In traditional aircraft conceptual design, subsystems are largely accounted for implicitly based on available historical data and trends. Such an approach has limitations when novel subsystem architectures such as More Electric or All Electric aircraft are considered, since historical data regarding such architectures is either limited or non-existent. In such cases, the incorporation of more thorough and explicit consideration of the aircraft subsystems into the conceptual design phase is warranted.
The first objective of this dissertation is to integrate subsystem sizing and analysis methods that are suitable for the early design phases with the traditional aircraft sizing methodology. The goal is to facilitate the assessment subsystem architecture performance with respect to vehicle and mission level metrics. The second objective is to investigate how the performance of different subsystem architectures varies with aircraft size. The third and final objective is to assess the sensitivity of architecture performance to epistemic and technological uncertainty.
These objectives are pursued through the development of an integrated sizing and analysis environment where the subsystems are sized in parallel with the aircraft itself using subsystem models that are computationally inexpensive and do not require detailed aircraft definition. The effects of subsystem mass, secondary power requirements, and drag increments are propagated to the mission performance analysis following which the vehicle and subsystems are re-sized. A number of experiments are performed to first test the capabilities of the developed environment and subsequently assess the performance of numerous subsystem architectures and the sensitivity of select architectures to epistemic and technological uncertainty.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/54427 |
| Date | 07 January 2016 |
| Creators | Chakraborty, Imon |
| Contributors | Mavris, Dimitri N. |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | application/pdf |
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