Research on Structural Optimization of Interventional Microaxial Blood Pump Based on Non-Dominated Sorting Genetic Algorithm-II

This study presents an optimization approach for interventional microaxial blood pump, aimed at addressing the rising burden of cardiovascular diseases and the limited availability of heart transplant donors in China. The methodology integrates design of experiments (DOE), computational fluid dynamics (CFD) analysis, and response surface methodology (RSM), with the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) multi-objective genetic algorithm employed to optimize impeller geometry. The primary objectives were to enhance hydraulic efficiency and improve hemocompatibility. The optimized blood pump model demonstrated notable performance improvements across various flow conditions: at a low flow rate of 1 L/min, the pump head increased by 2.97% and the hemolysis index decreased by 12.04%; at the design point, head improved by 5.22% while hemolysis was reduced by 11.71%; under high-flow conditions (4 L/min), head increased by 8.5% and hemolysis decreased by 12.57%. These enhancements contribute to higher energy efficiency and lower hemolytic risk, thereby improving the safety and reliability of the device in clinical applications. The findings provide a robust foundation for future advancements in blood pump design and optimization.