Multi-objective optimization design of a centrifugal pump with vaned diffuser based on improved whale optimization algorithm and back propagation neural network

A novel multi-objective optimization design approach is presented integrating the Improved Whale Optimization Algorithm (IWOA) with Back Propagation Neural Network (BPNN) for the centrifugal pump with vaned diffuser. The primary objectives of this optimization are to enhance pump efficiency and reduce pressure pulsation. Under head constraints, seven critical geometric design variables of the vaned diffuser centrifugal pump were identified as optimization parameters. Sample data were generated using Latin Hypercube Sampling (LHS) to construct a high-accuracy surrogate model, which was subsequently globally optimized using IWOA. The optimization results were validated through numerical simulations, revealing that the optimized model achieves a 1.56% increase in efficiency and a 28.6% reduction in pressure pulsation intensity. These enhancements significantly improve the operational stability and reliability of the pump. Furthermore, the research delves into entropy production analysis and the comparison of unsteady flow characteristics, elucidating the mechanisms behind the reductions in internal energy losses and the improvements in flow field properties resulting from the optimized design. This work provides a novel methodology for designing high-efficiency, low-vibration centrifugal pumps, offering substantial engineering application value and valuable theoretical insights.