Optimization and Validation of a Micro-Centrifugal Pump Based on a CFD Simulation and Optimization Platform

Computational fluid dynamics (CFD) plays a crucial role in optimizing micro-centrifugal pump geometries; however, conventional workflows often suffer from fragmentation, manual intervention, and poor interoperability among software tools. In this study, an integrated CFD-based simulation–optimization platform was developed to establish a closed-loop workflow covering parametric modeling, automated meshing, steady CFD analysis, and multi-objective optimization. Using a micro-centrifugal pump as a case study, optimal Latin hypercube sampling, a Kriging surrogate model, and a multi-objective genetic algorithm were combined to quantify the relationships between key structural parameters and hydraulic performance and to identify Pareto-optimal designs. Sensitivity analysis showed that blade count and volute throat height were the dominant factors affecting pump head and efficiency. Compared with the baseline design, the optimized schemes achieved average improvements of 40.36% in head and 22.89% in hydraulic efficiency, with Scheme 1 showing the best overall balance. Experimental validation using hydraulic performance testing and particle image velocimetry showed that the deviation between predicted and measured heads was within 10%, and the measured flow-field trends agreed well with the CFD results. The proposed framework provides a reproducible method for the design optimization of micro-centrifugal pumps and other small-scale turbomachinery.