Topologically assisted optimization for rotor design

Wang, Tianyu1; Yang, Yannian2; Chen, Xuanwu3; Li, Pengyu4; Iollo, Angelo5,6; Maceda, Guy Cornejo Y.1; Noack, Bernd R.1

2023-05-01

10.1063/5.0145941

PHYSICS OF FLUIDS   影响因子和分区

1070-6631

1089-7666

We develop and apply a novel shape optimization exemplified for a two-blade rotor with respect to the figure of merit. This topologically assisted optimization contains two steps. First, a global evolutionary optimization is performed for the shape parameters, and then a topological analysis reveals the local and global extrema of the objective function directly from the data. This non-dimensional objective function compares the achieved thrust with the required torque. Rotor blades have a decisive contribution to the performance of quadcopters. A two-blade rotor with pre-defined chord length distribution is chosen as the baseline model. The simulation is performed in a moving reference frame with a k - ? turbulence model for the hovering condition. The rotor shape is parameterized by the twist angle distribution. The optimization of this distribution employs a genetic algorithm. The local maxima are distilled from the data using a novel topological analysis inspired by discrete scalar-field topology. We identify one global maximum to be located in the interior of the data and five further local maxima related to errors from non-converged simulations. The interior location of the global optimum suggests that small improvements can be gained from further optimization. The local maxima have a small persistence, i.e., disappear under a small e perturbation of the figure of merit values. In other words, the data may be approximated by a smooth mono-modal surrogate model. Thus, the topological data analysis provides valuable insight for optimization and surrogate modeling.

SCI ; EI

英语

其他

National Science Foundation of China (NSFC)["12172109","12172111"] ; Guangdong province, China, via the Natural Science and Engineering[2022A1515011492] ; Shenzhen Research Foundation for Basic Research, China[JCYJ20220531095605012] ; AVIC General Aircraft Research Institute[AG-EX_HT_024] ; European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant[872442]

Mechanics ; Physics

Mechanics ; Physics, Fluids & Plasmas

WOS:000981230800011

AIP Publishing

20232014082473

Genetic algorithms ; Global optimization ; Shape optimization ; Topology

Combinatorial Mathematics, Includes Graph Theory, Set Theory:921.4 ; Optimization Techniques:921.5

PHYSICS

Web of Science

1.Harbin Inst Technol, Sch Mech Engn & Automat, Shenzhen 518055, Peoples R China
2.South China Univ Technol, Unmanned Aerial Vehicle Syst Engn Technol Res Ctr, Sch Automat Sci & Engn, Minst Educ,Key Lab Autonomous Syst & Networked Con, Guangzhou 510640, Peoples R China
3.Tsinghua Univ, Inst Aero Engine, 10084, Beijing, Peoples R China
4.Southern Univ Sci & Technol, Dept Mech & Aerosp Engn, Shenzhen 518055, Peoples R China
5.Univ Bordeaux, Inst Math Bordeaux, F-33400 Talence, France
6.Univ Bordeaux, Memphis Team, Ctr Inria, F-33400 Talence, France

Wang, Tianyu,Yang, Yannian,Chen, Xuanwu,et al. Topologically assisted optimization for rotor design[J]. PHYSICS OF FLUIDS,2023,35(5).

Wang, Tianyu.,Yang, Yannian.,Chen, Xuanwu.,Li, Pengyu.,Iollo, Angelo.,...&Noack, Bernd R..(2023).Topologically assisted optimization for rotor design.PHYSICS OF FLUIDS,35(5).

Wang, Tianyu,et al."Topologically assisted optimization for rotor design".PHYSICS OF FLUIDS 35.5(2023).