Robust topology optimization of biodegradable composite structures under uncertain degradation rates

被引:4
作者
Zhang, Heng [1 ,2 ]
Takezawa, Akihiro [2 ]
Ding, Xiaohong [1 ]
Zhang, Xiaopeng [3 ]
Xu, Shipeng [1 ]
Li, Hao [4 ]
Nozawa, Shuya [2 ]
Nishiwaki, Shinji [4 ]
机构
[1] Univ Shanghai Sci & Technol, Sch Mech Engn, 516 Jungong Rd, Shanghai 200093, Peoples R China
[2] Waseda Univ, Sch Fundamental Sci & Engn, Dept Appl Mech & Aerosp Engn, Shinjuku Ku, 59-311,3-4-1 Okubo, Tokyo 1698555, Japan
[3] Dalian Univ Technol, State Key Lab Struct Anal Ind Equipment, Dalian 116024, Peoples R China
[4] Kyoto Univ, Dept Mech Engn & Sci, Nishikyo Ku, Kyotodaigaku Katsura C3, Kyoto 6158540, Japan
基金
上海市自然科学基金; 中国国家自然科学基金; 中国博士后科学基金;
关键词
Robust design; Topology optimization; Composite structures; Biodegradable materials; Random degradation rates; POLYNOMIAL CHAOS; CORROSION MODEL; DESIGN; BEHAVIOR; SYSTEMS; ALLOYS; PLATE;
D O I
10.1016/j.compstruct.2022.115593
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
Biodegradable implants have the potential to serve as next-generation temporary medical devices as they can safely dissolve in the human body upon bone regeneration. Degradation uncertainty of the biodegradable material can remarkably affect the mechanical performance of biodegradable composite implant structures. It is necessary to consider this issue when designing resorbable metallic composite structures. To this end, this study introduces a novel robust topology optimization approach for designing biodegradable composite structures considering the degradation rate uncertainty of the biomaterial. The density-based topology optimization method is used to track the evolving of biomaterial layout during the optimization process, the Expansion Optimal Linear Estimation (EOLE) method is used to model the degradation uncertainties, and the Polynomial Chaos Expansion (PCE) based uncertain propagation analysis is implemented to predict the stochastic response. Then the robust topology optimization problem is formulated, in which a weighted function that achieves a trade-off between the expected mean and standard deviation of the performance function of interest was used as the objective function. The sensitivities of the design variables were deduced by considering the material degradation over time. Several numerical examples were presented to demonstrate that the proposed method could generate meaningful optimal topologies with the desired mechanical performance.
引用
收藏
页数:22
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