Design of High Altitude Propeller Using Multilevel Optimization

Author:

Liu Xinqiang1,He Weiliang1,Wei Fengmei2

Affiliation:

1. School of Astronautics, Beihang University, Beijing 100191, P. R. China

2. Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, P. R. China

Abstract

An improved D’Angelo optimization framework based on the surrogate model and optimization algorithm is proposed to design and optimize a new high altitude propeller which is applied to the propulsion system of the stratospheric aircraft. The framework adopts a multilevel optimization strategy to determine a high efficiency and light weight propeller. The aerodynamic characteristics of S1223 airfoil are calculated by Computational Fluid Dynamics (CFD) method. The aerodynamic performance of the D’Angelo propeller which is obtained by the first-level optimization is predicted by Blade element momentum (BEM) theory. Then the D’Angelo propeller chord and twist angle, which are regarded as the initial conditions of the second-level optimization, are optimized to achieve the maximum efficiency by Multi-island genetic algorithm (MIGA). In addition, the non-dominated sorting genetic algorithm II (NSGA-II) is applied to maximize the propeller efficiency and minimize the propeller weight. And the Pareto frontier solutions about the efficiency and the blade area are obtained by NSGA-II. What is more, the aerodynamic characteristics of the D’Angelo propeller, the optimization propeller by MIGA, and the optimization propeller by NSGA-II are calculated by CFD simulation and compared with BEM results. It is shown that the CFD results are in fair agreement with BEM results and the aerodynamic performance of the NSGA-II propeller is prior to the MIGA propeller and is close to the D’Angelo propeller. Besides, the NSGA-II propeller is the lightest among them and can satisfy the cruise requirements of the high altitude propeller.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computational Mathematics,Computer Science (miscellaneous)

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