Multi-Objective Optimization of Jet Pump Based on RBF Neural Network Model

In this study, an annular jet pump optimization method is proposed based on RBF (Radial Basis Function) neural network model and NSGA-II (Non-Dominated Sorting Genetic Algorithm) algorithm to improve the hydraulic performance of applied in submarine trenching dredging. Suction angle, diffusion area ratio flow were selected as design variables. The computational fluid dynamics (CFD) was used for numerical simulation obtain corresponding performance, accurate approximate established. Finally, carry out multi-objective optimal variable combination. results show that determination coefficient R2 two objective functions (jet efficiency head ratio) greater than 0.97. Compared with original model, optimized model’s suction angle increased, decreased. terms increased by 30.46% after pump, slightly. provides a reference improving other pumps.