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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Ultralow Frequency Waves as an Intermediary for Solar Wind Energy Input Into the Radiation Belts

Enhancements of electron fluxes in the outer radiation belt have been closely linked to increases in solar wind speed and density as well as to prolonged intervals of southward interplanetary magnetic field. Periodic oscillations in the Earth's magnetic field with frequencies in the range of a few millihertz (ultralow frequency or ultralow frequency waves) may be an intermediary through which these solar wind drivers influence radiation belt dynamics due to their potential for resonant interactions with energetic electrons causing the radial migration of resonant electrons. Using data from more than 180 ground magnetometers contributing to the worldwide SuperMAG collaboration, we explore possible relationships between relativistic electron flux variations and the spatial and temporal profiles of ultralow frequency wave power contained in the Pc5 frequency band (2–7 mHz). During 19 geomagnetic storms marked by relativistic (1.5 MeV < E < 6 MeV) electron flux enhancements and 19 storms that led to prolonged electron flux depletions, Pc5 wave power is found penetrating to L shells as low as 2–3. The enhancement of Pc5 wave power starts almost simultaneously with the storm onset. The depth of wave activity penetration was found associated with the strength of geomagnetic activity (Spearman's ρ = 0.54), which is also related to the location of electron flux maximum observed in the recovery phase. Pc5 wave activity persists longer (for up to ≈62 hr) for those storms that produced relativistic electrons. We also investigate the combination of interplanetary conditions necessary to differentiate the response of relativistic electron fluxes to geomagnetic storms. A coupling function that captures the increased reconnection rate at the dayside magnetopause affecting magnetospheric processes which may produce Pc5 wave power offers an additional key to further understanding the outer belt dynamics.

Georgiou, M.↗
NASA NTRS2012

RESOLVE Project

The RESOLVE project is a lunar prospecting mission whose primary goal is to characterize water and other volatiles in lunar regolith. The Lunar Advanced Volatiles Analysis (LAVA) subsystem is comprised of a fluid subsystem that transports flow to the gas chromatograph- mass spectrometer (GC-MS) instruments that characterize volatiles and the Water Droplet Demonstration (WDD) that will capture and display water condensation in the gas stream. The LAVA Engineering Test Unit (ETU) is undergoing risk reduction testing this summer and fall within a vacuum chamber to understand and characterize C!Jmponent and integrated system performance. Ray will be assisting with component testing of line heaters, printed circuit heaters, pressure transducers, temperature sensors, regulators, and valves in atmospheric and vacuum environments. He will be developing procedures to guide these tests and test reports to analyze and draw conclusions from the data. In addition, he will gain experience with preparing a vacuum chamber with fluid and electrical connections. Further testing will include integrated testing of the fluid subsystem with the gas supply system, near-infrared spectrometer, WDD, Sample Delivery System, and GC-MS in the vacuum chamber. This testing will provide hands-on exposure to a flight forward spaceflight subsystem, the processes associated with testing equipment in a vacuum chamber, and experience working in a laboratory setting. Examples of specific analysis Ray will conduct include: pneumatic analysis to calculate the WOO's efficiency at extracting water vapor from the gas stream to form condensation; thermal analysis of the conduction and radiation along a line connecting two thermal masses; and proportional-integral-derivative (PID) heater control analysis. In this Research and Technology environment, Ray will be asked to problem solve real-time as issues arise. Since LAVA is a scientific subsystem, Ray will be utilizing his chemical engineering background to operate the near-infrared spectrometer and GC-MS instruments during ETU testing. Ray will be working with Modified Commercial off the Shelf (MCOTS) instruments and characterizing their analytical behavior for optimization. Ray will be offered the opportunity to suggest testing modifications or configuration changes at any time to improve the experimental effectiveness. He will gain many skills needed for working in a technical team setting requiring flexibility and critical thinking.

Parker, Ray O.↗
NASA NTRS2017

Quantifying Black Carbon Deposition Over the Greenland Ice Sheet from Forest Fires in Canada

Black carbon (BC) concentrations observed in 22 snowpits sampled in the northwest sector of the Greenland ice sheet in April 2014 have allowed us to identify a strong and widespread BC aerosol deposition event, which was dated to have accumulated in the pits from two snow storms between 27 July and 2 August 2013. This event comprises a significant portion (57 on average across all pits) of total BC deposition over 10 months (July 2013 to April 2014). Here we link this deposition event to forest fires burning in Canada during summer 2013 using modeling and remote sensing tools. Aerosols were detected by both the Cloud-Aerosol Lidar with Orthogonal Polarization (on board CALIPSO) and Moderate Resolution Imaging Spectroradiometer (Aqua) instruments during transport between Canada and Greenland. We use high-resolution regional chemical transport modeling (WRF-Chem) combined with high-resolution fire emissions (FINNv1.5) to study aerosol emissions, transport, and deposition during this event. The model captures the timing of the BC deposition event and shows that fires in Canada were the main source of deposited BC. However, the model underpredicts BC deposition compared to measurements at all sites by a factor of 2100. Underprediction of modeled BC deposition originates from uncertainties in fire emissions and model treatment of wet removal of aerosols. Improvements in model descriptions of precipitation scavenging and emissions from wildfires are needed to correctly predict deposition, which is critical for determining the climate impacts of aerosols that originate from fires.

albedo↗
NASA NTRS2003

Detection of Strand Cleavage And Oxidation Damage Using Model DNA Molecules Captured in a Nanoscale Pore

We use a biological nano-scale pore to distinguish among individual DNA hairpins that differ by a single site of oxidation or a nick in the sugar-phosphate backbone. In earlier work we showed that the protein ion channel alpha-hemolysin can be used as a detector to distinguish single-stranded from double-stranded DNA, single base pair and single nucleotide differences. This resolution is in part a result of sensitivity to structural changes that influence the molecular dynamics of nucleotides within DNA. The strand cleavage products we examined here included a 5-base-pair (5-bp) hairpin with a 5-prime five-nucleotide overhang, and a complementary five-nucleotide oligomer. These produced predictable shoulder-spike and rapid near-full blockade signatures, respectively. When combined, strand annealing was monitored in real time. The residual current level dropped to a lower discrete level in the shoulder-spike blockade signatures, and the duration lengthened. However, these blockade signatures had a shorter duration than the unmodified l0bp hairpin. To test the pore sensitivity to nucleotide oxidation, we examined a 9-bp hairpin with a terminal 8-oxo-deoxyguanosine (8-oxo-dG), or a penultimate 8-oxo-dG. Each produced blockade signatures that differed from the otherwise identical control 9bp hairpins. This study showed that DNA structure is modified sufficiently by strand cleavage or oxidation damage at a single site to alter in a predictable manner the ionic current blockade signatures produced. This technique improves the ability to assess damage to DNA, and can provide a simple means to help characterize the risks of radiation exposure. It may also provide a method to test radiation protection.

Vercoutere, W.↗
NASA NTRS2007

Biomedical Support of U.S. Extravehicular Activity

The world's first extravehicular activity (EVA) was performed by A. A. Leonov on March 18, 1965 during the Russian Voskhod-2 mission. The first US EVA was executed by Gemini IV astronaut Ed White on June 3, 1965, with an umbilical tether that included communications and an oxygen supply. A hand-held maneuvering unit (HHMU) also was used to test maneuverability during the brief EVA; however the somewhat stiff umbilical limited controlled movement. That constraint, plus difficulty returning through the vehicle hatch, highlighted the need for increased thermal control and improved EVA ergonomics. Clearly, requirements for a useful EVA were interrelated with the vehicle design. The early Gemini EVAs generated requirements for suits providing micro-meteor protection, adequate visual field and eye protection from solar visual and infrared radiation, gloves optimized for dexterity while pressurized, and thermal systems capable of protecting the astronaut while rejecting metabolic heat during high workloads. Subsequent Gemini EVAs built upon this early experience and included development of a portable environmental control and life support systems (ECLSS) and an astronaut maneuvering unit. The ECLSS provided a pressure vessel and controller with functional control over suit pressure, oxygen flow, carbon dioxide removal, humidity, and temperature control. Gemini EVA experience also identified the usefulness of underwater neutral buoyancy and altitude chamber task training, and the importance of developing reliable task timelines. Improved thermal management and carbon dioxide control also were required for high workload tasks. With the Apollo project, EVA activity was primarily on the lunar surface; and suit durability, integrated liquid cooling garments, and low suit operating pressures (3.75 pounds per square inch absolute [psia] or 25.8 kilopascal [kPa],) were required to facilitate longer EVAs with ambulation and significant physical workloads with average metabolic rates of 1000 BTU/hr and peaks of up to 2200 BTU/hr. Mobility was further augmented with the Lunar Roving Vehicle. The Apollo extravehicular mobility unit (EMU) was made up of over 15 components, ranging from a biomedical belt for capturing and transmitting biomedical data, urine and fecal containment systems, a liquid cooling garment, communications cap, a modular portable life support system (PLSS), a boot system, thermal overgloves, and a bubble helmet with eye protection. Apollo lunar astronauts performed successful EVAs on the lunar surface from a 5 psia (34.4 kPa) 100% oxygen environment in the Lunar Lander. A maximum of three EVAs were performed on any mission. For Skylab a modified A7LB suit, used for Apollo 15, was selected. The Skylab astronaut life support assembly (ALSA) provided umbilical support through the life support umbilical (LSU) and used open loop oxygen flow, rather than closed-loop as in Apollo missions. Thermal control was provided by liquid water circulated by spacecraft pumps and electrical power also was provided from the spacecraft via the umbilical. The cabin atmosphere of 5 psia (34.4 kPa), 70% oxygen, provided a normoxic atmosphere and because of the very low nitrogen partial pressures, no special protocols were required to protect against decompression sickness (DCS) as was the case with the Apollo spacecraft with a 5 psi, 100% oxygen environment.

Gernhardt, Michael L.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-33231-DND

It is well established that clouds have a profound influence on Earth's energy budget and that cloud feedbacks are responsible for much of the uncertainty in climate model projections of global warming in response to radiative forcing by greenhouse gases. While most model evaluation efforts focus on model representation of the observed mean state. For example, the regional mean climatology of key climate variables there is also tremendous value in testing how a model represents observed internal variations of the climate system. Here we use CERES observations during and after the so-called global warming hiatus to evaluate a subset of CMIP6 climate models. The CERES data show a marked 0.83 Wm-2 reduction in global mean reflected SW TOA flux during the three years following the hiatus that results in an increase in net energy into the climate system. The primary driver of the decrease in SW TOA flux is a reduction in low cloud cover over the eastern Pacific Ocean that occurs in response to an unprecedented increase in SSTs in that region following the hiatus. The CMIP6 simulations consist of AMIP-style experiments in which SSTs and sea-ice boundary conditions are constrained by observations. For each model, the AMIP runs were extended through the end of 2017 from the official CMIP6 AMIP end period in 2014. Results show that the models do a good job at capturing the pattern of observed changes in TOA flux observed by CERES, but tend to underestimate the magnitude.

Norman G Loeb↗
NASA NTRSDate not supplied

TROPOMI Geometry-dependent Lambertian-Equivalent surface Reflectivity (GLER) Product for Improved Trace-Gas Retrieval

Accurate information about the reflectivity of the Earth's surface is required for most satellite retrievals of atmospheric composition, and this information is generally taken from monthly surface reflectivity climatology that neglects angular dependence. Previously we introduced Geometry-dependent Lambertian-equivalent surface reflectivity (GLER) which captures solar and satellite viewing angle dependence as well as daily and seasonal changes. GLER is calculated from simulations of Rayleigh-only top-of-atmosphere (TOA) radiances over non-Lambertian surfaces. We use NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF) product over land and the wind-dependent Cox–Munk wave-facet slope distribution including water-leaving radiance over water to accounts for surface BRDF. We have developed global GLER product, previously for the Ozone Monitoring Instrument (OMI) and recently for Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI) with several new improvements and updates. We have implemented the near real time daily V006 MODIS MCD43C1 BRDF data and gap-filled with a daily BRDF coefficient climatology created from 2002-2017 V006 MCD43GF data. The NASA’s Global Modelling Initiative hourly 0.25 x 0.25 deg Replay simulations are used for more accurate determination of pixel specific terrain pressure. To improve detection of seasonal snow/ice scenes, we use the 4-km snow cover product from the Interactive Multi-sensor Snow and Ice Mapping System (IMS). Finally, we use an improved version of the vector linearized discrete ordinate radiative transfer (VLIDORT) for update of the top-of-atmosphere (TOA) radiance look-up-tables (LUTs). We demonstrate how the use of GLER is beneficial to TROPOMI’s high spatial resolution (up to 3.5 km x 3.5 km) measurements to monitor atmospheric trace gas pollutants down to the sub-city scale.

TROPOMI↗
NASA NTRS1998

Raman Lidar Measurements of Aerosol Extinction and Backscattering: Derivation of Aerosol Real Refractive Index, Single-Scattering Albedo, and Humidification Factor using Raman Lidar and Aircraft Size Distribution - Report 2

Aerosol backscattering and extinction profiles measured by the NASA Goddard Space Flight Center Scanning Raman Lidar (SRL) during the remote cloud sensing (RCS) intensive operations period (IOP) at the Department of Energy Atmospheric Radiation Measurement (ARM) southern Great Plains (SGP) site during two nights in April 1994 are discussed. These profiles are shown to be consistent with the simultaneous aerosol size distribution measurements made by a PCASP (Passive Cavity Aerosol Spectrometer Probe) optical particle counter flown on the University of North Dakota Citation aircraft. We describe a technique which uses both lidar and PCASP measurements to derive the dependence of particle size on relative humidity, the aerosol real refractive index n, and estimate the effective single-scattering albedo Omega(sub 0). Values of n ranged between 1.4-1.5 (dry) and 1.37-1.47 (wet); Omega(sub 0) varied between 0.7 and 1.0. The single-scattering albedo derived from this technique is sensitive to the manner in which absorbing particles are represented in the aerosol mixture; representing the absorbing particles as an internal mixture rather than the external mixture assumed here results in generally higher values of Omega(sub 0). The lidar measurements indicate that the change in particle size with relative humidity as measured by the PCASP can be represented in the form discussed by Hattel with the exponent gamma = 0.3 + or - 0.05. The variations in aerosol optical and physical characteristics captured in the lidar and aircraft size distribution measurements are discussed in the context of the meteorological conditions observed during the experiment.

Ferrare, R. A.↗
NASA NTRSDate not supplied

Artificial Neural Networks to Predict Cognitive Impairment of Rodents Subjected to Space Radiation

INTRODUCTION We use artificial neural networks (ANNs) as an example machine learning (ML) tool to predict the cognitive performance impairment of rats induced by irradiation. The experimental data in the analyses is attentional set-shifting (ATSET) test scores from a rodent model exposed to ≤15 cGy of individual galactic cosmic radiation (GCR) ions: 4He, 28Si, or 56Fe, expected for a Lunar or Mars mission [1]. This work investigates rats at a subject-based level and uses applied dose and performance scores taken before irradiation to predict whether a rat will be impaired when irradiated. The results of this study are significant to crewed space missions as they support the potential of predicting an astronaut’s impairment in a specific task before spaceflight through the implementation of appropriately trained ML tools. METHODS Data used in this work are scores from the ATSET, a multi-stage constrained cognitive flexibility test [2]. Our computational model utilizes the number of attempts to reach the criterion to pass a stage as a behavioral performance measure for rats. We use the post-irradiation scores, generate thresholds from cumulative distribution plots of non-irradiated rats, and calculate the percent of irradiated rats whose scores fall below the threshold to infer how each radiation type/dose affects a population. Rats scoring above the threshold are labeled impaired while the others are non-impaired. We then employ ANNs as a typical ML technique, and use each subject’s individual scores taken before radiation along with the applied dose, to predict their personal susceptibility to cognitive impairment due to space radiation exposure. RESULTS AND CONCLUSION A significant finding is the exhibition of a dose-dependent increasing probability of impairment for 1 to 10 cGy of 28Si or 56Fe in the simple discrimination (SD) stage of the ATSET, and for 1 to 10 cGy of 56Fe in the compound discrimination (CD) stage. On a subject-based level, implementing ML classifiers such as ANNs identifies rats that have a higher tendency for impairment after GCR exposure [1]. The receiver operating characteristic (ROC) and the precision-recall (PR) curves of the ML models show a better prediction of impairment when 56Fe is the ion in question in both SD (Figure 1) and CD stages. They, however, do not depict impairment due to 4He in SD (Figure 1) and 28Si in CD, suggesting no dose-dependent impairment response in these cases. In this work, “good” prediction pertains to “better-than-random-chance”, due to the limited sample size and the high inter- and intra-individual variabilities in response to brain stimulation paradigms, as applicable to both animals and humans. More behavioral tests and biomarkers should be investigated on the same subjects, to be fed to the ML models to capture the agents responsible for performance alterations of some individuals versus others.

machine learning↗
NASA NTRSDate not supplied

Machine Learning Models to Predict Cognitive Impairment of Rodents Subjected to Space Radiation

INTRODUCTION We use artificial neural networks (ANNs) as an example machine learning (ML) tool to predict the cognitive performance impairment of rats induced by irradiation. The experimental data in the analyses is attentional set-shifting (ATSET) test scores from a rodent model exposed to ≤15 cGy of individual galactic cosmic radiation (GCR) ions: 4He, 28Si, or 56Fe, expected for a Lunar or Mars mission [1]. This work investigates rats at a subject-based level and uses applied dose and performance scores taken before irradiation to predict whether a rat will be impaired when irradiated. The results of this study are significant to crewed space missions as they support the potential of predicting an astronaut’s impairment in a specific task before spaceflight through the implementation of appropriately trained ML tools. METHODS Data used in this work are scores from the ATSET, a multi-stage constrained cognitive flexibility test [2]. Our computational model utilizes the number of attempts to reach the criterion to pass a stage as a behavioral performance measure for rats. We use the post-irradiation scores, generate thresholds from cumulative distribution plots of non-irradiated rats, and calculate the percent of irradiated rats whose scores fall below the threshold to infer how each radiation type/dose affects a population. Rats scoring above the threshold are labeled impaired while the others are non-impaired. We then employ ANNs as a typical ML technique, and use each subject’s individual scores taken before radiation along with the applied dose, to predict their personal susceptibility to cognitive impairment due to space radiation exposure. RESULTS AND CONCLUSION A significant finding is the exhibition of a dose-dependent increasing probability of impairment for 1 to 10 cGy of 28Si or 56Fe in the simple discrimination (SD) stage of the ATSET, and for 1 to 10 cGy of 56Fe in the compound discrimination (CD) stage. On a subject-based level, implementing ML classifiers such as ANNs identifies rats that have a higher tendency for impairment after GCR exposure [1]. The receiver operating characteristic (ROC) and the precision-recall (PR) curves of the ML models show a better prediction of impairment when 56Fe is the ion in question in both SD (Figure 1) and CD stages. They, however, do not depict impairment due to 4He in SD (Figure 1) and 28Si in CD, suggesting no dose-dependent impairment response in these cases. In this work, “good” prediction pertains to “better-than-random-chance”, due to the limited sample size and the high inter- and intra-individual variabilities in response to brain stimulation paradigms, as applicable to both animals and humans. More behavioral tests and biomarkers should be investigated on the same subjects, to be fed to the ML models to capture the agents responsible for performance alterations of some individuals versus others.

machine learning↗
NASA NTRS2014

Oceanic Storm Characteristics off the Kennedy Space Center Coast

Natural cloud-to-ground lightning may behave differently depending on the characteristics of the attachment mediums, including the peak current (inferred from radiation fields) and the number of ground strike locations per flash. Existing literature has raised questions over the years on these characteristics of lightning over oceans, and the behaviors are not yet well understood. To investigate this we will obtain identical electric field observations over adjacent land and ocean regions during both clear air and thunderstorm periods. Oceanic observations will be obtained using a 3-meter NOAA buoy that has been instrumented with a Campbell Scientific electric field mill and New Mexico Techs slow antenna, to measure the electric fields aloft. We are currently obtaining measurements from this system on-shore at the Florida coast, to calibrate and better understand the behavior of the system in elevated-field environments. Sometime during winter 2013, this system will be moored 20NM off the coast of the Kennedy Space Center. Measurements from this system will be compared to the existing on-shore electric field mill suite of 31 sensors and a coastal slow antenna. Supporting observations will be provided by New Mexico Techs Lightning Mapping Array, the Eastern Range Cloud to Ground Lightning Surveillance System, and the National Lightning Detection Network. An existing network of high-speed cameras will be used to capture cloud-to-ground lightning strikes over the terrain regions to identify a valid data set for analysis. This on-going project will demonstrate the value of off-shore electric field measurements for safety-related decision making at KSC, and may improve our understanding of relative lightning risk to objects on the ground vs. ocean. This presentation will provide an overview of this new instrumentation, and a summary of our progress to date.

Ocean↗
NASA NTRSDate not supplied

A Simplified Model of VIPER Thermal Management System. Part II: Integrated Vehicle

NASA’s Volatiles Investigating Polar Exploration Rover (VIPER) thermal management system (TMS) relies on four loop heat pipes (LHPs) to transport electronic waste heat to the vehicle cooling radiative surface and avoid overheating. The TMS has also ten constant conductance heat pipes (CCHPs) dedicated to balance the thermal load within the internal environment where the avionics boxes are mounted, also called warm electronic box (WEB), and to transport the heat from two of the science payload instruments. The TMS also uses two thermal straps to thermally link the batteries to the WEB. These thermal components, in addition to heaters, thermostat, multi-layer insulation (MLIs), and isolators forms the core of the VIPER TMS. The complex heat transport balance managed by the TMS is challenging to characterize and model. The more fidelity and granularity of a model, the more costly the computational resources needed and the longer the simulation and modeling time. When the priority is to provide quick but reliable assessments of the thermal performance or real time thermal feedback for training of console operators, simplified modeling tools are needed. To satisfy that need, this paper describes the effort to develop and correlate a model of VIPER TMS based on control volume approach. The correlation effort in particular focuses on hibernation, cold thermal balance, and hot thermal balance data from the integrated vehicle thermal vacuum (TVAC) test. Thus, the correlated model captures the heat leaks during hibernations and the performance at two extremes, bounding, operating scenarios.

Loop Heat Pipe↗
NASA NTRSDate not supplied

A Simplified Model of VIPER Thermal Management System. Part II: Integrated Vehicle

NASA’s Volatiles Investigating Polar Exploration Rover (VIPER) thermal management system (TMS) relies on four loop heat pipes (LHPs) to transport electronic waste heat to the vehicle cooling radiative surface and avoid overheating. The TMS has also ten constant conductance heat pipes (CCHPs) dedicated to balance the thermal load within the internal environment where the avionics boxes are mounted, also called warm electronic box (WEB), and to transport the heat from two of the science payload instruments. The TMS also uses two thermal straps to thermally link the batteries to the WEB. These thermal components, in addition to heaters, thermostat, multi-layer insulation (MLIs), and isolators forms the core of the VIPER TMS. The complex heat transport balance managed by the TMS is challenging to characterize and model. The more fidelity and granularity of a model, the more costly the computational resources needed and the longer the simulation and modeling time. When the priority is to provide quick but reliable assessments of the thermal performance or real time thermal feedback for training of console operators, simplified modeling tools are needed. To satisfy that need, this paper describes the effort to develop and correlate a model of VIPER TMS based on control volume approach. The correlation effort in particular focuses on hibernation, cold thermal balance, and hot thermal balance data from the integrated vehicle thermal vacuum (TVAC) test. Thus, the correlated model captures the heat leaks during hibernations and the performance at two extremes, bounding, operating scenarios.

Thermal Modeling↗
NASA NTRS2004

Note on the Effect of Horizontal Gradients for Nadir-Viewing Microwave and Infrared Sounders

Passive microwave and infrared nadir sounders such as the Advanced Microwave Sounding Unit A (AMSU-A) and the Atmospheric InfraRed Sounder (AIRS), both flying on NASA s EOS Aqua satellite, provide information about vertical temperature and humidity structure that is used in data assimilation systems for numerical weather prediction and climate applications. These instruments scan cross track so that at the satellite swath edges, the satellite zenith angles can reach approx. 60 deg. The emission path through the atmosphere as observed by the satellite is therefore slanted with respect to the satellite footprint s zenith. Although radiative transfer codes currently in use at operational centers use the appropriate satellite zenith angle to compute brightness temperature, the input atmospheric fields are those from the vertical profile above the center of the satellite footprint. If horizontal gradients are present in the atmospheric fields, the use of a vertical atmospheric profile may produce an error. This note attempts to quantify the effects of horizontal gradients on AIRS and AMSU-A channels by computing brightness temperatures with accurate slanted atmospheric profiles. We use slanted temperature, water vapor, and ozone fields from data assimilation systems. We compare the calculated slanted and vertical brightness temperatures with AIRS and AMSU-A observations. We show that the effects of horizontal gradients on these sounders are generally small and below instrument noise. However, there are cases where the effects are greater than the instrument noise and may produce erroneous increments in an assimilation system. The majority of the affected channels have weighting functions that peak in the upper troposphere (water vapor sensitive channels) and above (temperature sensitive channels) and are unlikely t o significantly impact tropospheric numerical weather prediction. However, the errors could be significant for other applications such as stratospheric analysis. Gradients in ozone and tropospheric temperature appear to be well captured by the analyses. In contrast, gradients in upper stratospheric and mesospheric temperature as well as upper tropospheric humidity are less well captured. This is likely due in part to a lack of data to specify these fields accurately in the analyses. Advanced new sounders, like AIRS, may help to better specify these fields in the future.

Joiner, J.↗
NASA NTRS2017

Mission Use of the SpaceCube Hybrid Data Processing System

The award-winning SpaceCube v2.0 system is a high performance, reconfigurable, hybrid data processing system that can be used in a multitude of applications including those that require a radiation hardened and reliable solution. This presentation provides an overview of the design architecture, flexibility, and the advantages of the modular SpaceCube v2.0 high performance data processing system for space applications. The current state of the proven SpaceCube technology is based on 11 years of engineering and operations. Eight systems have been successfully operated in space starting in 2008 with eight more to be delivered for payload integration in 2018 in support of various missions. This presentation will highlight how this multipurpose system is currently being used to solve design challenges of a variety of independent applications. The SpaceCube hardware adapts to new system requirements by allowing for application-unique interface cards that are utilized by reconfiguring the underlying programmable elements on the core processor card. We will show how this system is being used to improve on a heritage NASA GPS technology, enable a cutting-edge LiDAR instrument, and serve as a typical command and data handling (CDH) computer for a space robotics technology demonstration.Finally, this presentation will highlight the use of the SpaceCube v2.0 system on the Restore-L robotic satellite servicing mission. SpaceCube v2.0 is the central avionics responsible for the real-time vision system and autonomous robotic control necessary to find, capture, and service a national asset weather satellite.

Petrick, Dave↗
NASA NTRSDate not supplied

Analog Environments for Venus Aerosol Instrument and Mission Concept Testing

The most common hypothesis discussed for life on Venus is a habitat in the dense, persistent clouds, which are primarily sulfuric acid with a secondary water component. Although Earth lacks a complete Venus analog environment, several partial analogs exist which can inform our understanding of the requirements for cloud habitability as well as serving as potential testbeds for future Venus instruments or missions. Earth’s tropospheric clouds have larger particles, more water, and shorter lifetimes than Venus’s; however, they have a partial overlap in pressure and temperature, and are our only example of an airborne habitat.They can inform how particle residence time and microbial generation time constrain habitable atmospheric regions. On the biological side, this includes available nutrients and energy, environmental stressors such as radiation, osmotic potential and acidity, and time spent in protective but inactive forms (endospores, cysts, akinetes); on the physical side, gravity, air density and viscosity, thermal lofting, gravity waves, scavenging due to precipitation, and other airflow dynamics, as well as effective particle radius and electrical charge. They can also enable sampling strategy tests for airborne life detection, ranging from10 2 to10 8 viable cells/mL (10 -3 to 10 -9 cells/particle). Conversely, Earth's stratospheric sulfate layer lacks an active microbial presence, and is at a colder and less dense altitude but has partially analogous values in terms of H2SO4 and water concentration, particle size, and number density. These aerosols are accessible to aircraft and high-altitude balloons. Even more accessible potential analogs include sea spray, which overlaps with the smaller (haze) particle sizes and densities at Venus and contains trace organic constituents; marine fog, which at higher densities can match Venus’s larger (Mode 2) particle properties and contains a range of trace compounds including ammonia, phosphates, sulfates, and nitrates; and spray from acidic hydrothermal systems, which can cover a wide variety of sizes, densities, and chemical compositions. These analogs could improve the development of Venus cloud sampling instruments or sondes, including field tests of material compatibility, particle capture efficiency, and analysis sensitivity.

Analog↗
NASA NTRS1995

From LDEF to a national Space Environment and Effects (SEE) program: A natural progression

As the LDEF program draws to a close, it leaves in place the fundamental building blocks for a Space Environment and Effects (SEE) program. Results from LDEF data analyses and investigations now form a substantial core of knowledge on the long term effects of the space environment on materials, system and structures. In addition, these investigations form the basic structure of a critically-needed SEE archive and database system. An agency-wide effort is required to capture all elements of a SEE program to provide a more comprehensive and focused approach to understanding the space environment, determining the best techniques for both flight and ground-based experimentation, updating the models which predict both the environments and those effects on subsystems and spacecraft, and, finally, ensuring that this multitudinous information is properly maintained, and inserted into spacecraft design programs. Many parts and pieces of a SEE program already exist at various locations to fulfill specific needs. The primary purpose of this program, under the direction of the Office of Advanced Concepts and Technology (OACT) in NASA Headquarters, is to take advantage of these parts; apply synergisms where possible; identify and when possible fill-in gaps; coordinate and advocate a comprehensive SEE program. The SEE program must coordinate and support the efforts of well-established technical communities wherein the bulk of the work will continue to be done. The SEE program will consist of a NASA-led SEE Steering Committee, consisting of government and industry users, with the responsibility for coordination between technology developers and NASA customers; and Technical Working Groups with primary responsibility for program technical content in response to user needs. The Technical Working Groups are as follows: Materials and Processes; Plasma and Fields; Ionizing Radiation; Meteoroids and Orbital Debris; Neutral External Contamination; Thermosphere, Thermal, and Solar Conditions; Electromagnetic Effects; Integrated Assessments and Databases. Specific technology development tasks will be solicited through a NASA Research Announcement to be released in May of 1994. The areas in which tasks are solicited include: (1) engineering environment definitions, (2) environments and effects design guidelines, (3) environments and effects assessment models and databases, and (4) flight/ground simulation/technology assessment data.

Bowles, David E.↗
NASA NTRS1994

X-ray clusters in a cold dark matter + lambda universe: A direct, large-scale, high-resolution, hydrodynamic simulation

A new, three-dimensional, shock-capturing, hydrodynamic code is utilized to determine the distribution of hot gas in a cold dark matter (CDM) + lambda model universe. Periodic boundary conditions are assumed: a box with size 85/h Mpc, having cell size 0.31/h Mpc, is followed in a simulation with 270(exp 3) = 10(exp 7.3) cells. We adopt omega = 0.45, lambda = 0.55, h identically equal to H/100 km/s/Mpc = 0.6, and then, from the cosmic background explorer (COBE) and light element nucleosynthesis, sigma(sub 8) = 0.77, omega(sub b) = 0.043. We identify the X-ray emitting clusters in the simulation box, compute the luminosity function at several wavelength bands, the temperature function and estimated sizes, as well as the evolution of these quantities with redshift. This open model succeeds in matching local observations of clusters in contrast to the standard omega = 1, CDM model, which fails. It predicts an order of magnitude decline in the number density of bright (h nu = 2-10 keV) clusters from z = 0 to z = 2 in contrast to a slight increase in the number density for standard omega = 1, CDM model. This COBE-normalized CDM + lambda model produces approximately the same number of X-ray clusters having L(sub x) greater than 10(exp 43) erg/s as observed. The background radiation field at 1 keV due to clusters is approximately the observed background which, after correction for numerical effects, again indicates that the model is consistent with observations.

Cen, Renyue↗