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基于一种新的性能预测算法的涡轮分子泵结构优化与流场分析

Structural optimization and flow field analysis of turbomolecular pump based on a new performance prediction algorithm.

作者信息

Sun Kun, Deng Haishun, Wang Cheng, Zhang Shiwei

机构信息

School of Mechatronics Engineering, Anhui University of Science and Technology, Huainan, 232001, Anhui, China.

Anhui Intelligent Mine Technology and Equipment Engineering Research Center, Anhui University of Science and Technology, Huainan, 232001, Anhui, China.

出版信息

Sci Rep. 2024 Jun 3;14(1):12735. doi: 10.1038/s41598-024-63690-9.

Abstract

In the present study, a new turbomolecular pump (TMP) performance prediction algorithm is proposed according to the variable surface combined blade row (VSCBR) geometric model. The simulation calculation program is designed to perform structural optimization and flow field analysis. Research on the pumping performance of the traditional straight blade row (TSBR) indicates that when the blade velocity ratio is greater than 1, the increase in the pumping speed and compression ratio of the TMP gradually tends to stabilize. Response surface methodology is used to optimize the structural parameters of the first four stages of the combined blade row. The optimized VSCBR increases the pumping speed by 18.2% compared to that of the TSBR. The flow field analysis based on the optimized VSCBR shows that gas molecules reaching the rear blades are likely to approach the outlet, and the proportion of gas molecules in this region exceeds 50%. Therefore, the blades we designed should be conducive to additional gas molecules reaching the outlet.

摘要

在本研究中,根据可变表面组合叶片排(VSCBR)几何模型提出了一种新的涡轮分子泵(TMP)性能预测算法。设计了模拟计算程序以进行结构优化和流场分析。对传统直叶片排(TSBR)的抽气性能研究表明,当叶片速度比大于1时,TMP的抽气速度和压缩比的增加逐渐趋于稳定。采用响应面方法对组合叶片排前四级的结构参数进行优化。优化后的VSCBR与TSBR相比,抽气速度提高了18.2%。基于优化后的VSCBR的流场分析表明,到达后叶片的气体分子很可能接近出口,该区域的气体分子比例超过50%。因此,我们设计的叶片应有利于更多气体分子到达出口。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e86/11637116/04b0987048dc/41598_2024_63690_Fig1_HTML.jpg

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