Lifting surface optimization of wake-adapted propeller by surrogate model - Xue, Ying; Yang, Chen-Jun; Dong, Xiao-Qian (Journal of ocean engineering and science, 2024)
•A lifting surface method is presented for optimizing wake-adapted propellers.•A surrogate model based on neural network is developed for the optimization.•The particle swarm algorithm is employed to optimize the circulation distribution.•Numerical validation results indicate the present method is reasonably accurate. A method is presented for optimizing the radial circulation distribution of the marine propeller operating in a radially non-uniform inflow. The optimum circulation distribution is obtained by searching a BPNN surrogate model with the PSO algorithm. The BPNN model establishes the nonlinear relationship between the radial circulation distribution and the thrust loading coefficient as well as the hydrodynamic efficiency. An in-house lifting-surface VLM code is employed to generate the performance data of sample propellers for the purpose of training, validating, and testing the surrogate model. The camber surface geometry and pitch distribution corresponding to the optimum circulation distribution are designed by the VLM-based method developed by the authors previously. Numerical examples are presented for a five-bladed propeller subject to a radially non-uniform inflow and a seven-bladed propeller in open water to assess the performance of the present design method, and the numerical validation results yielded from an in-house surface panel code indicate that the design requirements are fulfilled with reasonable accuracy. In addition, the effect of the hub on the optimum circulation distribution is investigated.