期刊
COMPUTERS & STRUCTURES
卷 87, 期 17-18, 页码 1166-1174出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compstruc.2009.04.008
关键词
Friction stir welding; Aluminum alloys; Continuous dynamic recrystallization; Neural networks; FEM
资金
- MIUR (Italian Ministry for University and Scientific Research) funds
In the paper the microstructural phenomena in terms of average grain size occurring in friction stir welding (FSW) processes are focused. A neural network was linked to a finite element model (FEM) of the process to predict the average grain size values. The utilized net was trained starting from experimental data and numerical results of butt joints and then tested on further butt, lap and T-joints. The obtained results show the capability of the Al technique in conjunction with the FE tool to predict the final microstructure in the FSW joints. (C) 2009 Elsevier Ltd. All rights reserved.
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