Multi-objective Optimisation of Low Pressure Compression System

Adaptive Range Multi-Objective Genetic Algorithm (ARMOGA) has been developed to obtain trade-offs more efficiently than conventional Multi-Objective Evolutionary Algorithms. In this paper, the performance of ARMOGA is demonstrated through a multiobjective design optimisation of Bypass Fan Outlet Guide Vanes as part of the Low Pressure Compression (LPC) system. In the present optimisation, the objectives of the LPC system are to reduce the circumferential pressure variation at the inlet boundary and mixed-out total pressure loss at selected radial height. These objective functions are evaluated by an in-house, parallel, high-fidelity CFD solver. Throughout the optimisation, ARMOGA has shown reasonable performance for obtaining trade-offs even with a small number of evaluations.