期刊
MATERIALS & DESIGN
卷 196, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.matdes.2020.109185
关键词
Additive manufacturing; Finite element; Quiet element method; Mapping; Thermal stress; Molten pool; Thermal-fluid flow
资金
- National Natural Science Foundation of China [51975393]
The prediction of thermal stress and distortion is a prerequisite for high-quality additive manufacturing (AM). The widely applied thermo-mechanical model using the finite element method (FEM) leaves much to be improved due to their oversimplifications on material deposition, molten pool flow, etc. In this study, a highfidelity modelling approach by linking the thermal-fluid (computational fluid dynamics, CFD) and mechanical models (named as CFD-FEMmodel) is developed to predict the thermal stress for AM taking into account the influences of thermal-fluid flow. Profiting from the precise temperature profiles and melt track geometry extracted from the thermal-fluid model as well as the remarkable flexibility of the quiet element method of FEM, this work aims at simulating the thermal stress distribution by involving physical changes in the AM process, e.g., melting and solidification of powder particles, molten pool evolution and inter-track inter-layer re-melting. Unlike the conventional thermo-mechanical analysis, in this approach, thermal stress calculation is purely based on a mechanical model where the thermal loads are applied by using a linear interpolation function to spatially and temporally map the temperature values from the thermal-fluid model's cell centres into the FEM element nodes. With the proposed approach, the thermal stress evolution in the AM process of single track, multiple tracks and multiple layers are simulated, where the rough surfaces and internal voids can be well incorporated. Moreover, a conventional thermo-mechanical simulation of two tracks with predefined track geometry is conducted for cross comparison. Finally, the simulated thermal stress distribution can rationally explain the crack distribution observed in the experiments. (C) 2020 The Author(s). Published by Elsevier Ltd.
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