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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 55 records · Page 3
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NASA NTRS2003

Developing Passenger Demand Models for International Aviation from/to Egypt: A Case Study of Cairo Airport and Egyptair

This research is concerned with developing passenger demand models for international aviation from/to Egypt. In this context, aviation sector in Egypt is represented by the biggest and main airport namely Cairo airport as well as by the main Egyptian international air carrier namely Egyptair. The developed models utilize two variables to represent aviation demand, namely total number of international flights originating from and attracted to Cairo airport as well as total number of passengers using Egyptair international flights originating from and attracted to Cairo airport. Such demand variables were related, using different functional forms, to several explanatory variables including population, GDP and number of foreign tourists. Finally, two models were selected based on their logical acceptability, best fit and statistical significance. To demonstrate usefulness of developed models, these were used to forecast future demand patterns.

Abbas, Khaled A.↗
NASA NTRS2010

Aviation Frontiers: On-Demand Aircraft

Throughout the 20th Century, NASA has defined the forefront of aeronautical technology, and the aviation industry owes much of its prosperity to this knowledge and technology. In recent decades, centralized aeronautics has become a mature discipline, which raises questions concerning the future aviation innovation frontiers. Three transformational aviation capabilities, bounded together by the development of a Free Flight airspace management system, have the potential to transform 21st Century society as profoundly as civil aviation transformed the 20th Century. These mobility breakthroughs will re-establish environmental sustainable centralized aviation, while opening up latent markets for civil distributed sensing and on-demand rural and regional transportation. Of these three transformations, on-demand aviation has the potential to have the largest market and productivity improvement to society. The information system revolution over the past 20 years shows that vehicles lead, and the interconnecting infrastructure to make them more effective follows; that is, unless on-demand aircraft are pioneered, a distributed Air Traffic Control system will likely never be established. There is no single technology long-pole that will enable on-demand vehicle solutions. However, fully digital aircraft that include electric propulsion has the potential to be a multi-disciplinary initiator of solid state technologies that can provide order of magnitude improvements in the ease of use, safety/reliability, community and environmental friendliness, and affordability.

Moore, Mark D.↗
NASA NTRS2010

Managing Demand and Capacity Using Multi-Sector Planning and Flexible Airspace: Human-in-the-Loop Evaluation of NextGen

When demand for an airspace sector exceeds capacity, the balance can be re-established by reducing the demand, increasing the capacity, or both. The Multi-Sector Planner (MSP) concept has been proposed to better manage traffic demand by modifying trajectories across multiple sectors. A complementary approach to MSP, called Flexible Airspace Management (FAM), reconfigures the airspace such that capacity can be reallocated dynamically to balance the traffic demand across multiple sectors, resulting in fewer traffic management initiatives. The two concepts have been evaluated with a series of human-in-the-loop simulations at the Airspace Operations Laboratory to examine and refine the roles of the human operators in these concepts, as well as their tools and procedural requirements. So far MSP and FAM functions have been evaluated individually but the integration of the two functions is desirable since there are significant overlaps in their goals, geographic/temporal scope of the problem space, and the implementation timeframe. Ongoing research is planned to refine the humans roles in the integrated concept.

Lee, Paul U.↗
NASA NTRS2015

Understanding Air Transportation Market Dynamics Using a Search Algorithm for Calibrating Travel Demand and Price

This paper presents a search algorithm based framework to calibrate origin-destination (O-D) market specific airline ticket demands and prices for the Air Transportation System (ATS). This framework is used for calibrating an agent based model of the air ticket buy-sell process - Airline Evolutionary Simulation (Airline EVOS) -that has fidelity of detail that accounts for airline and consumer behaviors and the interdependencies they share between themselves and the NAS. More specificially, this algorithm simultaneous calibrates demand and airfares for each O-D market, to within specified threshold of a pre-specified target value. The proposed algorithm is illustrated with market data targets provided by the Transportation System Analysis Model (TSAM) and Airline Origin and Destination Survey (DB1B). Although we specify these models and datasources for this calibration exercise, the methods described in this paper are applicable to calibrating any low-level model of the ATS to some other demand forecast model-based data. We argue that using a calibration algorithm such as the one we present here to synchronize ATS models with specialized forecast demand models, is a powerful tool for establishing credible baseline conditions in experiments analyzing the effects of proposed policy changes to the ATS.

Kumar, Vivek↗
NASA NTRSDate not supplied

Communication Demand in the National Airspace - A Federated Learning Approach

Within the national airspace system (NAS), efficient use of spectrum remains a challenge; as UAS and UAM missions evolve, the amount of mission-critical aircraft communications are expected to significantly grow. To accommodate the increased demand, NASA Glenn Research Center is investigating artificial intelligence approaches that could dynamically allocate spectrum; however, these solutions are driven by communication and aviation data items, many of which are not directly available. One such cornerstone data item is communication demand, parameterizing the needs within a sector in terms that may directly inform spectrum allocation, such as channel access duration, bandwidth, and modulation type. This paper considers the complexity of predicting communication demand as a function of NAS behaviors. Unlike prior prediction work in communications, this research must consider how the NAS may be impacted by external factors - such as convective weather and closures - rather than estimating demand from time-series forecasting alone. Much of this research considers a federated learning design to predict communication events in terms of the type of event occurring (sector coordination, conflict resolution, etc.). To do so, an investigation of products from Sherlock Data Warehouse is conducted, identifying the trends, sufficiency, and correlations of each product to identified events. Additionally, a preliminary discussion for inferring associations between these event types and their communication parameters (duration, bandwidth, modulation) is presented. By utilizing federated learning, imbalances in the types of events and data present throughout the NAS can inform local models without impairing global training. Furthermore, the two-stage approach proposed allows for robust and speculative communication modelling, as communication techniques continue to evolve. As a result, this model enables a generalized approach to understanding NAS communications which is able to inform long-term changes to aviation spectrum management.

Nathan Schimpf↗
NASA NTRSDate not supplied

A Federated Learning Approach to Predicting Communication Demand in the National Airspace

Within the national airspace system (NAS), efficient use of spectrum remains a challenge; as UAS and UAM missions evolve, the amount of mission-critical aircraft communications are expected to significantly grow. To accommodate the increased demand, NASA Glenn Research Center is investigating artificial intelligence approaches that could dynamically allocate spectrum; however, these solutions are driven by communication and aviation data items, many of which are not directly available. One such cornerstone data item is communication demand, parameterizing the needs within a sector in terms that may directly inform spectrum allocation, such as channel access duration, bandwidth, and modulation type. This paper considers the complexity of predicting communication demand as a function of NAS behaviors. Unlike prior prediction work in communications, this research must consider how the NAS may be impacted by external factors - such as convective weather and closures - rather than estimating demand from time-series forecasting alone. Much of this research considers a federated learning design to predict communication events in terms of the type of event occurring (sector coordination, conflict resolution, etc). To do so, an investigation of products from Sherlock Data Warehouse is conducted, identifying the trends, sufficiency, and correlations of each product to identified events. Additionally, a preliminary discussion for inferring associations between these event types and their communication parameters (duration, bandwidth, modulation) is presented. By utilizing federated learning, imbalances in the types of events and data present throughout the NAS can inform local models without impairing global training. Furthermore, the two-stage approach proposed allows for robust and speculative communication modelling, as communication techniques continue to evolve. As a result, this model enables a generalized approach to understanding NAS communications which is able to inform long-term changes to aviation spectrum management.

Nathan Schimpf↗
NASA NTRS2022

Estimating groundwater use and demand in arid Kenya through assimilation of satellite data and in-situ sensors with machine learning toward drought early action

Groundwater is an important source of water for people, livestock, and agriculture during drought in the Horn of Africa. In this work, areas of high groundwater use and demand in drought-prone Kenya were identified and forecasted prior to the dry season. Estimates of groundwater use were extended from a sentinel network of 69 in-situ sensored mechanical boreholes to the region with satellite data and a machine learning model. The sensors contributed 756 site-month observations from June 2017 to September 2021 for model building and validation at a density of approximately one sensor per 3700 sq.km. An ensemble of 19 parameterized algorithms was informed by features including satellite-derived precipitation, surface water availability, vegetation indices, hydrologic land surface modeling, and site characteristics to dichotomize high groundwater pump utilization. Three operational definitions of high demand on groundwater infrastructure were considered: 1) mechanical runtime of pumps greater than a quarter of a day (6+ hr) and daily per capita volume extractions indicative of 2) domestic water needs (35+ L), and 3) intermediate needs including livestock (75+ L). Gridded interpolation of localized groundwater use and demand was provided from 2017 to 2020 and forecasted for the 2021 dry season, June–September 2021. Cross-validated skill for contemporary estimates of daily pump runtime and daily volume extraction to meet domestic and intermediate water needs was 68%, 69%, and 75%, respectively. Forecasts were externally validated with an accuracy of at least 56%, 70%, or 72% for each groundwater use definition. The groundwater maps are accessible to stakeholders including the Kenya National Drought Management Authority (NDMA) and the Famine Early Warning Systems Network (FEWS NET). These maps represent the first operational spatially-explicit sub-seasonal to seasonal (S2S) estimates of groundwater use and demand in the literature. Knowledge of historical and forecasted groundwater use is anticipated to improve decision-making and resource allocation for a range of early warning early action applications.

Katie Fankhauser↗
NASA NTRS2017

Development and Validation of an Automated Simulation Capability in Support of Integrated Demand Management

Integrated Demand Management (IDM) is a near- to mid-term NASA concept that proposes to address mismatches in air traffic system demand and capacity by using strategic flow management capabilities to pre-condition demand into the more tactical Time-Based Flow Management System (TBFM). This paper describes an automated simulation capability to support IDM concept development. The capability closely mimics existing human-in-the-loop (HITL) capabilities, automating both the human components and collaboration between operational systems, and speeding up the real-time aircraft simulations. Such a capability allows for parametric studies that will inform the HITL simulations, identifying breaking points and parameter values at which significant changes in system behavior occur. This paper also describes the initial validation of individual components of the automated simulation capability, and an example application comparing the performance of the IDM concept under two TBFM scheduling paradigms. The results and conclusions from this simulation compare closely to those from previous HITL simulations using similar scenarios, providing an initial validation of the automated simulation capability.

Integrated Demand Management↗
NASA NTRS1971

Study of an intraurban travel demand model incorporating commuter preference variables

The model is based on the substantial travel data base for the nine-county San Francisco Bay Area, provided by the Metropolitan Transportation Commission. The model is of the abstract type, and makes use of commuter attitudes towards modes and simple demographic characteristics of zones in a region to predict interzonal travel by mode for the region. A characterization of the STOL/VTOL mode was extrapolated by means of a subjective comparison of its expected characteristics with those of modes characterized by the survey. Predictions of STOL demand were made for the Bay Area and an aircraft network was developed to serve this demand. When this aircraft system is compared to the base case system, the demand for STOL service has increased five fold and the resulting economics show considerable benefit from the increased scale of operations. In the previous study all systems required subsidy in varying amounts. The new system shows a substantial profit at an average fare of $3.55 per trip.

Holligan, P. E.↗
NASA NTRS1972

The Market Demand for Air Transportation

Although the presentation will touch upon the areas of market for air transportation, the theoretical foundations of the demand function, the demand models, and model selection and evaluation, the emphasis of the presentation will be on a qualitative description of the factors affecting the demand for air transportation. The presentation will rely heavily on the results of market surveys carried out by the Port of New York Authority, the University of Michigan, and Census of Transportation.

Taneja, N.↗
NASA NTRS1975

Remote sensing inputs to water demand modeling

In an attempt to determine the ability of remote sensing techniques to economically generate data required by water demand models, the Geography Remote Sensing Unit, in conjunction with the Kern County Water Agency of California, developed an analysis model. As a result it was determined that agricultural cropland inventories utilizing both high altitude photography and LANDSAT imagery can be conducted cost effectively. In addition, by using average irrigation application rates in conjunction with cropland data, estimates of agricultural water demand can be generated. However, more accurate estimates are possible if crop type, acreage, and crop specific application rates are employed. An analysis of the effect of saline-alkali soils on water demand in the study area is also examined. Finally, reference is made to the detection and delineation of water tables that are perched near the surface by semi-permeable clay layers. Soil salinity prediction, automated crop identification on a by-field basis, and a potential input to the determination of zones of equal benefit taxation are briefly touched upon.

Estes, J. E.↗
NASA NTRS1978

Demand modelling of passenger air travel: An analysis and extension. Volume 1: Background and summary

The framework for a model of travel demand which will be useful in predicting the total market for air travel between two cities is discussed. Variables to be used in determining the need for air transportation where none currently exists and the effect of changes in system characteristics on attracting latent demand are identified. Existing models are examined in order to provide insight into their strong points and shortcomings. Much of the existing behavioral research in travel demand is incorporated to allow the inclusion of non-economic factors, such as convenience. The model developed is characterized as a market segmentation model. This is a consequence of the strengths of disaggregation and its natural evolution to a usable aggregate formulation. The need for this approach both pedagogically and mathematically is discussed.

Jacobson, I. D.↗
NASA NTRS1978

Demand modelling of passenger air travel: An analysis and extension, volume 2

Previous intercity travel demand models in terms of their ability to predict air travel in a useful way and the need for disaggregation in the approach to demand modelling are evaluated. The viability of incorporating non-conventional factors (i.e. non-econometric, such as time and cost) in travel demand forecasting models are determined. The investigation of existing models is carried out in order to provide insight into their strong points and shortcomings. The model is characterized as a market segmentation model. This is a consequence of the strengths of disaggregation and its natural evolution to a usable aggregate formulation. The need for this approach both pedagogically and mathematically is discussed. In addition this volume contains two appendices which should prove useful to the non-specialist in the area.

Jacobson, I. D.↗
NASA NTRS1979

The 18/30 GHz fixed communications system service demand assessment. Volume 2: Main text

The total demand for communications services, and satellite transmission services at the 4/6 GHz, 12/14 GHz, and 18/30 GHz frequencies is assessed. The services are voice, video, and data services. Traffic demand, by service, is distributed by geographical regions, population density, and distance between serving points. Further distribution of traffic is made among four major end user groups: business, government, institutions and private individuals. A traffic demand analysis is performed on a typical metropolitan city to examine service distribution trends. The projected cost of C and Ku band satellite systems are compared on an individual service basis to projected terrestrial rates. Separation of traffic between transmission systems, including 18/30 GHz systems, is based on cost, user, and technical considerations.

Gabriszeski, T.↗
NASA NTRS1981

The cognitive demands of second order manual control: Applications of the event related brain potential

Three experiments are described in which tracking difficulty is varied in the presence of a covert tone discrimination task. Event related brain potentials (ERPs) elicited by the tones are employed as an index of the resource demands of tracking. The ERP measure reflected the control order variation, and this variable was thereby assumed to compete for perceptual/central processing resources. A fine-grained analysis of the results suggested that the primary demands of second order tracking involve the central processing operations of maintaining a more complex internal model of the dynamic system, rather than the perceptual demands of higher derivative perception. Experiment 3 varied tracking bandwidth in random input tracking, and the ERP was unaffected. Bandwidth was then inferred to compete for response-related processing resources that are independent of the ERP.

Wickens, C.↗
NASA NTRS1982

Non-urban mobile radio market demand forecast

A national nonmetropolitan land mobile traffic model for 1990-2000 addresses user classes, density classes, traffic mix statistics, distance distribution, geographic distribution, price elasticity, and service quality elasticity. Traffic demands for business, special industrial, and police were determined on the basis of surveys in 73 randomly selected nonurban counties. The selected services represent 69% of total demand. The results were extrapolated to all services in the non-SMSA areas of the contiguous United States. Radiotelephone services were considered separately. Total non-SMSA mobile radio demand (one way) estimates are given. General functional requirements include: hand portability, privacy, reduction of blind spots, two way data transmission, position location, slow scan imagery.

Castruccio, P. A.↗
NASA NTRS1984

Trends of jet fuel demand and properties

Petroleum industry forecasts predict an increasing demand for jet fuels, a decrease in the gasoline-to-distillate (heavier fuel) demand ratio, and a greater influx of poorer quality petroleum in the next two to three decades. These projections are important for refinery product analyses. The forecasts have not been accurate, however, in predicting the recent, short term fluctuations in jet fuel and competing product demand. Changes in petroleum quality can be assessed, in part, by a review of jet fuel property inspections. Surveys covering the last 10 years show that average jet fuel freezing points, aromatic contents, and smoke points have trends toward their specification limits.

Friedman, R.↗
NASA NTRS1984

Propulsion options for orbit-on-demand vehicles

Vehicles which can achieve orbit within minutes of a command decision may be needed in the future for a variety of missions. Such orbit-on-demand vehicles may have propulsion requirements that are somewhat different from vehicles designed for routine transportation, but the propulsion evaluation studies of the past need to be considered as a starting point for orbit-on-demand vehicle studies. This paper surveys airbreathing propulsion studies including composite, airturbo-rocket, and scramjet systems and rocket propulsion studies including composite, airturborocket, and scramjet and rocket propulsion studies including dual-fuel and pure hydrocarbon systems. One indication from the results is that a horizontal takeoff airbreathing system with supersonic staging will have a higher development cost than rocket systems primarily because of the cost of the airbreathing engine development. Another indication is that pure hydrocarbon rocket propulsion for a vertical takeoff system may be feasible. Eliminating the requirement for hydrogen fuel may be worthwhile for orbit-on-demand vehicles.

Martin, J. A.↗