Abstract：
The centrifugal blood pump is a commonly used ventricular assist device. It can replace part of the heart function, pumping blood throughout the body in order to maintain normal function. However, the high shear stress caused by the impeller rotating at high speeds can lead to hemolysis and, as a consequence, to stroke and other syndromes. Therefore, reducing the hemolysis level while ensuring adequate pressure generation is key to the optimization of centrifugal blood pumps. In this study, a screw centrifugal blood pump was used as the research object. In addition, pressure generation and the hemolysis level were optimized simultaneously using a coupled algorithm composed of random forest (RF) and multi-objective gray wolf optimization (MOGWO). After verifying the prediction accuracy of the algorithm, three optimized models were selected and compared with the baseline model in terms of pressure cloud, 2D streamline, SSS distribution, HI distribution, and vortex distribution. Finally, via a comprehensive evaluation, the optimized model was selected as the final optimization design, in which the pressure generation increased by 24% and the hemolysis value decreased by 48%.
摘要：
离心血泵是一种常用的心室辅助装置。它可以替代部分心脏功能，将血液泵入全身以维持正常功能。然而,叶轮高速旋转引起的高剪切应力会导致溶血，因此，中风和其他综合症。因此,降低溶血水平，同时确保产生足够的压力是优化离心血泵的关键。在这项研究中,以螺旋离心血泵为研究对象。此外,使用由随机森林（RF）和多目标灰狼优化（MOGWO）组成的耦合算法同时优化压力生成和溶血水平。在验证了算法的预测准确性后,选择了三个优化模型，并在压力云方面与基线模型进行了比较，2D、流线SSS分布,HI分布,和涡流分布。最后,通过全面评估，选择优化后的模型作为最终的优化设计，其中压力产生增加了24%，溶血值降低了48%。
