Multi-Objective Optimization of Bioresorbable Magnesium Alloy Stent by Kriging Surrogate Model

被引:5
|
作者
Wang, Hongjun [1 ]
Jiao, Li [2 ]
Sun, Jie [1 ]
Yan, Pei [2 ]
Wang, Xibin [2 ]
Qiu, Tianyang [2 ]
机构
[1] Beijing Inst Technol, Sch Mech Engn, 5 Zhongguancun South St, Beijing 100081, Peoples R China
[2] Beijing Inst Technol, Key Lab Fundamental Sci Adv Machining, 5 Zhongguancun South St, Beijing 100081, Peoples R China
基金
中国国家自然科学基金;
关键词
Magnesium alloy stents; Stent expansion; Radial recoil and foreshortening ratio; Design optimization; Kriging surrogate model; CORONARY-ARTERIES; DESIGN; PERFORMANCE; MULTICENTER; FABRICATION; RESTENOSIS; SIMULATION; IMPACT;
D O I
10.1007/s13239-022-00619-1
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Purpose-The study proposed a multi-objective optimization method based on Kriging surrogate model and finite element analysis to mitigate the redial recoil and foreshortening ratio of bioresorbable magnesium alloy stent, and investigate the impact of strut thickness on stent expansion behavior. Methods-Finite element analysis have been carried out to compare the expansion behavior of stents with various strut thickness. Latin hypercube sampling (LHS) was adopted to generate train sample points in the design space, and the Kriging surrogate model was constructed between strut parameters and stent behavior. The genetic algorithm (GA) was employed to find the optimal solution in the global design space. Results-Stents with thinner struts experience lower stress but suffer from severe radial recoil and foreshortening effects. The radial recoil is decreased by 66%, and foreshortening ratio is reduced by 60% for the optimized stent with U-bend width 90.7 mu m and link width 77.9 mu m. The errors between Kriging surrogate model and finite element simulation are 6% and 9% for the radial recoil and foreshortening ratio. Conclusion-Stent expansion behavior are highly dependent on design parameters, i.e. thickness, U-bend and link strut width. The purposed Multi-objective optimization approach based on Kriging surrogate model and finite element analysis is efficient in stent design optimization problem.
引用
收藏
页码:829 / 839
页数:11
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