CLC number: TG5
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2009-03-04
Cited: 13
Clicked: 6212
Yun-bo BI, Qun-lin CHENG, Hui-yue DONG, Ying-lin KE. Machining distortion prediction of aerospace monolithic components[J]. Journal of Zhejiang University Science A, 2009, 10(5): 661-668.
@article{title="Machining distortion prediction of aerospace monolithic components",
author="Yun-bo BI, Qun-lin CHENG, Hui-yue DONG, Ying-lin KE",
journal="Journal of Zhejiang University Science A",
volume="10",
number="5",
pages="661-668",
year="2009",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A0820392"
}
%0 Journal Article
%T Machining distortion prediction of aerospace monolithic components
%A Yun-bo BI
%A Qun-lin CHENG
%A Hui-yue DONG
%A Ying-lin KE
%J Journal of Zhejiang University SCIENCE A
%V 10
%N 5
%P 661-668
%@ 1673-565X
%D 2009
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A0820392
TY - JOUR
T1 - Machining distortion prediction of aerospace monolithic components
A1 - Yun-bo BI
A1 - Qun-lin CHENG
A1 - Hui-yue DONG
A1 - Ying-lin KE
J0 - Journal of Zhejiang University Science A
VL - 10
IS - 5
SP - 661
EP - 668
%@ 1673-565X
Y1 - 2009
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A0820392
Abstract: To predict the distortion of aerospace monolithic components, a model is established to simulate the numerical control (NC) milling process using 3D finite element method (FEM). In this model, the cutting layer is simplified firstly. Then, the models of cutting force and cutting temperature are established to gain the cutting loads, which are applied to the mesh model of the part. Finally, a prototype of machining simulation environment is developed to simulate the milling process of a spar. Key factors influencing the distortion, such as initial residual stress, cutting loads, fixture layout, cutting sequence, and tool path are considered all together. The total distortion of the spar is predicted and an experiment is conducted to validate the numerical results. It is found that the maximum discrepancy between the simulation results and experiment values is 19.0%.
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