Turbofan engine sizing and tradeoff analysis via signomial programming/

Abstract

This thesis presents a full 1D core+fan flowpath turbofan optimization model, based on first principles, and meant to be used during aircraft conceptual design optimization. The model is formulated as a signomial program, which is a type of optimization problem that can be solved locally using sequential convex optimization. Signomial programs can be solved reliably and eciently, and are straightforward to integrate with other optimization models in an all-at-once manner. To demonstrate this, the turbofan model is integrated with a simple commercial aircraft sizing model. The turbofan model is validated against the Transport Aircraft System OPTimization turbofan model as well as two Georgia Tech Numerical Propulsion System Simulation turbofan models. Four integrated engine/aircraft parametric studies are performed, including a 2,460 variable multi-mission optimization that solves in 28 seconds.