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基于聚合物加工显式有限元法,利用真实应力-应变关系预测切削力与切屑形成

Prediction of Cutting Force and Chip Formation from the True Stress-Strain Relation Using an Explicit FEM for Polymer Machining.

作者信息

Yang Bin, Wang Hongjian, Fu Kunkun, Wang Chonglei

机构信息

School of Aerospace Engineering and Applied Mechanics, Tongji University, Shanghai 200092, China.

School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, Sydney 2006, Australia.

出版信息

Polymers (Basel). 2022 Jan 4;14(1):189. doi: 10.3390/polym14010189.

Abstract

In the present work, an explicit finite element (FE) model was developed for predicting cutting forces and chip morphologies of polymers from the true stress-strain curve. A dual fracture process was used to simulate the cutting chip formation, incorporating both the shear damage failure criterion and the yield failure criterion, and considering the strain rate effect based on the Johnson-Cook formulation. The frictional behaviour between the cutting tool and specimen was defined by Coulomb's law. Further, the estimated cutting forces and chip thicknesses at different nominal cutting depths were utilized to determine the fracture toughness of the polymer, using an existing mechanics method. It was found that the fracture toughness, cutting forces, and chip morphologies predicted by the FE model were consistent with the experimental results, which proved that the present FE model could effectively reflect the cutting process. In addition, a parametrical analysis was performed to investigate the effects of cutting depth, rake angle, and friction coefficient on the cutting force and chip formation, which found that, among these parameters, the friction coefficient had the greatest effect on cutting force.

摘要

在本研究中,基于真实应力-应变曲线,开发了一种显式有限元(FE)模型,用于预测聚合物的切削力和切屑形态。采用双断裂过程模拟切屑形成,结合剪切损伤失效准则和屈服失效准则,并基于Johnson-Cook公式考虑应变率效应。切削刀具与试样之间的摩擦行为由库仑定律定义。此外,利用现有力学方法,通过不同名义切削深度下估计的切削力和切屑厚度来确定聚合物的断裂韧性。结果发现,有限元模型预测的断裂韧性、切削力和切屑形态与实验结果一致,这证明了当前有限元模型能够有效反映切削过程。此外,进行了参数分析,以研究切削深度、前角和摩擦系数对切削力和切屑形成的影响,结果发现,在这些参数中,摩擦系数对切削力的影响最大。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0555/8747417/afbe26e743bb/polymers-14-00189-g001.jpg

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