Economics of Advanced Thin-Haul Concepts and Operations

Author(s)
Harish, Anusha
Perron, Christian
Bavaro, Daniel
Ahuja, Jai
Ozcan, Melek D.
Justin, Cedric Y.
Briceno, Simon
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Daniel Guggenheim School of Aerospace Engineering
The Daniel Guggenheim School of Aeronautics was established in 1931, with a name change in 1962 to the School of Aerospace Engineering
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Abstract
The thin-haul commuter concept refers to an envisioned class of four to nine passenger aircraft operating very short flights and providing scheduled and on-demand air services from smaller airports. Its objective is to enhance regional mobility reach by combining the flexibility of automobile travel with the shorter commute times associated with air travel. To achieve economic viability, the thin-haul commuter concept must provide appreciable economic advantages when compared to current commuter aircraft. This may be achieved by increasing the revenue potential through innovative pricing and scheduling, while drastically reducing operating costs, in particular, energy, maintenance, and labor costs. These ambitious objectives require the infusion of new cutting edge technologies. The use of distributed electric propulsion is investigated to reduce both energy and maintenance expenditures. New avionics systems are considered to enable simplified operations and thus to reduce both labor and training costs. The purpose of this on-going research is to assess the viability of the thin-haul aviation concept by investigating both the operational and economic impact of introducing a fleet of distributed electric propulsion aircraft into the operations of a commuter airline. This paper presents the development of an integrated economics and operations model that incorporates preliminary estimates of a distributed electric propulsion vehicle performance as well as some aspects of typical commuter operator schedules. The model helps compare advanced electric vehicles with more conventional commuters, and therefore enables a preliminary assessment of the expected cost savings.
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Date
2016
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