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American Institute of Aeronautics and Astronautics (AIAA) Papers

  • Evaluating the Efficiency of a Small Aircraft Transportation System Network Using Planning and Simulation Models (2006)

    This paper presents an evaluation scheme to determine network efficiency parameters (level of service) for an ondemand air transportation service using NASA’s Small Aircraft Transportation System. The analysis employs a large-scale transportation planning model (TSAM) and an operational Monte Carlo network simulation model (MCATS) to study supply and demand network equilibrium conditions for on-demand services. The level of service is an important factor in determining the number of travelers who would use any transportation system including on-demand air taxi services proposed in the SATS Program. In the present version of the Transportation Systems Analysis Model (TSAM) developed by the Air Transportation Systems Laboratory at Virginia Tech (Trani.et al (2003)) it is assumed that SATS services are available within a prescribed accommodation time period (typically one or two hours). This factor is modeled as a schedule delay parameter to account for network inefficiencies. It is also assumed that the cost of using SATS is fixed throughout the network. A life cycle cost model has determined the cost of on-demand services using very light jets to vary from $1.50 to $2.00 per passenger mile.

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  • A Preliminary Assessment of Airport Noise and Emission Impacts Induced by Small Aircraft Transportation System Operations (2006)

    This paper evaluates potential noise and emission impacts associated with an advanced Small Aircraft Transportation System (SATS). Specifically, the analysis presented in this paper quantifies possible noise and emission contributions of advanced single-engine and multi-engine piston-powered aircraft and very light jetpowered aircraft. The noise impact analysis is carried out using the standard Federal Aviation Administration (FAA) Integrated Noise Model (INM). The emission influence is modeled using the FAA Emission and Dispersion Modeling System (EDMS). The noise signature and emission parameters of a new generation Very Light Jet (VLJ) are modeled in our analysis. Major emission pollutant level is estimated at 3,415 airports. Noise contours studies are conducted at five airport noise impact spanning both metropolitan and rural General Aviation (GA) airports. Sensitivity analysis is conducted to evaluate influence of the fleet composition and advanced approach procedures in the present and future years.


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  • Nationwide Impacts of Very Light Jet Traffic in the Future Next Generation Air Transportation System (NGATS) (2006)

    This paper describes a methodology to predict on-demand air taxi services using emerging Very Light Jets (VLJ) technology in the future National Air Transportation System (NAS). The paper describes airspace and airport impacts of VLJ traffic considering an improved Next Generation Air Transportation System (NGATS). The analysis presented fits within the framework of the Transportation Systems Analysis Model (TSAM) developed by the Air Transportation Systems Laboratory at Virginia Tech for NASA Langley Research Center. TSAM uses traditional air transportation systems engineering techniques to: 1) predict the number of intercity trips generated in the country based on socio-economic factors, 2) distribute these trips across the country, 3) predict the most likely modes of transportation used to execute these trips, 4) predict flights and trajectories associated with air transportation trips, and 5) predict impacts of the intercity trips generated in the National Airspace System (NAS).


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  • Integrating Air Transportation System Demand Predictions in Preliminary Aircraft Design (2005)

    This paper describes a methodology to integrate air transportation demand estimates in the preliminary aircraft design process. The paper describes the adaptation of the Transportation Systems Analysis Model (TSAM) developed by the Air Transportation Systems Laboratory at Virginia Tech for NASA Langley Research Center to predict potential demand of aerospace vehicle concepts. TSAM uses traditional air transportation systems engineering techniques to: 1) predict the number of intercity trips generated in the country based on socio-economic factors, 2) distribute these trips across the country, 3) predict the most likely modes of transportation used to execute these trips, 4) predict flights and trajectories associated with air transportation trips, and 5) predict impacts of the intercity trips generated in the National Airspace System (NAS). The paper includes a case study to estimate the potential demand for advanced tilt-rotor aircraft technology operating in the Northeast Corridor in the United States.

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  • A Neural Network Model to Estimate Aircraft Fuel Consumption (2004)

    The purpose of this paper is to present a simplified method to estimate aircraft fuel consumption using an artificial neural network. The models developed here are can be implemented in fast-time airspace and airfield simulation models. A representative neural network aided fuel consumption model was developed using data given in the aircraft performance manual. The data used in this study was applicable to the Fokker 100 aircraft powered by Rolls-Royce Tay 650 engines. A second data set was applied to the SAAB 2000 turboprop aircraft with good results. The methodology can be extended to any type of aircraft including piston and turboprop type vehicles with confidence.
    The neural network was trained to estimate fuel consumption of an example aircraft. Results were compared to the actual performance provided in the aircraft performance manual and found to be accurate for possible implementation in fast-time simulation models. The result from the neural network model was compared with analytical models. The results of this study illustrate that a threelayer artificial neural network with nonlinear transfer func-tions can accurately represent complex aircraft fuel consumption functions for climb, cruise and descent phases of flight.

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Air Transportation Systems Laboratory at Virginia Tech
301-P Patton Hall, Blacksburg, VA 24061
Phone: 540-231-4418 - Fax: 540-231-7532 - eMail: vuela@vt.edu