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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Applications of Remote Sensing for Land Use Planning Scenarios with Suitability Analysis

In regions undergoing rapid urbanization, such as West Africa, land use planning (LUP) is vital to accommodate growing population and manage natural resources. Suitability analysis modeling is a widely used tool in LUP to determine the extent to which a land area is suitable for a designated purpose, but there is a gap in the integration of remote sensing time series data into land use decisions. The goal of this study was to incorporate remote sensing time series information with suitability analyses to inform LUP decisions in urban areas. In the study area of Kumasi, Ghana, land cover trends and land surface temperature (LST) from 2000 to 2019 were used to understand climate change trends. Suitability analyses determined the fitness of land areas for predetermined uses. These background processes informed a genetic algorithm to project plausible futures for three land use scenarios. One scenario represented current land use planning practices for addressing population growth, another scenario prioritized minimizing climate change impacts while also accommodating population growth, and the final scenario focused on both of these climate and population goals in addition to high density urban development. Each of these scenarios was successful in achieving population accommodation and respective climate change mitigation goals. The results for these scenarios provide insight into plausible land use distributions in 2050 based on different planning approaches. The genetic algorithm was able to effectively develop results for each scenario through the integration of remotely sensed trends and suitability models, providing a novel approach to land use decision-making.

remote sensing time series↗
NASA NTRS2023

Aviation 2072: Scenario Planning for Wicked Problems

The world is changing rapidly. And with it, so are the potential futures for humanity. Many of these potential futures pose hidden threats, while others offer new opportunities for aviation and the broader aerospace community. To mitigate these risks and capitalize on opportunities, organizations must work to deeply understand these potential future scenarios and uncover any underlying drivers. Organizations will be more equipped and informed when making strategic investment decisions by better understanding these threats, opportunities, and drivers . The future scenarios and their threats and opportunities described in this paper were identified through a series of extensive brainstorming workshops, collectively titled MADNESS (Mapping for Aviation Driven by Needs Emergence and Satiating Society). These workshops engaged NASA civil servants and contractors with diverse backgrounds through a facilitated process of future scenario development and critique. The participants were led through exercises focused on a time horizon spanning from 2022 to 2072 and on problems that aviation might solve and or create during this period. From the broad results, two patterns of critical uncertainty emerged: “availability” (scarcity versus abundance) and “transparency” (openness versus security and privacy). The successful iteration and ideation across the MADNESS workshops also suggests a repeatable mechanism for strategic risk exploration across a variety of NASA and industry stakeholders.

Mapping↗
NASA NTRS1988

Suggested GOES I-M satellite operational scenarios

Plans for the GOES I-M satellite system are reviewed, focusing on the use of GOES data in severe local storm and tropical cyclone analysis and forecasting. The instrumentation and capabilities of the GOES I-M system, which is expected to be launched beginning in the spring of 1990, are discussed. Sounder and imaging coverage scenarios and scenario timetables are presented.

Shenk, William E.↗
NASA NTRS1986

NASA space plans and scenarios to 2000 and beyond

NASA's research and development plans, as reflected in its missions, goals, and objectives to the year 2000 and beyond, are presented. New starts for the next decade and space program activities are highlighted, including space science and applications, space flight, space stations, space tracking and data systems, and space research and technology. Space programs for the 21st century are also covered.

Source record↗
NASA NTRS1986

The impact of physical and mental tasks on pilot mental workoad

Seven instrument-rated pilots with a wide range of backgrounds and experience levels flew four different scenarios on a fixed-base simulator. The Baseline scenario was the simplest of the four and had few mental and physical tasks. An activity scenario had many physical but few mental tasks. The Planning scenario had few physical and many mental taks. A Combined scenario had high mental and physical task loads. The magnitude of each pilot's altitude and airspeed deviations was measured, subjective workload ratings were recorded, and the degree of pilot compliance with assigned memory/planning tasks was noted. Mental and physical performance was a strong function of the manual activity level, but not influenced by the mental task load. High manual task loads resulted in a large percentage of mental errors even under low mental task loads. Although all the pilots gave similar subjective ratings when the manual task load was high, subjective ratings showed greater individual differences with high mental task loads. Altitude or airspeed deviations and subjective ratings were most correlated when the total task load was very high. Although airspeed deviations, altitude deviations, and subjective workload ratings were similar for both low experience and high experience pilots, at very high total task loads, mental performance was much lower for the low experience pilots.

Berg, S. L.↗
NASA NTRS2015

Exploring NASA Human Spaceflight and Pioneering Scenarios

The life cycle cost analysis of space exploration scenarios is explored via a merger of (1) scenario planning, separating context and (2) modeling and analysis of specific content. Numerous scenarios are presented, leading to cross-cutting recommendations addressing life cycle costs, productivity, and approaches applicable to any scenarios. Approaches address technical and non-technical factors.

cost modeling estimation↗
NASA NTRS2015

Exploring NASA Human Spaceflight and Pioneering Scenarios

The life cycle cost analysis of space exploration scenarios is explored via a merger of (1) scenario planning, separating context and (2) modeling and analysis of specific content. Numerous scenarios are presented, leading to cross-cutting recommendations addressing life cycle costs, productivity, and approaches applicable to any scenarios. Approaches address technical and non-technical factors.

space systems life cycle costs↗
NASA NTRS2006

NAS Demand Predictions, Transportation Systems Analysis Model (TSAM) Compared with Other Forecasts

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Viken, Jeff↗
NASA NTRS2006

Utilizing Traveler Demand Modeling to Predict Future Commercial Flight Schedules in the NAS

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Viken, Jeff↗
NASA NTRS1986

Full-Scale Transport controlled Impact Demonstration

The controlled impact demonstration (CID) test of a transport aircraft took place on December 1, 1984, crashing at a prepared site on Rogers Dry Lakebed, Edwards Air Force Base, California. The demonstration was a setback for the antimisting kerosene (AMK) researchers. The impact conditions, considerably different from the planned scenario, exposed large quantities of degraded AMK and hydraulic fluid and caused unexpectedly hot ignition sources, bulk loss of fuel from the right wing, airflow patterns over the wings and fuselage that were untested on AMK, and fuel intrusion into the lower fuselage. The test was much more severe than planned and is generally considered to be unrepresentative of the type of survivable crash that would benefit from AMK. Ninety-seven percent of the sensors on the fuselage and wing structure, seats, dummies, restraint systems, galley, and bins were active at impact. A wealth of sensor data was collected from this once-in-a-lifetime research test. The flight data recorder experiments on board were also generally successful.

Hayduk, R. J.↗
NASA NTRS1999

Digital Earth Initiative: A Joint Interagency Program

The Digital Earth is a virtual representation of our planet that enables a person to explore and interact with the vast amounts of natural and cultural information gathered about the Earth. The Digital Earth comprises data interfaces and standards enabling access to geo-referenced data from remote sensing, cartographic, demographic, medical, and other sources to respond to questions posed by the user. In a recent address at the California Science Center in Los Angeles, Vice President Al Gore articulated a Digital Earth Vision. That vision spoke to developing a multi-resolution, three-dimensional representation of the planet, into which we can roam and zoom into vast quantities of embedded geo-referenced data. The vision was not limited to moving through space but also allowing travel over a time-line, which can be set for days, years, centuries, or even geological epochs. As prototypes become available, it would also be possible to interact with the Digital Earth in multiple places around the country with access to high-speed networks and at a more limited level of access over the Internet. NASA was asked by the Vice President to lead an interagency initiative that would take steps to bring this vision to the public. This talk describes the start-up and plans of the Digital Earth Interagency Working Group in the formulation of its charter, an architecture reference model for Digital Earth, public/private partnerships, cooperative agreement notices, Digital Earth prototypes, and testbeds. Animations employing technologies for virtual roaming and zooming through multi-resolution satellite data set as prototype systems will be presented along with examples of potential user scenarios. Plans for engaging academia and industry in implementing the Digital Earth initiative will be discussed.

Halem, Milton↗
NASA NTRSDate not supplied

Assessing Flooding Vulnerability to Assist High Water Intervention and Urban Planning Programs in the Charles River Watershed with NASA DEVELOP

The Charles River watershed intersects 35 municipalities within the Boston Metropolitan Area and has a total population of 1.2 million, making it one of the most densely populated watersheds in New England. In recent years, the watershed has observed higher rates of flood inundation, mainly due to increased development, extreme precipitation events, and increased surface runoff. As the frequency of flooding events increases and a changing climate poses an ongoing threat to local communities, governments and organizations in Massachusetts are in need of accurate flood risk assessments. NASA DEVELOP partnered with the Charles River Watershed Association, the Town of Natick’s Office of Sustainability, and the Massachusetts Audubon Society to assess flood vulnerability and susceptibility in the watershed. The team used Landsat 5 Thematic Mapper, Landsat 8 Operational Land Imager, Sentinel-1 C-Band Synthetic Aperture Radar, and Sentinel-2 MultiSpectral Instrument to assess the feasibility of identifying the extent of past flood events using remote sensing. After identifying images that overlapped with reported flood events, the team concluded that it was not feasible to use Earth observation data to detect localized flooding in the time available for this study. Instead, the Federal Emergency Management Agency (FEMA) 100-year floodplain was used as a proxy for areas where flooding may occur. The team used statistical regression analysis and validation and supervised classification to develop a flood susceptibility map, incorporating several flood conditioning factors. The susceptibility maps were calibrated to various thresholds, including two that highlight hypothetical flooding under more liberal and more conservative planning scenarios. These were overlaid with demographic and socioeconomic data to create flood vulnerability maps. The team’s flood susceptibility maps showed an improvement in capturing known flood events over the FEMA 100-year and 500-year floodplain maps. These results will be improved with the addition of stormwater drainage mapping and precipitation data. Results can be used to fill in the gaps to help the stakeholders understand their communities’ vulnerability and susceptibility to flooding and improve their preparedness plans.

Trista Brophy↗
NASA NTRS1988

Using full-mission simulation for human factors research in air transport operations

This study examined state-of-the-art mission oriented simulation and its use in human factors research. Guidelines were developed for doing full-mission human factors research on crew member behavior during simulated air transport operations. The existing literature was reviewed. However, interviews with experienced investigators provided the most useful information. The fundamental scientific and practical issues of behavioral research in a simulation environment are discussed. Guidelines are presented for planning, scenario development, and the execution of behavioral research using full-mission simulation in the context of air transport flight operations . Research is recommended to enhance the validity and productivity of full-mission research by: (1) validating the need for high-fidelity simulation of all major elements in the operational environment, (2) improving methods for conducting full-mission research, and (3) examining part-task research on specific problems through the use of vehicles which contain higher levels of abstraction (and lower fidelity) of the operational environment.

Orlady, Harry W.↗
NASA NTRS1989

Using an instrumented manikin for Space Station Freedom analysis

One of the most intriguing and complex areas of current computer graphics research is animating human figures to behave in a realistic manner. Believable, accurate human models are desirable for many everyday uses including industrial and architectural design, medical applications, and human factors evaluations. For zero-gravity (0-g) spacecraft design and mission planning scenarios, they are particularly valuable since 0-g conditions are difficult to simulate in a one-gravity Earth environment. At NASA/JSC, an in-house human modeling package called PLAID is currently being used to produce animations for human factors evaluation of Space Station Freedom design issues. Presented here is an introductory background discussion of problems encountered in existing techniques for animating human models and how an instrumented manikin can help improve the realism of these models.

Orr, Linda↗
NASA NTRS1993

Natural environment application for NASP-X-30 design and mission planning

The NASA/MSFC Mission Analysis Program has recently been utilized in various National Aero-Space Plane (NASP) mission and operational planning scenarios. This paper focuses on presenting various atmospheric constraint statistics based on assumed NASP mission phases using established natural environment design, parametric, threshold values. Probabilities of no-go are calculated using atmospheric parameters such as temperature, humidity, density altitude, peak/steady-state winds, cloud cover/ceiling, thunderstorms, and precipitation. The program although developed to evaluate test or operational missions after flight constraints have been established, can provide valuable information in the design phase of the NASP X-30 program. Inputting the design values as flight constraints the Mission Analysis Program returns the probability of no-go, or launch delay, by hour by month. This output tells the X-30 program manager whether the design values are stringent enough to meet his required test flight schedules.

Johnson, D. L.↗
NASA NTRS1993

Mission activities planning for a Hermes mission by means of AI-technology

Mission Activities Planning is a complex task to be performed by mission control centers. AI technology can offer attractive solutions to the planning problem. This paper presents the use of a new AI-based Mission Planning System for crew activity planning. Based on a HERMES servicing mission to the COLUMBUS Man Tended Free Flyer (MTFF) with complex time and resource constraints, approximately 2000 activities with 50 different resources have been generated, processed, and planned with parametric variation of operationally sensitive parameters. The architecture, as well as the performance of the mission planning system, is discussed. An outlook to future planning scenarios, the requirements, and how a system like MARS can fulfill those requirements is given.

Pape, U.↗
NASA NTRS2006

Trade Studies of Space Launch Architectures using Modular Probabilistic Risk Analysis

A top-down risk assessment in the early phases of space exploration architecture development can provide understanding and intuition of the potential risks associated with new designs and technologies. In this approach, risk analysts draw from their past experience and the heritage of similar existing systems as a source for reliability data. This top-down approach captures the complex interactions of the risk driving parts of the integrated system without requiring detailed knowledge of the parts themselves, which is often unavailable in the early design stages. Traditional probabilistic risk analysis (PRA) technologies, however, suffer several drawbacks that limit their timely application to complex technology development programs. The most restrictive of these is a dependence on static planning scenarios, expressed through fault and event trees. Fault trees incorporating comprehensive mission scenarios are routinely constructed for complex space systems, and several commercial software products are available for evaluating fault statistics. These static representations cannot capture the dynamic behavior of system failures without substantial modification of the initial tree. Consequently, the development of dynamic models using fault tree analysis has been an active area of research in recent years. This paper discusses the implementation and demonstration of dynamic, modular scenario modeling for integration of subsystem fault evaluation modules using the Space Architecture Failure Evaluation (SAFE) tool. SAFE is a C++ code that was originally developed to support NASA s Space Launch Initiative. It provides a flexible framework for system architecture definition and trade studies. SAFE supports extensible modeling of dynamic, time-dependent risk drivers of the system and functions at the level of fidelity for which design and failure data exists. The approach is scalable, allowing inclusion of additional information as detailed data becomes available. The tool performs a Monte Carlo analysis to provide statistical estimates. Example results of an architecture system reliability study are summarized for an exploration system concept using heritage data from liquid-fueled expendable Saturn V/Apollo launch vehicles.

Mathias, Donovan L.↗
NASA NTRS2003

An Approach to Autonomous Operations for Remote Mobile Robotic Exploration

This viewgraph presentation addresses the use of autonomy for remote mobile robotic exploration. The contents include; 1) Why Use Autonomy?; 2) What Are Some Options? JPL (Reasoning); 3) More Options.. . (Modeling); 4) The CLEaR Control System (Closed Loop Execution and Recovery); 5) Method of Response; 6) Overall Goal; 7) CLEaR in Action; 8) Initial Scenario; 9) Initial Scenario - Planned; 10) Unforeseen Events; and 11) Ongoing Research.

rovers↗