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 efficiently, 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.

Efficient Aircraft Multidisciplinary Design Optimization and Sensitivity Analysis via Signomial Programming

“…The SP model uses the full 1D core fan flow path simulation turbofan engine model developed by York et al [6]. An additional boundary-layer ingestion model used for the SP D8.2 is described in Appendix B.…”

“…SP model results are presented alongside TASOPT results in Tables 2-4. Differences in the SP and TASOPT subsystem models, which manifest as solution differences, are discussed in [5,6] and Appendices A-D. A few of the notable differences include the SP model's optimization of the engine ondesign point versus the predefinition of the on-design point in TASOPT, the SP model's use of a physics-and geometry-based landing gear model versus the fractional weights used in TASOPT, Fig. 4 The signomial equality constraint C D fC L and its approximation.…”

“…BLI engines ingest air with lower average velocity, and in turn lower stagnation pressure, than free stream air. Three constraints from [6] were modified to account for BLI. Engine inlet stagnation pressure was reduced by the factor f BLI P .…”

“…Note that f BLI P represents the average drop in stagnation pressure across the entire inlet. Following [6], Z 0 replaces the non-GP-compatible expression 1 γ − 1∕2M 0 2 in stagnation relations. P t 0 f BLI P P atm Z 0 (B4)…”

“…The utility of this new architecture is demonstrated through the solution of a series of commercial aircraft MDO problems. Prior work has developed physics-based SP-compatible models for aircraft wings, fuselages, horizontal tails, vertical tails, landing gear, and turbofan engines [5,6]. These models, along with a mission profile, have been combined to form a full-system aircraft MDO tool of comparable fidelity to the widely used Transport Aircraft System Optimization (TASOPT) [7].…”