多物理
计算模型
过程(计算)
计算机科学
领域(数学)
联轴节(管道)
比例(比率)
机械工程
系统工程
材料科学
有限元法
工程类
人工智能
结构工程
物理
数学
量子力学
操作系统
纯数学
作者
Shashank Sharma,Sameehan S. Joshi,Mangesh V. Pantawane,M. Radhakrishnan,Sangram Mazumder,Narendra B. Dahotre
标识
DOI:10.1080/09506608.2023.2169501
摘要
This review article provides a critical assessment of the progress made in computational modelling of metal-based additive manufacturing (AM) with emphasis on its ability to predict physical phenomena, concepts of microstructural evolution, residual stresses, role of multiple thermal cycles, and formation of multi-dimensional defects along with the achieved degree of experimental validation. The uniqueness of this article stems from the inclusion of comprehensive information on computational progress in the field of fusion-based, sintering-based, and mechanical deformation-based AM. A computational model's role in determining the process framework for the desired outcome of the set properties of the AM components is recognised while presenting the process-microstructure maps, thereby appraising computational ability towards the qualification of products. The inclusion of a detailed discussion on the bi-directional coupling of machine learning and physics-based computational models provides a futuristic roadmap for the digital twin of metal-based AM.
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