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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 541 records · Page 30

Distributions of Beryllium 7 and Lead 210, and Soluble Aerosol-Associated Ionic Species Over the Western Pacific: PEM West B, February - March 1994

Aerosol sampling for the determination of the concentrations of soluble ionic species and the natural radionuclides Be-7 and Pb-210 was conducted from the NASA DC-8 over the western Pacific as part of GTE/PEM-West B during February - March 1994. Concentrations of most soluble ionic species in the free troposphere were higher in samples collected on flights originating from Hong Kong and Japan than those collected further east over the open ocean. In both regions the measured concentrations were higher than those found during PEM-West A (fall 1991). Activities of Pb-210, a tracer of air masses influenced by sources on the Asian continent, showed the same patterns. These data indicate the effect of stronger continental outflow from Asia over the western Pacific during the spring compared to fall season. For readily scavenged aerosol-associated species and soluble acidic gases the strongest indications of Asian outflow were restricted to altitudes below 6 km. The distribution of the continental tracer Pb-210 was also compared to those of a large number of gas phase species measured on the DC-8. Relatively strong correlations were found with O3, and peroxyacetylnitrate (PAN), but only during the flights over the remote Pacific. During PEM-West A, similar correlations were seen, but they were stronger near Asia. We believe that correlations are a signature of continental air that has been processed by deep wet convection over land before being advected over the ocean. One flight over the Sea of Japan provided the opportunity to sample upper troposphere/lower stratosphere air in and around a tropopause fold. Concentrations of Be-7 reached 7 pCi/cu m STP, and peak O3, mixing ratios of 480 ppb were encountered at 10.7 km. The Be-7 data are used to estimate the fraction of stratospheric air mixed down into the troposphere by circulation in the fold.

Dibb, J. E.↗

Distributions of Beryllium 7 and Lead 210, and Soluble Aerosol-Associated Ionic Species Over the Western Pacific: PEM West B

Aerosol sampling for the determination of the concentrations of soluble ionic species and the natural radionuclides Be-7 and Pb-210 was conducted from the NASA DC-8 over the western Pacific as part of GTE/PEM-West B during February - March 1994. Concentrations of most soluble ionic species in the free troposphere were higher in samples collected on flights originating from Hong Kong and Japan than those collected further east over the open ocean. In both regions the measured concentrations were higher than those found during PEM-West A (fall 1991). Activities of Pb-210 tracer of air masses influenced by sources on the Asian continent, showed the same patterns. These data indicate the effect of stronger continental outflow from Asia over the western Pacific during the spring compared to fall season. For readily scavenged aerosol-associated species and soluble acidic gases the strongest indications of Asian outflow were restricted to altitudes below 6 km. The distribution of the continental tracer Pb-210 was also compared to those of a large number of gas phase species measured on the DC-8. Relatively strong correlations were found with O3 and peroxyacetylnitrate (PAN), but only during the flights over the remote Pacific. During PEM-West A, similar correlations were seen, but they were stronger near Asia. We believe that these correlations are a signature of continental air that has been processed by deep wet convection over land before being advected over the ocean. One flight over the Sea of Japan provided the opportunity to sample upper troposphere/lower stratosphere air in and around a tropopause fold. Concentrations of Be-7 reached 7 pCi/cu m STP, and peak O3, mixing ratios of 480 ppb were encountered at 10.7 km. The Be-7 data are used to estimate the fraction of stratospheric air mixed down into the troposphere by circulation in the fold.

Didd, J. E.↗

Cloud and Radiation Studies during SAFARI 2000

Though the emphasis of the Southern Africa Regional Science Initiative 2000 (SAFARI-2000) dry season campaign was largely on emission sources and transport, the assemblage of aircraft (including the high altitude NASA ER-2 remote sensing platform and the University of Washington CV-580, UK MRF C130, and South African Weather Bureau JRA in situ aircrafts) provided a unique opportunity for cloud studies. Therefore, as part of the SAFARI initiative, investigations were undertaken to assess regional aerosol-cloud interactions and cloud remote sensing algorithms. In particular, the latter part of the experiment concentrated on marine boundary layer stratocumulus clouds off the southwest coast of Africa. Associated with cold water upwelling along the Benguela current, the Namibian stratocumulus regime has received limited attention but appears to be unique for several reasons. During the dry season, outflow of continental fires and industrial pollution over this area can be extreme. From below, upwelling provides a rich nutrient source for phytoplankton (a source of atmospheric sulphur through DMS production as well as from decay processes). The impact of these natural and anthropogenic sources on the microphysical and optical properties of the stratocumulus is unknown. Continental and Indian Ocean cloud systems of opportunity were also studied during the campaign. Aircraft flights were coordinated with NASA Terra Satellite overpasses for synergy with the Moderate Resolution Imaging Spectroradiometer (MODIS) and other Terra instruments. An operational MODIS algorithm for the retrieval of cloud optical and physical properties (including optical thickness, effective particle radius, and water path) has been developed. Pixel-level MODIS retrievals (11 km spatial resolution at nadir) and gridded statistics of clouds in th SAFARI region will be presented. In addition, the MODIS Airborne Simulator flown on the ER-2 provided high spatial resolution retrievals (50 m at nadir). These retrievals will be discussed and compared with in situ observations.

Platnick, Steven↗

Optical Measurements for Intelligent Aerospace Propulsion

There is growing interest in applying intelligent technologies to aerospace propulsion systems to reap expected benefits in cost, performance, and environmental compliance. Cost benefits span the engine life cycle from development, operations, and maintenance. Performance gains are anticipated in reduced fuel consumption, increased thrust-toweight ratios, and operability. Environmental benefits include generating fewer pollutants and less noise. Critical enabling technologies to realize these potential benefits include sensors, actuators, logic, electronics, materials, and structures. For propulsion applications, the challenge is to increase the robustness of these technologies so that they can withstand harsh temperatures, vibrations, and grime while providing extremely reliable performance. This paper addresses the role that optical metrology is playing in providing solutions to these challenges. Optics for ground-based testing (development cycle), flight sensing (operations), and inspection (maintenance) are described. Opportunities for future work are presented.

Mercer, Carolyn R.↗

Tropospheric Airborne Meteorological Data and Reporting (TAMDAR) Icing Sensor Performance during the 2003/2004 Alliance Icing Research Study (AIRS II)

NASA Langley Research Center and its research partners from the University of North Dakota (UND) and the National Center for Atmospheric Research (NCAR) participated in the AIRS II campaign from November 17 to December 17, 2003. AIRS II provided the opportunity to compare TAMDAR in situ in-flight icing condition assessments with in situ data from the UND Citation II aircraft's Rosemont system. TAMDAR is designed to provide a general warning of ice accretion and to report it directly into the Meteorological Data Communications and Reporting System (MDCRS). In addition to evaluating TAMDAR with microphysical data obtained by the Citation II, this study also compares these data to the NWS operational in-flight icing Current Icing Potential (CIP) graphic product and with the NASA Advanced Satellite Aviation-weather Products (ASAP) Icing Severity product. The CIP and ASAP graphics are also examined in this study to provide a context for the Citation II's sorties in AIRS II.

Murray, John J.↗

STS-114: Mission Status/Post MMT Briefing

Paul Hill, STS-114 Lead Shuttle Flight Director, and Wayne Hill, Deputy Manager for the Space Shuttle Program and Chair of the Mission Management Team, discusses with the News media the complete operational success of the STS-114 Flight. Paul Hill mentioned the undocking and flight around did occur right on time that day, and checking out Discovery's entry system in preparation for de-orbit on Monday morning. He summarized the long list of flight operations and activities demonstrated like various forms of inspections on RCC and tile, gap fillers and blanket, imagery and photography, three space walks and re-supply. Wayne Hill talked about flight control check out, pre-entry plans, opportunity landing in Cape Carneval, Florida and back-up landing operations in Edwards Air Force Base, California. He emphasized the concern for crew and public safety during landing. News media focused their questions on public expectations and feelings about the return of the Shuttle to Earth, analysis of mechanical and technical failures, safety of dark or daylight landings.

Source record↗

Exploring Modeling Options and Conversion of Average Response to Appropriate Vibration Envelopes for a Typical Cylindrical Vehicle Panel with Rib-stiffened Design

Although applications for Statistical Energy Analysis (SEA) techniques are more widely used in the aerospace industry today, opportunities to anchor the response predictions using measured data from a flight-like launch vehicle structure are still quite valuable. Response and excitation data from a ground acoustic test at the Marshall Space Flight Center permitted the authors to compare and evaluate several modeling techniques available in the SEA module of the commercial code VA One. This paper provides an example of vibration response estimates developed using different modeling approaches to both approximate and bound the response of a flight-like vehicle panel. Since both vibration response and acoustic levels near the panel were available from the ground test, the evaluation provided an opportunity to learn how well the different modeling options can match band-averaged spectra developed from the test data. Additional work was performed to understand the spatial averaging of the measurements across the panel from measured data. Finally an evaluation/comparison of two conversion approaches from the statistical average response results that are output from an SEA analysis to a more useful envelope of response spectra appropriate to specify design and test vibration levels for a new vehicle.

Harrison, Phil↗

Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% was shown on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗

Transcriptomics-based Machine Learning (ML) Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗

Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% was shown on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗

Methodology and Results of the Near-Earth Object (NEO) Human Space Flight (HSF) Accessible Targets Study (NHATS)

Near-Earth Asteroids (NEAs) have been identified by the Administration as potential destinations for human explorers during the mid-2020s. Planning such ambitious missions requires selecting potentially accessible targets from the growing known population of 8,008 NEAs. NASA is therefore conducting the Near-Earth Object (NEO) Human Space Flight (HSF) Accessible Targets Study (NHATS), in which the trajectory opportunities to all known NEAs are being systematically evaluated with respect to a set of defined constraints. While the NHATS algorithms have identified hundreds of NEAs which satisfy purposely inclusive trajectory constraints, only a handful of them offer truly attractive mission opportunities in the time frame of greatest interest. In this paper we will describe the structure of the NHATS algorithms and the constraints utilized in the study, present current study results, and discuss various mission design considerations for future human space flight missions to NEAs.

Barbee, Brent W.↗

Support of Helicopter 'Free Flight' Operations in the 1996 Olympics

The microcosm of activity surrounding the 1996 Olympic Games provided researchers an opportunity for demonstrating state-of-the art technology in the first large-scale deployment of a prototype digital communication/navigation/surveillance system in a confined environment. At the same time it provided an ideal opportunity for transportation officials to showcase the merits of an integrated transportation system in meeting the operational needs to transport time sensitive goods and provide public safety services under real-world conditions. Five aeronautical CNS functions using a digital datalink system were chosen for operational flight testing onboard 91 aircraft, most of them helicopters, participating in the Atlanta Short-Haul Transportation System. These included: GPS-based Automatic Dependent Surveillance, Cockpit Display of Traffic Information, Controller-Pilot Communications, Graphical Weather Information (uplink), and Automated Electronic Pilot Reporting (downlink). Atlanta provided the first opportunity to demonstrate, in an actual operating environment, key datalink functions which would enhance flight safety and situational awareness for the pilot and supplement conventional air traffic control. The knowledge gained from such a large-scale deployment will help system designers in development of a national infrastructure where aircraft would have the ability to navigate autonomously.

Branstetter, James R.↗

Hyper-X Engine Design and Ground Test Program

The Hyper-X Program, NASA's focused hypersonic technology program jointly run by NASA Langley and Dryden, is designed to move hypersonic, air-breathing vehicle technology from the laboratory environment to the flight environment, the last stage preceding prototype development. The Hyper-X research vehicle will provide the first ever opportunity to obtain data on an airframe integrated supersonic combustion ramjet propulsion system in flight, providing the first flight validation of wind tunnel, numerical and analytical methods used for design of these vehicles. A substantial portion of the integrated vehicle/engine flowpath development, engine systems verification and validation and flight test risk reduction efforts are experimentally based, including vehicle aeropropulsive force and moment database generation for flight control law development, and integrated vehicle/engine performance validation. The Mach 7 engine flowpath development tests have been completed, and effort is now shifting to engine controls, systems and performance verification and validation tests, as well as, additional flight test risk reduction tests. The engine wind tunnel tests required for these efforts range from tests of partial width engines in both small and large scramjet test facilities, to tests of the full flight engine on a vehicle simulator and tests of a complete flight vehicle in the Langley 8-Ft. High Temperature Tunnel. These tests will begin in the summer of 1998 and continue through 1999. The first flight test is planned for early 2000.

Voland, R. T.↗

Micro Raman Spectroscopy for Characterizing Molecular Contamination on Space Flight Hardware

In the field of contamination control,many unknowns exist. Often, contamination control engineers have to utilize multiple spectroscopic, macroscopic, and microscopic tools to identify contamination sources when there is a potential contamination exposure to space flight hardware. Understanding the chemical composition of the molecular contamination provides an opportunity for contamination control engineers to determine if this contamination is problematic or benign. In this study, an existing witness plate program for monitoring space flight hardware during the assembly, integration, and testing phases is coupled with micro Raman spectroscopy analysis. The main goal of this study is to determine the limitations, reproducibility, and throughput of micro Raman spectroscopy for characterizing molecular contamination. Micro Raman Spectroscopy will be an additional tool used by contamination control engineers to monitor the cleanliness of space flight hardware.

Microscope↗

Simulated spaceflight effects on mating and pregnancy of rats

The mating of rats was studied to determine the effects of: simulated reentry stresses at known stages of pregnancy, and full flight simulation, consisting of sequential launch stresses, group housing, mating opportunity, diet, simulated reentry, and postreentry isolation of male and female rats. Uterine contents, adrenal mass and abdominal fat as a proportion of body mass, duration of pregnancy, and number and sex of offspring were studied. It is found that: (1) parturition following full flight simulation was delayed relative to that of controls; (2) litter size was reduced and resorptions increased compared with previous matings in the same group of animals; and (3) abdominal fat was highly elevated in animals that were fed the Soviet paste diet. It is suggested that the combined effects of diet, stress, spacecraft environment, and weightlessness decreased the probability of mating or of viable pregnancies in the Cosmos 1129 flight and control animals.

Sabelman, E. E.↗

Distributed science operations for JPL planetary missions

Advances in spacecraft, flight instruments, and ground systems provide an impetus and an opportunity for scientific investigation teams to take direct control of their instruments' operations and data collection while at the same time, providing a cost effective and flexible approach in support of increasingly complex science missions. Operations of science instruments have generally been integrated into planetary flight and ground systems at a very detailed level. That approach has been successful, but the cost of incorporating instrument expertise into the central mission operations system has been high. This paper discusses an approach to simplify planetary science operations by distributing instrument computing and data management tasks from the central mission operations system to each investigator's home center of observational expertise. Some early results of this operations concept will be presented based on the Mars Observer (MO) Project experience and Cassini Project plans.

Benson, Richard D.↗

Proceedings of the NASA Aerospace Technology Symposium 2002

Reports are presented from the NASA Aerospace Technology Symposium 2002 on the following: Geo-Referenced Altitude Hold For Latex Ballons; NASA Spaceport Research: Opportunities For space Grant and EPSCoR Involvement; Numerical Simulation Of The Combustion Of Fuel Droplets: Applications, Aircraft/Spacecraft Flight Control, Guidance Navigation; Expertise In System Dynamics and Control, Control Theory and Aerospace Education Ooutreach Opportunities; and Technology For The Improvement Of General Aviation Security: A Needs Assessmemt.

Bowen, Brent D.↗