Test Development Challenges and Success Factors

The NASA Constellation Program's Ares I-X rocket launched successfully on October 28, 2009 collecting valuable data and providing risk reduction for the Ares I project. The Ares I-X mission was formulated and implemented in less than four years commencing with the Exploration Systems Architecture Study in 2005. The test configuration was founded upon assets and processes from other rocket programs including Space Shuttle, Atlas, and Peacekeeper. For example, the test vehicle's propulsion element was a Shuttle Solid Rocket Motor. The Ares I-X rocket comprised a motor assembly, mass and outer mold line simulators of the Ares I Upper Stage, Orion Spacecraft and Launch Abort System, a roll control system, avionics, and other miscellaneous components. The vehicle was 327 feet tall and weighed approximately 1,800,000 pounds. During flight the rocket reached a maximum speed of Mach 4.8 and an altitude of 150,000 feet. The vehicle demonstrated staging at 130,000 feet, tested parachutes for recovery of the motor, and utilized approximately 900 sensors for data collection. Developing a new launch system and preparing for a safe flight presented many challenges. Specific challenges included designing a system to withstand the environments, manufacturing large structures, and re-qualifying heritage hardware. These and other challenges, if not mitigated, may have resulted in test cancellation. Ares I-X succeeded because the mission was founded on carefully derived objectives, led by decisive and flexible management, implemented by an exceptionally talented and dedicated workforce, and supported by a thorough independent review team. Other major success factors include the use of proven heritage hardware, a robust System Integration Laboratory, multi-NASA center and contractor team, concurrent operations, efficient vehicle assembly, effective risk management, and decentralized element development with a centralized control board. Ares I-X was a technically complex test that required creative thinking, risk taking, and a passion to succeed.

Askins, Bruce↗

NASA NTRS2003

Development of a Crosslink Channel Simulator for Simulation of Formation Flying Satellite Systems

Multi-vehicle missions are an integral part of NASA s and other space agencies current and future business. These multi-vehicle missions generally involve collectively utilizing the array of instrumentation dispersed throughout the system of space vehicles, and communicating via crosslinks to achieve mission goals such as formation flying, autonomous operation, and collective data gathering. NASA s Goddard Space Flight Center (GSFC) is developing the Formation Flying Test Bed (FFTB) to provide hardware-in- the-loop simulation of these crosslink-based systems. The goal of the FFTB is to reduce mission risk, assist in mission planning and analysis, and provide a technology development platform that allows algorithms to be developed for mission hctions such as precision formation flying, synchronization, and inter-vehicle data synthesis. The FFTB will provide a medium in which the various crosslink transponders being used in multi-vehicle missions can be plugged in for development and test. An integral part of the FFTB is the Crosslink Channel Simulator (CCS),which is placed into the communications channel between the crosslinks under test, and is used to simulate on-orbit effects to the communications channel due to relative vehicle motion or antenna misalignment. The CCS is based on the Starlight software programmable platform developed at General Dynamics Decision Systems which provides the CCS with the ability to be modified on the fly to adapt to new crosslink formats or mission parameters.

Hart, Roger↗

DOE OSTI2021

National Park Service Bus Electrification Study: 2020 Report

This report summarizes important considerations for implementing BEBs in the three national park fleets, detailing information about current buses at each fleet, electric bus demonstration vehicles, as well as performance evaluations of BEBs in Zion, Bryce, and Yosemite. Results include in-use data collection results reporting metrics such as average bus speed, energy usage per trip, and daily distance traveled, as well as effects of high heating, ventilation, and air conditioning (HVAC) system use to both heat and cool the buses, emissions estimations before and after use of electric buses, operating costs, electric vehicle infrastructure, maintenance, and bus driver user experience survey information. Analysis results from this project will help the NPS understand how BEBs and future expansion of BEBs could assist in meeting their bottom line and operational goals and assist NPS in choosing appropriate locations for future BEB deployments.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2001

Engineering sensors for the Cassini spacecraft

The intent of this paper is to review the subsystems of the Cassini spacecraft and to discuss the types of devices that are used to collect engineering data for each of these subsystems.

vehicle health management fault protection spacecr↗

NASA NTRS1977

JSC thunderstorm experiment results

To gain more insight into the various effects of lightning and thunderstorms on future shuttle vehicle launch and landing operations, an experiment was conducted to obtain data on the nature of electric fields in the vicinity of thunderstorms and particularly in the region of cumulonimbus cloud anvils during their various stages of build-up, maturity, and dissipation. These data supplement the airborne electric field data collected during the summer of 1975 in support of the Apollo Soyuz Test Project and the Viking launches. A Learjet aircraft was outfitted with four special electric field meters for collecting data. The onboard aircraft radar was also used to investigate cells embedded in large thunderstorm systems such as those found in frontal and squall line activities. Data were collected from 33 storm cells and used to establish a launch criteria to preclude triggering lightning during shuttle vehicle operations in close proximity to thunderstorms.

Source record↗

DOE OSTI2023

Analysis of Uncertainty Impacts on Emissions and Fuel Economy Evaluation for Chassis Dynamometer Testing

This study illustrates a methodology for quantifying the uncertainties encountered in the measurement of tailpipe emissions and in the fuel consumption measurements for light-duty conventional vehicles tested on a four-wheel drive chassis dynamometer. The study leverages high-fidelity experimental data collected over three standard drive cycles, UDDS, HWY and US06, intended to simulate a wide range of operating conditions. Here, a method is developed to estimate the measurement uncertainties in fuel consumption for a test cycle, which occur due to the accumulation of measurement uncertainties propagated through the system. The uncertainty determination model uses statistical analysis and standard propagation techniques to evaluate and combine the uncertainties introduced from various sources (including the vehicle, chassis dynamometer, driver, and instrumentation). The analysis also examines three different experimental methods for determining the fuel consumption: 1) carbon mass balance, 2) volumetric fuel scale and 3) gravimetric fuel scale, and takes into consideration the properties of the instrumentation used. The results show that the most significant influence on the determination of the emissions comes from the concentration measurement, and similarly the biggest impact on the total fuel consumption uncertainty comes from the uncertainty in the determination of the carbon dioxide mass, due to the large presence of this pollutant in the overall emissions. It was found that the fuel consumption uncertainties are in the range of ±1-2% for all three methods analyzed, with the lowest values being obtained for measurements performed using the gravimetric method for all three drive cycles considered.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Real-time and Autonomous Water Quality Monitoring System Based on Remotely Operated Vehicle

Existing water quality monitoring systems near hydropower facilities are limited by the lack of mobility of the sensors’ carrier platform. Most systems use a buoy, a mounting fixture attached to a solid structure, or a human worker, which significantly limits the selection of the sampling sites and poses safety risks during data collection and equipment maintenance. To improve on this technology, we developed an autonomous water quality monitoring system that can operate in dangerous water environments near hydropower facilities for water sampling at multiple locations. The goal is to enable safe, timely, and comprehensive water-quality data collection; maximize power generation revenue with improved operational control; and reduce Federal Energy Regulatory Commission and state water quality monitoring costs for compliance. The system incorporates a remotely operated vehicle as the mobile monitoring platform, a dissolved oxygen sensor for monitoring water quality, a tether management system for automatically winding the tether, a solar mobile docking platform for suppling power to the ROV, and a web-based graphical user interface for data post-processing and visualization. In addition, preliminary field research are presented to demonstrate the system capabilities.

Salalila, Aljon L.↗

DOE OSTI2020

INTERFUEL: EPAct AFV Compliance Analysis [Slides]

This presentation presents an overview of the extent to which the Federal government's fleet of motor vehicles is shown as compliant with a requirement in the Energy Policy Acts of 1992 and 2005 that the Federal government acquire alternative fuel vehicles for fleet use, causes behind the recent decrease in compliance, and a proposed change to how the fleet data collected through the Federal Automotive Statistical Tool might be used by the US Department of Energy to arrive at a more correct characterization of compliance. The presentation is intended for delivery at the February 12, 2020 meeting of the DOE-sponsored INTERFUEL working group.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1997

Characterization of the breakup of the Pegasus rocket body 1994-029B

The breakup of a Pegasus hydrazine auxiliary propulsion system in June 1996, officially recognized as the worst satellite breakup in terms of cataloged debris, is considered. The fragmentation event is analyzed and it is discussed how these debris contribute to the current and future near earth space environment. The low altitude of the breakup and the large range of ejection velocities present concerns for other earth orbiting space vehicles, especially the Space Shuttle and the Hubble Space Telescope. In addition to orbit data collected by the U.S. Space Surveillance Network, observations were conducted with ground-based radar observatories. These observations show that the overabundance of debris is not limited to the trackable population, but also extends down to debris with sizes of less than 1 cm. Attempts to detect the debris with optical sensors were less successful.

Matney, Mark↗