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A series of prediction algorithms suitable for the pre-design stage of industrial conceptual transport aircraft design are derived in this treatise. The methods have been devised by hybridizing statistical correlation of design variables, synthetic functions and macro-objective functions with fractional change analytical constructs. Applicability of these prediction algorithms encompasses personal/micro turbofans, business aircraft from very light to ultra-long range categories to commercial aircraft from commuters to narrow-body transports of around 100 PAX. It is highlighted that the methods have been generated from a dataset of information limited to in-production or formally launched transport aircraft, hence reflects only a contemporary level of technological sophistication.

During this study, the conceptual design of a 19 passenger turbofan transport aimed primarily at the regional/ commuter market was synthesised. Final configuration selection was based on a method conceived by the author which incorporates a hybrid of the conventional intuitive conceptual design process with overtones of a non-hierarchic multi-disciplinary optimisation philosophy. To ensure validity of the aforementioned design and optimisation algorithms, the General Aviation Synthesis Program (GASP) software developed by NASA-Ames Research Centre and subsequently refined by Williams- Rolls Inc. was used. In addition, attention was paid during the design sequence to minimise the alterations necessary for variants of the basic design, i.e. future extended range and stretched versions.