4.7 Article

Controlling local overheating in topology optimization for additive manufacturing

出版社

SPRINGER
DOI: 10.1007/s00158-022-03258-1

关键词

Topology optimization; Additive manufacturing; Design for additive manufacturing; Local overheating; Ovehangs

资金

  1. EU Framework Programme for Research and Innovation-Horizon 2020 [721383]

向作者/读者索取更多资源

A novel constraint based on the physics of Additive Manufacturing (AM) process is proposed to prevent local overheating in topology optimization (TO). By using a computationally inexpensive thermal process model, the proposed constraint can detect areas prone to local overheating and achieve optimized results in a computationally efficient manner.
A novel constraint to prevent local overheating is presented for use in topology optimization (TO). The very basis for the constraint is the Additive Manufacturing (AM) process physics. AM enables fabrication of highly complex topologically optimized designs. However, local overheating is a major concern especially in metal AM processes leading to part failure, poor surface finish, lack of dimensional precision, and inferior mechanical properties. It should therefore be taken into account at the design optimization stage. However, including a detailed process simulation in the optimization would make the optimization intractable. Hence, a computationally inexpensive thermal process model, recently presented in the literature, is used to detect zones prone to local overheating in a given part geometry. The process model is integrated into density-based TO in combination with a robust formulation, and applied in various numerical test examples. It is found that existing AM-oriented TO methods which rely purely on overhang control do not ensure overheating avoidance. Instead, the proposed physics-based constraint is able to suppress geometric features causing local overheating and delivers optimized results in a computationally efficient manner.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据