Multiscale topology optimization of biodegradable metal matrix composite structures for additive manufacturing

Heng Zhang, Xiaohong Ding*, Honghu Guo, Shipeng Xu, Hao Li, Shinji Nishiwaki, Yanyu Chen, Akihiro Takezawa


研究成果: Article査読

5 被引用数 (Scopus)


Recent advances in biomedical engineering have promoted the development of innovative metal implants that have integrated mechanical and biodegradable properties. Most of the existing implant designs were created by using a trial-and-error approach, which depends on the designer's experience. Alternatively, inverse design approaches, such as topology optimization, have evolved into an efficient design solution to optimize the structural and material layout within a given design domain. Here we introduce a novel topology optimization scheme to support the microstructural design of biodegradable metal matrix composite structures (BM−MCS). The effect of material degradation on the mechanical performance of the structure is considered by integrating a degradation simulation algorithm into the structural finite element (FE) analysis. The objective function is to minimize the structural compliance at macroscale in a certain number of time steps to realize sufficient structural integrity in the initial bone healing stage, and the different stiffness reduction properties can be adjusted by changing the volume ratio of the two base constitutive biodegradable materials. The sensitivity of the above objective function concerning design variables was derived with considering the time-dependent degradation of the biodegradable material. Several numerical design examples were presented and benchmarked with classical designs. Finally, several prototypes were fabricated by integrating additive manufacturing with casting technology. Collectively, this demonstrates the feasibility and effectiveness of the proposed inverse design method for additive manufacturing.

ジャーナルApplied Mathematical Modelling
出版ステータスPublished - 2023 2月

ASJC Scopus subject areas

  • モデリングとシミュレーション
  • 応用数学


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