Multi-condition design optimization of groove flow control technique in an axial-flow pump

To address the limitations of conventional groove designs in groove flow control technique, this paper optimizes the groove flow control technique for an axial-flow pump combining the design of experiment (DOE), response surface methodology (RSM), and particle swarm optimization (PSO). The sample space is designed using a combination method (OD-LHS) of orthogonal design (OD) and Latin hypercube sampling (LHS). Performance prediction models for the axial-flow pump are established using RSM. Taking the multi-condition comprehensive evaluation function as the final optimization objective, PSO is used to find the optimum groove parameters. The results show that the proposed method is effective in solving multi-condition optimization problems for grooves in axial-flow pumps. The optimal groove length, depth, and distance from the center of the impeller are 0.8, 0.05, and 0.2 times the impeller diameter, respectively, and the number is three times the number of blades. In addition, the optimal grooves effectively improve the hydraulic performance of the axial-flow pump under stall conditions. This study sheds light on the design optimization of the groove flow control technique for axial-flow pumps and other types of hydraulic machinery.