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At least 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

The Determination of Titan Gravity Field from Doppler Tracking of the Cassini Spacecraft

In its tour of the Saturnian system, the spacecraft Cassini is carrying out measurements of the gravity field of Titan, whose knowledge is crucial for constraining the internal structure of the satellite. In the five flybys devoted to gravity science, the spacecraft is tracked in X (8.4 GHz) and Ka band (32.5 GHz) from the antennas of NASA's Deep Space Network. The use of a dual frequency downlink is used to mitigate the effects of interplanetary plasma, the largest noise source affecting Doppler measurements. Variations in the wet path delay are effectively compensated by means of advanced water vapor radiometers placed close to the ground antennas. The first three flybys occurred on February 27, 2006, December 28, 2006, and June 29, 2007. Two additional flybys are planned in July 2008 and May 2010. This paper presents the estimation of the mass and quadrupole field of Titan from the first two flybys, carried out by the Cassini Radio Science Team using a short arc orbit determination. The data from the two flybys are first independently fit using a dynamical model of the spacecraft and the bodies of the Saturnian system, and then combined in a multi-arc solution. Under the assumption that the higher degree harmonics are negligible, the estimated values of the gravity parameters from the combined, multi-arc solution are GM = 8978.1337 +/- 0.0025 km(exp 3) / s(exp 2), J (sub 2) = (2.7221 +/- 0.0185) 10 (exp -5) and C (sub 22) = (1.1159 +/- 0.0040) 10 (exp -5) The excellent agreement (within 1.7 sigma) of the results from the two flybys further increases the confidence in the solution and provides an a posteriori validation of the dynamical model.

Iess, L.↗
NASA NTRSDate not supplied

The View From Out Here: The Solar System Planets as Exoplanet Analogs

As we begin to characterize planets orbiting other stars, one of the most important tools available to us is the collection of disk-integrated solar system observations. To date, these have been limited in how they match up with expected exoplanet observations in terms of wavelength, time, viewing geometry, and separations. The Interstellar Probe mission could push the boundaries of planetary science by providing a much-needed and unique dataset for the solar system viewed as an extrasolar system in advance of the next generation of ground and space-based telescopes. Viewing the solar system at large separations over a long period serves several purposes. It acts as a practical test directly analogous to exoplanet observations under realistic conditions, including such effects as zodiacal dust (e.g., Roberge et al., 2012). Secondly, it allows for both the validation of forward models (that is, simulating a planet and generating spectra) and retrievals (where some of the planetary properties are not known) (e.g., Robinson et al., 2011; Agarwal and Wettlaufer, 2017). Third, the mission pro le would be able to collect data at both high- and low-phase angles, which are lacking for most of the solar system planets (e.g., Mallama and Hilton, 2018). Lastly, the long duration of the proposed mission would allow not only snapshots, but time resolved observations using the same instrument, highlighting the dynamic nature of the planets (e.g., seasonality, storms). The planets need not be resolved to make these observations, which eases instrumentation requirements. Here, we show simulations of what an Interstellar Probe imager would see, improving on work that was part of a white paper submitted to the Planetary Science and Astrobiology Decadal Survey. The opportunity for multiple full orbits for most of the solar system planets, including a full phase curve of Saturn, is unique and worth pursuing during the development of the Interstellar Probe mission.

Chester Harman↗
NASA NTRS1973

Mariner 9, an instrument of dynamical science

Mariner 9 viewed Mars and its satellites for a period of almost a year, transmitting doppler, time delay, visual images, and spectra to earth from its satellite orbit. This paper reviews the reduction of Mariner 9 data to more accurately define the dynamical characteristics of the Martian system. Primary results include the discovery of triaxiality of Martian gravity field and physical shape of Mars, and the verification of the discrepancy in optical and dynamic flattening. The impact of the Mariner 9 results on future space missions is evaluated in terms of the accuracy of control of a spacecraft in a 24.6 hour synchronous orbit about Mars.

Jordan, J. F.↗
NASA NTRS1992

Transient loads analysis for space flight applications

A significant part of the flight readiness verification process involves transient analysis of the coupled Shuttle-payload system to determine the low frequency transient loads. This paper describes a methodology for transient loads analysis and its implementation for the Spacelab Life Sciences Mission. The analysis is carried out using two major software tools - NASTRAN and an external FORTRAN code called EZTRAN. This approach is adopted to overcome some of the limitations of NASTRAN's standard transient analysis capabilities. The method uses Data Recovery Matrices (DRM) to improve computational efficiency. The mode acceleration method is fully implemented in the DRM formulation to recover accurate displacements, stresses, and forces. The advantages of the method are demonstrated through a numerical example.

Thampi, S. K.↗
DOE OSTI2016

An X-band waveguide measurement technique for the accurate characterization of materials with low dielectric loss permittivity

In this work, we present a new X-band waveguide (WR90) measurement method that permits the broadband characterization of the complex permittivity for low dielectric loss tangent material specimens with improved accuracy. An electrically long polypropylene specimen that partially fills the cross-section is inserted into the waveguide and the transmitted scattering parameter (S{sub 21}) is measured. The extraction method relies on computational electromagnetic simulations, coupled with a genetic algorithm, to match the experimental S{sub 21} measurement. The sensitivity of the technique to sample length was explored by simulating specimen lengths from 2.54 to 15.24 cm, in 2.54 cm increments. Analysis of our simulated data predicts the technique will have the sensitivity to measure loss tangent values on the order of 10{sup −3} for materials such as polymers with relatively low real permittivity values. The ability to accurately characterize low-loss dielectric material specimens of polypropylene is demonstrated experimentally. The method was validated by excellent agreement with a free-space focused-beam system measurement of a polypropylene sheet. This technique provides the material measurement community with the ability to accurately extract material properties of low-loss material specimen over the entire X-band range. This technique could easily be extended to other frequency bands.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRSDate not supplied

Improving Regional Air Quality Forecasting Through Chemical Data Assimilation and Dynamic Emissions Adjustment

Poor air quality (AQ) is one of the most important human-health and environmental problems facing the United States (US). In addition to the detrimental impacts on human- and environmental-health, poor AQ has an economic cost of ~5% of the US gross domestic product (~$790 billion). AQ managers use AQ analyses and modeling to better understand, anticipate, and avoid poor AQ events. Our research focuses on improving AQ analysis/forecast skill, predictability, and emission estimates through improved and more efficient: (i) modeling and data assimilation strategies; (ii) dynamic emissions adjustment strategies; and (iii) use of satellite remote-sensing Earth observations (e.g., MOPITT, IASI, MODIS, OMI, TROPOMI, TEMPO, etc.). This seminar will review: (i) regional chemical weather forecasting/data assimilation with dynamic emissions adjustment with WRF-Chem/DART; (ii) strategies for efficiently assimilating satellite retrieval profiles with ‘compact phase space retrievals’ (CPSRs); (iii) results from joint assimilation of multiple satellite retrievals at medium (12 km × 12 km) and high (4 km × 4 km) spatial resolutions; and (iv) results from observing system simulation experiments (OSSEs) to investigate whether we can recover COVID-period anthropogenic emissions by assimilating synthetic TEMPO NO2 tropospheric column retrievals with dynamic emissions adjustment. Biographical Sketch: Dr. Mizzi is a Senior Research Fellow working and Dr. Johnson at the NASA Ames Research Center. He holds BA and MS degrees in Environmental Science from the University of Virginia, MS and PhD degrees in Applied Mathematics from the University of Colorado at Boulder (CUB), and a JD degree (with an emphasis in Environmental Law) from the University of Colorado School of Law. He worked at the National Center for Atmospheric Research for nearly 25 years on global atmospheric modeling, dynamic and physical initialization, regional hybrid data assimilation, and most recently on regional chemical data assimilation. He also worked as an environmental attorney and consultant for nearly 15 years. He is an expert in numerical modeling and is recognized internationally as a leading expert in regional, chemical data assimilation with dynamic emissions adjustment. Dr. Mizzi became affiliated with NASA Ames in March 2020 to work on improving AQ analysis/forecast skill, predictability, and ‘top-down’ emissions adjustment though the assimilation of Earth observations. An emphasis of his current work is developing methods for assimilating synthetic TEMPO retrievals to quantify the expected benefits of TEMPO relative to existing AQ observations.

Arthur P. Mizzi↗
NASA NTRS1986

Status and future of lunar geoscience

The Moon is of special interest among the many and diverse bodies of the solar system because it serves as a scientific baseline for understanding the terrestrial planets, its origin is closely tied to the early history of the Earth, and its proximity permits a variety of space applications such as mining and establishment of bases and colonies. Data acquisition and analysis have enabled advances to be made and the remaining questions in many fields of lunar geoscience to be identified. The status and unresolved problems of lunar science are discussed. Immediate needs, new unmanned missions, and a return to the Moon (a lunar base) are examined.

Source record↗
NASA NTRS1986

Earth observing system - Concepts and implementation strategy

The concepts of an Earth Observing System (EOS), an information system being developed by the EOS Science and Mission Requirements Working Group for international use and planned to begin in the 1990s, are discussed. The EOS is designed to study the factors that control the earth's hydrologic cycle, biochemical cycles, and climatologic processes by combining the measurements from remote sensing instruments, in situ measurement devices, and a data and information system. Three EOS platforms are planned to be launched into low, polar, sun-synchronous orbits during the Space Station's Initial Operating Configuration, one to be provided by ESA and two by the United States.

Hartle, R. E.↗
NASA NTRS2004

Regional Assimilation of NASA Atmospheric Infrared Sounder (AIRS) Data

The NASA Short-term Prediction Research and Transition (SPORT) Center seeks to accelerate the infusion of NASA Earth Science Enterprise (ESE) observations, data assimilation and modeling research into NW S forecast operations and decision-making. The Atmospheric Infrared Sounder (AIRS), is expected to advance climate research and weather prediction into the 21 st century. It is one of six instruments onboard Aqua, a satellite that is part of NASA s Earth Observing System. AIRS, along with two partner microwave sounding instruments, represents the most advanced atmospheric sounding system ever deployed in space. The system is capable of measuring the atmospheric temperature in the troposphere with radiosonde accuracies of 1 K over 1 km-thick layers under both clear and cloudy conditions, while the accuracy of the derived moisture profiles will exceed that obtained by radiosondes. It is imperative that the scientific community is prepared to take full advantage of next-generation satellite data that will become available within the next decade. The purpose of this paper is to describe a procedure designed to optimally assimilate AIRS data at high spatial resolution over both land and ocean. The assimilation system used in this study is the Local Analysis and Prediction System (LAPS) developed at the Forecast System Laboratory used extensively around the globe. Results will focus on quality control issues associated with AIRS, optimal assimilation strategies, and the impact of the AIRS data on subsequent numerical forecasts at 12 km produced by the next generation Weather Research and Forecast (WRF) model.

Chou, Shih-Hung↗
NASA NTRS2012

Lidar Remote Sensing of Forests: New Instruments and Modeling Capabilities

Lidar instruments provide scientists with the unique opportunity to characterize the 3D structure of forest ecosystems. This information allows us to estimate properties such as wood volume, biomass density, stocking density, canopy cover, and leaf area. Structural information also can be used as drivers for photosynthesis and ecosystem demography models to predict forest growth and carbon sequestration. All lidars use time-in-flight measurements to compute accurate ranging measurements; however, there is a wide range of instruments and data types that are currently available, and instrument technology continues to advance at a rapid pace. This seminar will present new technologies that are in use and under development at NASA for airborne and space-based missions. Opportunities for instrument and data fusion will also be discussed, as Dr. Cook is the PI for G-LiHT, Goddard's LiDAR, Hyperspectral, and Thermal airborne imager. Lastly, this talk will introduce radiative transfer models that can simulate interactions between laser light and forest canopies. Developing modeling capabilities is important for providing continuity between observations made with different lidars, and to assist the design of new instruments. Dr. Bruce Cook is a research scientist in NASA's Biospheric Sciences Laboratory at Goddard Space Flight Center, and has more than 25 years of experience conducting research on ecosystem processes, soil biogeochemistry, and exchange of carbon, water vapor and energy between the terrestrial biosphere and atmosphere. His research interests include the combined use of lidar, hyperspectral, and thermal data for characterizing ecosystem form and function. He is Deputy Project Scientist for the Landsat Data Continuity Mission (LDCM); Project Manager for NASA s Carbon Monitoring System (CMS) pilot project for local-scale forest biomass; and PI of Goddard's LiDAR, Hyperspectral, and Thermal (G-LiHT) airborne imager.

Cook, Bruce D.↗
NASA NTRS2016

Beaconless Pointing for Deep-Space Optical Communication

Free space optical communication is of interest to NASA as a complement to existing radio frequency communication methods. The potential for an increase in science data return capability over current radio-frequency communications is the primary objective. Deep space optical communication requires laser beam pointing accuracy on the order of a few microradians. The laser beam pointing approach discussed here operates without the aid of a terrestrial uplink beacon. Precision pointing is obtained from an on-board star tracker in combination with inertial rate sensors and an outgoing beam reference vector. The beaconless optical pointing system presented in this work is the current approach for the Integrated Radio and Optical Communication (iROC) project.

free-space optical communication↗
NASA NTRSDate not supplied

Distributed Lunar Data Platform with Advanced Machine Learning Capabilities in Support of Lunar Science and Exploration

The United States 2020 Space Policy directive declares that NASA, in cooperation with private industry, will “extend human economic activity into deep space by establishing a permanent human presence on the Moon”. This goal will require advanced data management, as well as analysis, modeling and representation of lunar information in order to prepare for Artemis human missions, lunar science investigations and exploration. To meet this requirement, we conceptualize and present an implementation strategy for a distributed platform for lunar data retrieval, inferencing and analysis, which will be based on federated learning and the NASA Celestial Mapping System (CMS). In addition to demonstrating the imperative of enabling lunar-borne data to remain in-situ but still accessible, this presentation will also include examples of how third parties could contribute both datasets and new functionality into this platform using an AI-based data import pipeline and a plug-in architecture respectively.

Artificial Intelligence↗
NASA NTRS2022

Supporting Responsible Machine Learning in Heliophysics

Over the last decade, Heliophysics researchers have increasingly adopted a variety of machine learning methods such as artificial neural networks, decision trees, and clustering algorithms into their workflow. Adoption of these advanced data science methods had quickly outpaced institutional response, but many professional organizations such as the European Commission, the National Aeronautics and Space Administration (NASA), and the American Geophysical Union have now issued (or will soon issue) standards for artificial intelligence and machine learning that will impact scientific research. These standards add further (necessary) burdens on the individual researcher who must now prepare the public release of data and code in addition to traditional paper writing. Support for these is not reflected in the current state of institutional support, community practices, or governance systems. We examine here some of these principles and how our institutions and community can promote their successful adoption within the Heliophysics discipline.

Machine learning↗
NASA NTRS1988

Oceanographic wide field sensor

The Oceanographic Wide Field Sensor (SeaWiFS) science project will provide measurements of ocean color from space to which will support research into: (1) the character of ocean physical and biological processes; (2) to assess the global oceanic biomass; and (3) to better understand the role of oceanic processes in modulating the Earth's biogeochemical cycles, including the CO2 cycle as it is affected by fossil fuel combustion. The present work extends previous work to study the feasibility of an ocean color mission using the proposed compact Wide-Field Sensor (SeaWiFS) and the EOSAT Corporation's LANDSAT-6 satellite. A Phase A study was conducted which defines a NASA Facility Data System and accompanying Science Program for the EOSAT Company's commercial ocean color instrument called SeaWiFS to be launched on board LANDSAT-6 in 1991.

Kirk, R. G.↗
NASA NTRS2009

An Overview of the Microgravity Science Glovebox (MSG) Facility and the Research Performed in the MSG on the International Space Station (ISS)

The Microgravity Science Glovebox (MSG) is a double rack facility aboard the International Space Station (ISS) designed for investigation handling. The MSG has been operating on the ISS since July 2002 and is currently located in the Columbus Laboratory Module. The unique design of the facility allows it to accommodate science and technology investigations in a workbench type environment. The facility has an enclosed working volume that is held at a negative pressure with respect to the crew living area. This allows the facility to provide two levels of containment for small parts, particulates, fluids, and gases. This containment approach protects the crew from possible hazardous operations that take place inside the MSG work volume. Research investigations operating inside the MSG are provided a large 255 liter enclosed work space, 1000 watts of dc power via a versatile supply interface (120, 28, +/- 12, and 5 Vdc), 1000 watts of cooling capability, video and data recording and real time downlink, ground commanding capabilities, access to ISS Vacuum Exhaust and Vacuum Resource Systems, and gaseous nitrogen supply. These capabilities make the MSG one of the most utilized facilities on ISS. In fact, the MSG has been used for over 5000 hours of scientific payload operations. MSG investigations involve research in cryogenic fluid management, fluid physics, spacecraft fire safety, materials science, combustion, plant growth, and life support technologies. MSG is an ideal platform for science investigations and research required to advance the technology readiness levels (TRLs) applicable to the Constellation Program. This paper will provide an overview of the MSG facility, a synopsis of the research that has already been accomplished in the MSG, an overview of future investigations currently planned for operation in the MSG, and potential applications of MSG investigations that can provide useful data to the Constellation Program. In addition, this paper will address the role of the MSG facility in the ISS National Lab.

Spivey, Reggie↗
NASA NTRS2008

An Overview of the Microgravity Science Glovebox (MSG) Facility, and the Gravity-Dependent Phenomena Research Performed in the MSG on the International Space Station (ISS)

The Microgravity Science Glovebox (MSG) is a double rack facility aboard the International Space Station (ISS) designed for gravity-dependent phenomena investigation handling. The MSG has been operating in the ISS US Laboratory Module since July 2002. The MSG facility provides an enclosed working area for investigation manipulation and observation, The MSG's unique design provides two levels of containment to protect the ISS crew from hazardous operations. Research investigations operating inside the MSG are provided a large 255 liter work volume, 1000 watts of dc power via a versatile supply interface (120, 28, +/-12, and 5 Vdc), 1000 watts of cooling capability, video and data recording and real time downlink, ground commanding capabilities, access to ISS Vacuum Exhaust and Vacuum Resource Systems, and gaseous nitrogen supply. With these capabilities, the MSG is an ideal platform for research required to advance the technology readiness levels (TRL) needed for the Crew Exploration Vehicle and the Exploration Initiative. Areas of research that will benefit from investigations in the MSG include thermal management, fluid physics, spacecraft fire safety, materials science, combustion, reaction control systems, in situ fabrication and repair, and advanced life support technologies. This paper will provide a detailed explanation of the MSG facility, a synopsis of the research that has already been accomplished in the MSG and an overview of investigations planning to operate in the MSG. In addition, this paper will address possible changes to the MSG utilization process that will be brought about by the transition to ISS as a National Laboratory.

Spivey, Reggie A.↗
NASA NTRSDate not supplied

Nearest-Neighbor Machine Learning Feature Selection for Interpretation of Microbial Molecular Signatures from Isotope Ratio Mass Spectrometry Data

Mass spectrometry (MS) promises to be a powerful tool for potential biosignature detection during astrobiological missions on ocean worlds in our solar system. Accurate and generalizable machine learning methods could enhance science return on investment by predicting seawater chemistry and classifying isotopic biosignatures, either as a signature consistent with microbial life (biotic) or as a novelty (unclassified/unique). However, machine learning models are likely to be complex and involve interactions between MS features, making biosignatures difficult to interpret. Feature selection methods provide biological and chemical context that help interpret the mechanisms of machine learning models, but these methods also need the ability to detect complex interactions. Previously, we developed a machine learning feature selection algorithm called nearest-neighbor projected distance regression (NPDR) that has the ability to identify important model features that involve complex interactions and automatically reduce correlation and the dimensionality in a high-dimensional variable space. The standard distance metrics used in NPDR – Manhattan and Euclidean – assume the multivariate data are isotropic, which is often violated in real data due to differences in the covariance between variables. Thus, we extend NPDR to include a random forest distance, and other anisotropic distance metrics, for computing nearest neighbors. We also augment the isotope-ratio MS data with time-series features from the raw MS signal to improve biotic classification. We test NPDR on our novel experimental ocean world seawater analog MS data. We measure isotope fractionations of volatile CO 2 that could be measured in exospheres or plumes. Samples include baseline abiotic conditions using a range of possible seawater chemistry consistent with Europa and Enceladus, and biotic samples that include microbes in these seawaters. We use penalized NPDR with random forest proximity to identify interpretable microbial molecular signatures. We compare features with random forest importance, and we train a classifier that discriminates between biotic and abiotic samples with high accuracy. These ML-trained ocean-world analog MS data could be used to assist in identifying biosignatures during future missions.

geochemistry↗
NASA NTRS2007

The Microgravity Science Glovebox (MSG), a Resource for Gravity-Dependent Phenomena Research on the International Space Station (ISS)

The Microgravity Science Glovebox (MSG) is a double rack facility aboard the International Space Station (ISS) designed for gravity-dependent phenomena investigation handling. The MSG has been operating in the ISS US Laboratory Module since July 2002. The MSG facility provides an enclosed working area for investigation manipulation and observation in the ISS. The MSG s unique design provides two levels of containment to protect the ISS crew from hazardous operations. Research investigations operating inside the MSG are provided a large 255 liter work volume, 1000 watts of dc power via a versatile supply interface (120,28, +/-12, and 5 Vdc), 1000 watts of cooling capability, video and data recording and real time downlink, ground commanding capabilities, access to ISS Vacuum Exhaust and Vacuum Resource Systems, and gaseous nitrogen supply. With these capabilities, the MSG is an ideal platform for research required to advance the technology readiness levels (TRL) needed for the Crew Exploration Vehicle and the Exploration Initiative. Areas of research that will benefit from investigations in the MSG include thermal management, fluid physics, spacecraft fire safety, materials science, combustion and reacting control systems, in situ fabrication and repair, and advanced life support technologies. This paper will provide a detailed explanation of the MSG facility, a synopsis of the research that has already been accomplished in the MSG, an overview of investigations planning to operate in the MSG, and possible augmentations that can be added to the MSG facility to further enhance the resources provided to investigations.

Spivey, Reggie A.↗