SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
The benefits of utilizing remote sensor data in the urban planning process of the Metropolitan Washington Council of Governments are investigated. An evaluation of sensor requirements, a description/ comparison of costs, benefits, levels of accuracy, ease of attainment, and frequency of update possible using sensor versus traditional data acquisition techniques are discussed.
One is likely to read the terms 'land use' and 'land cover' in the same sentence, yet these concepts have different origins and different applications. Land cover is typically analyzed by earth scientists working with remotely sensed images. Land use is typically studied by urban planners who must prescribe solutions that could prevent future problems. This apparent dichotomy has led to different classification systems for land-based data. The works of earth scientists and urban planning practitioners are beginning to come together in the field of spatial analysis and in their common use of new spatial analysis technology. In this context, the technology can stimulate a common 'language' that allows a broader sharing of ideas. The increasing amount of land use and land cover change challenges the various efforts to classify in ways that are efficient, effective, and agreeable to all groups of users. If land cover and land uses can be identified by remote methods using aerial photography and satellites, then these ways are more efficient than field surveys of the same area. New technology, such as high-resolution satellite sensors, and new methods, such as more refined algorithms for image interpretation, are providing refined data to better identify the actual cover and apparent use of land, thus effectiveness is improved. However, the closer together and the more vertical the land uses are, the more difficult the task of identification is, and the greater is the need to supplement remotely sensed data with field study (in situ). Thus, a number of land classification methods were developed in order to organize the greatly expanding volume of data on land characteristics in ways useful to different groups. This paper distinguishes two land based classification systems, one developed primarily for remotely sensed data, and the other, a more comprehensive system requiring in situ collection methods. The intent is to look at how the two systems developed and how they can work together so that land based information can be shared among different users and compared over time.
NASA's Urban Air Mobility (UAM) Sub-Project is engaged in research to support the introduction of air taxis into the National Airspace System. Such operations will require a range of communication, navigation, and surveillance systems. Air vehicles for UAM are under development and will initially have human pilots. Separation from other aircraft, obstacles, and weather may be a pilot responsibility or provided by an operator's ground-based systems. Eventually, air taxis may be flown from the ground or fly autonomously. There will be a need for dispatch services for UAM. This report presents a gap analysis, data and capability requirements, and workstation design concepts for the UAM dispatcher or Fleet Manager (FM) position.
NASA’s Urban Air Mobility (UAM) Sub-Project is engaged in re-search to facilitate the introduction of air taxis into the US National Airspace System. Given the history of conventional aircraft operations, it is clear that dispatcher support will be required for UAM. This paper presents a gap analysis, system requirements, and a workstation design concept for the UAM dispatcher or Fleet Manager (FM) position. The gap analysis focuses on the differences be-tween the tasks of the airline dispatcher and those projected for the FM. FM system capabilities and data requirements are then presented as foundations for soft-ware development. An initial user interface concept is provided. The FM software uses a single, large display. The system supports prediction, monitoring, and task execution. This paper is intended to support FM software design for future air taxi systems.
Designing data acquisition and information retrieval system for urban affairs research
A description is given of the design features of the Small Helium-Cooled Infrared Telescope (IRT) being developed for the 1983 Spacelab 2 mission and the problems encountered during the development of its (1) superfluid helium system requirements, (2) interfaces with Spacelab, and (3) Kennedy Space Center prelaunch operations requirements and restrictions. The IRT comprises cryogenic, IR optical, mechanical, and electronics subsystems. Attention is given the preflight management of superfluid helium by a vacuum maintenance assembly (VMA), which will operate almost continuously until launch and then be deactivated to fly as unavoidable ballast. The objective of IRT design and development is the meeting of IR science and engineering objectives with a relatively low-cost system.
Enabling safe, routine, and high-density flight operations of small UAS at low-altitude over heavily populated urban centers presents a difficult challenge for emerging UAS Traffic Management (UTM) system concepts. Urban operations by definition involve flight over people, property, and infrastructure. Low-altitude urban environments - such as urban canyons – are one of the most difficult areas for UTM to consider. Mission concepts require routine operations in a cluttered radio-frequency (RF) environment with degraded or denied Global Positioning System (GPS) reception. Flights with any appreciable distance will be beyond visual and communications line-of-sight from ground operators. Timely detection and response to emergencies and onboard failures, which is critical for safe aircraft operation, will be difficult. This work seeks to establish a feasible reference autonomy architecture for autonomous vehicles in an urban UTM system, then verifying and validating this architecture within a complete UTM concept point-design and systems analysis study. In this paper, we present the results from the NASA SAFE50 conceptual design and systems study that investigates the trade-space of urban UTM operations. This advanced conceptual design study develops a feasible, verified, validated point-design solution. The SAFE50 point-design concept places emphasis on advanced, highly-autonomous, and highly-capable vehicles that favors intelligent onboard autonomy over direct human control with today's technologies and operating in today's urban environments. This paper focuses on an general overview of the design study, highlighting decisions made in the architectural solution. This paper will presents a summary of the study, architectures, and requirements. We present an overview of the architecture designs as derived from the top-level UTM system. The point-design has been implemented in both simulation and through flight testing of hardware design prototypes. The results from simulation and flight testing as part of the verification and validation process of the reference design study.
Explore the source record for details and available documents.
A viable quality program for the urban mass transit industry, and a management approach to ensure compliance with the program are outlined. Included are: (1) a set of guidelines for quality assurance to be imposed on transit authorities, and a management approach to ensure compliance with them; (2) a management approach to be used by the transit authorities (properties) for assuring compliance with the QA guidelines; and (3) quality assurance guidelines to be imposed by properties and umta for procurement of hardware and systems.
Although cities cover only 2 percent of the Earth's surface, more than 50 percent of the world's people live in urban environments, collectively consuming 75 percent of the Earth's resources. Because of their population densities, reliance on infrastructure, and role as centers of industry, cities will be greatly impacted by, and will play a large role in, the reduction or exacerbation of climate change. However, although urban dwellers are becoming more aware of the need to reduce their carbon usage and to implement adaptation strategies, education efforts on these strategies have not been comprehensive. To meet the needs of an informed and engaged urban population, a more systemic, multiplatform and coordinated approach is necessary. The Climate and Urban Systems Partnership (CUSP) is designed to explore and address this challenge. Spanning four cities-Philadelphia, New York, Pittsburgh, and Washington, DC-the project is a partnership between the Franklin Institute, the Columbia University Center for Climate Systems Research, the University of Pittsburgh Learning Research and Development Center, Carnegie Museum of Natural History, New York Hall of Science, and the Marian Koshland Science Museum of the National Academy of Sciences. The partnership is developing a comprehensive, interdisciplinary network to educate urban residents about climate science and the urban impacts of climate change.
This is an effort to assess the applicability of air and spaceborne photography toward providing data inputs to urban and regional planning, management, and research. Through evaluation of remote sensing inputs to urban change detection systems, analyzing an effort to replicate an existing urban land use data file using remotely sensed data, estimating population and dwelling units from imagery, and by identifying and evaluating a system of urban places ultilizing space photography, it was determined that remote sensing can provide data concerning land use, changes in commercial structure, data for transportation planning, housing quality, residential dynamics, and population density.
Work at the JPL in systems engineering is surveyed with the emphasis on practical experience with large hardware and software systems. Systems concepts in lunar and planetary projects, in the Morgantown project, and in the Urban Health Systems Task are discussed. Goal definition, problem statement, objective and criteria development, and synthesis, analysis, selection and implementation of systems are considered as successive steps in the optimization of the overall system.-
The utility of remote sensing techniques to urban data acquisition problems in several distinct areas was identified. This endeavor included a comparison of remote sensing systems for urban data collection, the extraction of housing quality data from aerial photography, utilization of photographic sensors in urban transportation studies, urban change detection, space photography utilization, and an application of remote sensing techniques to the acquisition of data concerning intra-urban commercial centers. The systematic evaluation of variable extraction for urban modeling and planning at several different scales, and the model derivation for identifying and predicting economic growth and change within a regional system of cities are also studied.
Urban Air Mobility (UAM) vehicles have the potential to augment urban transportation systems, allowing passengers to skip the traffic below for a fee. This emerging market is opening up the design space for a new class of Urban Air Mobility (UAM) vehicles which could be powered by electric propulsion systems to be economical and environmentally friendly. However, development of these UAM concepts presents several additional challenges in the design process. First, these concept designs require including new disciplinary models for subsystems including the electric motors, cables, batteries and thermal management systems. Second, correctly designing and evaluating these various subsystems requires tight coupling between the discipline models to capture interactions. This paper presents the continued development of a multidisciplinary design optimization environment to aid in the development of these vehicle concepts. The multidisciplinary environment fully couples the various subsystem models allowing for the full vehicle to be designed and optimized simultaneously. In this research, the developed modeling approach is demonstrated in the analysis of a small, all-electric quadrotor UAM concept. Results from these studies show that numerous disciplines can be tightly coupled and producing improved overall vehicle designs.
The foreseeable high traffic density suggests that a large number of electric propulsion systems will enter the airspace, and that they will also operate at high frequency, e.g., large number of take offs and landings per unit time. The reliability of such critical systems is therefore key to ensure high safety standards in the low-altitude airspace. Diagnostic systems, which aim at identifying incipient faults, can mitigate unexpected failures or lower-than-expected reliability by performing early fault detection by monitoring the systems. A key element of fault diagnosis is fault detection and isolation (FDI), which complexity increases with the complexity of the system itself, namely the number of subsystems and components, interactions among sub-systems, and the number of sensors available. The proposed approach leverages combination of failure mode and effect analysis (FMEA) integrated with Bayesian networks, thus introducing dependability structures into a diagnostic framework to aid FDI. Faults and failure events from the FMEA are mapped within a Bayesian network, where network edges replicate the links embedded within FMEAs. The integrated framework enables the fault isolation process by identifying the probability of occurrence of specific faults or root causes given evidence observed through sensor signals. In this work, sub systems of Urban Air Mobility (UAM) type vehicle like avionics, structures, power-train etc. are taken into account to show the approach at the system level. This work integrates early design phase in the development of UAM type vehicles with diagnostic tools, which are often developed later in the product life-cycle, or retrofitted at a later time on systems. Failure mode and effect analysis (FMEA) derived for the system in the design phase is embedded within a Bayesian network (BN).
A system of electronic hardware and software, now undergoing development, automatically estimates the location of a robotic land vehicle in an urban environment using a somewhat imprecise map, which has been generated in advance from aerial imagery. This system does not utilize the Global Positioning System and does not include any odometry, inertial measurement units, or any other sensors except a stereoscopic pair of black-and-white digital video cameras mounted on the vehicle. Of course, the system also includes a computer running software that processes the video image data. The software consists mostly of three components corresponding to the three major image-data-processing functions: Visual Odometry This component automatically tracks point features in the imagery and computes the relative motion of the cameras between sequential image frames. This component incorporates a modified version of a visual-odometry algorithm originally published in 1989. The algorithm selects point features, performs multiresolution area-correlation computations to match the features in stereoscopic images, tracks the features through the sequence of images, and uses the tracking results to estimate the six-degree-of-freedom motion of the camera between consecutive stereoscopic pairs of images (see figure). Urban Feature Detection and Ranging Using the same data as those processed by the visual-odometry component, this component strives to determine the three-dimensional (3D) coordinates of vertical and horizontal lines that are likely to be parts of, or close to, the exterior surfaces of buildings. The basic sequence of processes performed by this component is the following: 1. An edge-detection algorithm is applied, yielding a set of linked lists of edge pixels, a horizontal-gradient image, and a vertical-gradient image. 2. Straight-line segments of edges are extracted from the linked lists generated in step 1. Any straight-line segments longer than an arbitrary threshold (e.g., 30 pixels) are assumed to belong to buildings or other artificial objects. 3. A gradient-filter algorithm is used to test straight-line segments longer than the threshold to determine whether they represent edges of natural or artificial objects. In somewhat oversimplified terms, the test is based on the assumption that the gradient of image intensity varies little along a segment that represents the edge of an artificial object.
A study of urban transportation systems are presented characterized by intensive scrutiny of many ideas, philosophies, and academic perspectives. This report is intended to communicate some dimensions of the urban transportation problem to the general public.
Relevant causes of failure by the remote sensing community in the urban scene are analyzed. The reasons for the insignificant role of remote sensing in urban land use data collection are called the law of realism, the incompatibility of remote sensing and urban management system data formats is termed the law of nominal/ordinal systems compatibility, and the land use/population correlation dilemma is referred to as the law of missing persons. The study summarizes the three laws of urban land use information for which violations, avoidance, or ignorance have caused the decline of present remote sensing research. Particular attention is given to the rationale for urban land use information and for remote sensing. It is shown that remote sensing of urban land uses compatible with the three laws can be effectively developed by realizing the 10 percent contribution of remote sensing to urban land use planning data collection.