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New SIMS data for mobile elements in Lonar Crater clay minerals are remarkably similar to data for alteration material in the Lafayette Mars meteorite. This work strongly supports the use of terrestrial analogues for Mars, including a new mass balance model for mobile elements through time. Additional information is contained in the original extended abstract.
The protocol structure of the international aeronautical mobile satellite service (AMSS) is reviewed with emphasis on those aspects of protocol performance, validation, and conformance which are peculiar to mobile services. This is in part an analysis of what can be learned from the AMSS experience with protocols which is relevant to the design of other mobile satellite data networks, e.g., land mobile.
A system that would comprise mobile and stationary electronic hardware and software subsystems has been proposed for collection and automated interpretation of electroencephalographic (EEG) data from subjects in everyday activities in a variety of environments. By enabling collection of EEG data from mobile subjects engaged in ordinary activities (in contradistinction to collection from immobilized subjects in clinical settings), the system would expand the range of options and capabilities for performing diagnoses. Each subject would be equipped with one of the mobile subsystems, which would include a helmet that would hold floating electrodes (see figure) in those positions on the patient s head that are required in classical EEG data-collection techniques. A bundle of wires would couple the EEG signals from the electrodes to a multi-channel transmitter also located in the helmet. Electronic circuitry in the helmet transmitter would digitize the EEG signals and transmit the resulting data via a multidirectional RF patch antenna to a remote location. At the remote location, the subject s EEG data would be processed and stored in a database that would be auto-administered by a newly designed relational database management system (RDBMS). In this RDBMS, in nearly real time, the newly stored data would be subjected to automated interpretation that would involve comparison with other EEG data and concomitant peer-reviewed diagnoses stored in international brain data bases administered by other similar RDBMSs.
A mobile lidar system was used to obtain plume rise and dispersion measurements for validating plume models. Predictions of rise and spread from the two-thirds law were found to agree well with observations. These predictions were used in combination with Lamb's results for neutrally buoyant particle diffusion in the mixed layer to estimate dispersion when convective turbulence became important.
The data from the collimated sensors of the LEND instrument are shown to be of exceptionally high quality. Counting uncertainties are about 0.3% relative and are shown to be the only significant source of random error, thus conclusions based on small differences in count rates are valid. By comparison with the topography of Shoemaker crater, the spatial resolution of the instrument is shown to be consistent with the design value of 5 km for the radius of the circle over which half the counts from the lunar surface would be determined. The observed epithermal-neutron suppression factor due to the hydrogen deposit in Shoemaker crater of 0.25 plus or minus 0.04 cps is consistent with the collimated field-of-view rate of 1.7 cps estimated by Mitrofanov et al. (2010a). The statistical significance of the neutron suppressed regions (NSRs) relative to the larger surrounding polar region is demonstrated, and it is shown that they are not closely related to the permanently shadowed regions. There is a significant increase in H content in the polar regions independent of the H content of the NSRs. The non-NSR H content increases directly with latitude, and the rate of increase is virtually identical at both poles. There is little or no increase with latitude outside the polar region. Various mechanisms to explain this steep increase in the non-NSR polar H with latitude are investigated, and it is suggested that thermal volatilization is responsible for the increase because it is minimized at the low surface temperatures close to the poles.
A new method is presented for handling data resulting from Mobile Satellite propagation experiments such as the Pilot Field Experiment (PiFEx) conducted by JPL. This method uses the UNIX operating system and C programming language. The data management system is implemented on a VAX minicomputer. The system automatically divides the large data file housing data from various experiments under a predetermined format into various individual files containing data from each experiment. The system also has a number of programs written in C and FORTRAN languages to allow the researcher to obtain meaningful quantities from the data at hand.
Aviation is broadly a combination of aircraft, airspace and airports. The data science life cycle comprises of five steps - capture, maintain, process, analyze and communicate. The presentation introduces the legacy of conventional aviation research in the context of the data science life cycle to motivate the challenges with Urban Air Mobility, a field that is quite nascent. A summary of recent research will be presented to highlight the innovative ways to address the challenges. Examples provided will include the generation of synthetic data, encounter models from simulations, and leveraging novel and diverse data sets from traditional transportation and non-aviation sources, to analyze problems of operation in urban airspace. Finally, opportunities will be identified for further exploration, niche development and filling the gaps in the field of data science for UAM.
Aviation is broadly a combination of aircraft, airspace and airports. The data science life cycle comprises of five steps - capture, maintain, process, analyze and communicate. The presentation introduces the legacy of conventional aviation research in the context of the data science life cycle to motivate the challenges with Urban Air Mobility, a field that is quite nascent. A summary of recent research will be presented to highlight the innovative ways to address the challenges. Examples provided will include the generation of synthetic data, encounter models from simulations, and leveraging novel and diverse data sets from traditional transportation and non-aviation sources, to analyze problems of operation in urban airspace. Finally, opportunities will be identified for further exploration, niche development and filling the gaps in the field of data science for UAM.
National Aeronautics and Space Administration (NASA) is spearheading an innovative digital engineering approach to integrate, communicate, and facilitate the research of Urban Air Mobility (UAM) operations. The UAM vision is one in which advanced technologies and new operational procedures enable practical and cost-effective air transport as an integrated mode of movement of people and goods throughout metropolitan areas. To safely support UAM operations at scale in the National Airspace System (NAS), NASA’s Air Traffic Management-Exploration (ATM-X) project has been conducting research that evolves the UAM air traffic management system towards a highly automated and operationally flexible system of the future. The complexity of UAM airspace evolution to accommodate the increasing tempo of UAM operations over time is managed through the UAM airspace research roadmap, which is a system engineering approach to the R&D of complex system-of-systems, where system’s interdependencies make it nearly impossible to define requirements for individual elements of the system in isolation. These interdependencies form a knowledge graph (node-link network) with a highly complex structure far beyond the human user’s ability to extract insights for project management’s research portfolio assessment. This study applies advanced data analytics in knowledge graph to the UAM knowledge graph to facilitate the portfolio assessment.
National Aeronautics and Space Administration (NASA) is spearheading an innovative digital engineering approach to integrate, communicate, and facilitate the research of Urban Air Mobility (UAM) operations. The UAM vision is one in which advanced technologies and new operational procedures enable practical and cost-effective air transport as an integrated mode of movement of people and goods throughout metropolitan areas. To safely support UAM operations at scale in the National Airspace System (NAS), NASA’s Air Traffic Management-Exploration (ATM-X) project has been conducting research that evolves the UAM air traffic management system towards a highly automated and operationally flexible system of the future. The complexity of UAM airspace evolution to accommodate the increasing tempo of UAM operations over time is managed through the UAM airspace research roadmap, which is a system engineering approach to the R&D of complex system-of-systems, where system’s interdependencies make it nearly impossible to define requirements for individual elements of the system in isolation. These interdependencies form a knowledge graph (node-link network) with a highly complex structure far beyond the human user’s ability to extract insights for project management’s research portfolio assessment. This study applies advanced data analytics in knowledge graph to the UAM knowledge graph to facilitate the portfolio assessment.
An adaptive data rate SSMA (spread spectrum multiple access) system is proposed for mobile and personal multimedia satellite communications without the aid of system control earth stations. This system has a constant occupied bandwidth and has variable data rates and processing gains to mitigate communication link impairments such as fading, rain attenuation and interference as well as to handle variable data rate on demand. Proof of concept hardware for 6MHz bandwidth transponder is developed, that uses offset-QPSK (quadrature phase shift keying) and MSK (minimum shift keying) for direct sequence spread spectrum modulation and handle data rates of 4k to 64kbps. The RS422 data interface, low rate voice and H.261 video codecs are installed. The receiver is designed with coherent matched filter technique to achieve fast code acquisition, AFC (automatic frequency control) and coherent detection with minimum hardware losses in a single matched filter circuit. This receiver structure facilitates variable data rate on demand during a call. This paper shows the outline of the proposed system and the performance of the prototype equipment.
The Goddard VLBI group reports the results of analyzing 101 Mark III data sets acquired from mobile observing sites through the end of 1986 and available to the Crustal Dynamics Project. The fixed VLBI observations at Hat Creek, Ft. Davis, Mojave, and OVRO are included as they participate heavily in the mobile schedules. One large solution GLB171 was used to obtain baseline length and transverse evolutions. Radio source positions were estimated globally, while nutation offsets were estimated from each data set. The results include 28 mobile sites.
NASA Advanced Air Mobility (AAM) National Campaign has hosted multiple flight tests in a effort to promote public confidence and accelerate the realization of emerging aviation markets for passenger and cargo transportation in urban, suburban, rural, and regional environments. The goals and objectives for each flight test are intended to assess the performance of the vehicle’s capacity to operate safely, efficiently, and sustainably in urban areas. The Airspace Test and Infrastructure (ATI) team processes the flight data to evaluate the effectiveness of air vehicle and airspace management integration, while its analysis capabilities support the assessment of the efficacy of proposed vehicles and ground systems required to enable the vehicles’ operations. The ATI data services team creates many products from the data, first by transforming and merging the data into a single Integrated Data Product (IDP). This aligns data from many sources by time, so that, for example, the winds that impacted a flight can be aligned with its ground track and speed. A detailed IDP enables many types of statistical computation and visualizations that help researchers understand what transpired during the flight and how it can be explained. This Tech Talk will give an overview of the IDP process, including examples of the resulting products created by the data services team. It will also share an application that will allow participants to perform their own data analysis.
In contrast to most commercial air traffic today, vehicles serving the urban air mobility (UAM) market are anticipated to operate within communities and be close to the public at large. The approved model for assessing environmental impact of air traffic actions in the United States, the Federal Aviation Administration (FAA) Aviation Environmental Design Tool (AEDT), does not directly support analysis of such operations due to a combined lack of UAM aircraft flight performance model data and aircraft noise data. This paper addresses the latter by offering two prediction-based approaches for generation of noise-power-distance (NPD) data for use within AEDT. One utilizes the AEDT fixed-wing aircraft modeling approach and the other utilizes the AEDT rotary-wing aircraft modeling approach.
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Improvements in data quality for the mobile VLBI systems have placed higher accuracy requirements on Earth orientation calibrations. Errors in these calibrations may give rise to systematic effects in the nonlength components of the baselines. Various sources of Earth orientation data were investigated for calibration of Mobile VLBI baselines. Significant differences in quality between the several available sources of UT1-UTC were found. It was shown that the JPL Kalman filtered space technology data were at least as good as any other and adequate to the needs of current Mobile VLBI systems and observing plans. For polar motion, the values from all service suffice. The effect of Earth orientation errors on the accuracy of differenced baselines was also investigated. It is shown that the effect is negligible for the current mobile systems and observing plan.
Aviation is a combination of aircraft, airspace and airports. The data science life cycle comprises of five steps - capture, maintain, process, analyze and communicate. The presentation introduces the legacy of conventional aviation research in the context of the data science life cycle to motivate the challenges with Urban Air Mobility, a field that is quite nascent. A summary of recent research will be presented to highlight the innovative ways to address the challenges. Examples provided will include the generation of synthetic data, encounter models from simulations, and leveraging novel and diverse data sets from traditional transportation and non-aviation sources, to analyze problems of operation in urban airspace. Finally, opportunities will be identified for further exploration, niche development and filling the gaps in the field of data science for UAM.
Aviation is a combination of aircraft, airspace and airports. The data science life cycle comprises of five steps - capture, maintain, process, analyze and communicate. The presentation introduces the legacy of conventional aviation research in the context of the data science life cycle to motivate the challenges with Urban Air Mobility, a field that is quite nascent. A summary of recent research will be presented to highlight the innovative ways to address the challenges. Examples provided will include the generation of synthetic data, encounter models from simulations, and leveraging novel and diverse data sets from traditional transportation and non-aviation sources, to analyze problems of operation in urban airspace. Finally, opportunities will be identified for further exploration, niche development and filling the gaps in the field of data science for UAM.