Internal combustion (IC) engines that consume hydrocarbon fuels have dominated the propulsion systems of air-vehicles for the first century of aviation. In recent years, however, growing concern over rapid climate changes and national energy security has galvanized the aerospace community into delving into new alternatives that could challenge the dominance of the IC engine. Nevertheless, traditional aircraft sizing methods have significant shortcomings for the design of such unconventionally powered aircraft. First, the methods are specialized for aircraft powered by IC engines, and thus are not flexible enough to assess revolutionary propulsion concepts that produce propulsive thrust through a completely different energy conversion process. Another deficiency associated with the traditional methods is that a user of these methods must rely heavily on experts experience and advice for determining appropriate design margins. However, the introduction of revolutionary propulsion systems and energy sources is very likely to entail an unconventional aircraft configuration, which inexorably disqualifies the conjecture of such connoisseurs as a means of risk management.
Motivated by such deficiencies, this dissertation aims at advancing two aspects of aircraft sizing: 1) to develop a generalized aircraft sizing formulation applicable to a wide range of unconventionally powered aircraft concepts and 2) to formulate a probabilistic optimization technique that is able to quantify appropriate design margins that are tailored towards the level of risk deemed acceptable to a decision maker.
A more generalized aircraft sizing formulation, named the Architecture Independent Aircraft Sizing Method (AIASM), was developed for sizing revolutionary aircraft powered by alternative energy sources by modifying several assumptions of the traditional aircraft sizing method. Along with advances in deterministic aircraft sizing, a non-deterministic sizing technique, named the Probabilistic Aircraft Sizing Method (PASM), was developed. The method allows one to quantify adequate design margins to account for the various sources of uncertainty via the application of the chance-constrained programming (CCP) strategy to AIASM. In this way, PASM can also provide insights into a good compromise between cost and safety.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/14575 |
| Date | 09 April 2007 |
| Creators | Nam, Taewoo |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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