EURODYMAT 2006 - 8th International Conference on Mehanical and Physical Behaviour of Materials under Dynamic Loading
J. Cirne, R. Dormeval, et al.
J. Phys. IV France 134 (2006) 417-422
DOI: 10.1051/jp4:2006134064

Numerical modelling of orthogonal cutting: Influence of cutting conditions and separation criterion

H. Miguélez¹, R. Zaera², A. Rusinek³, A. Moufki³ and A. Molinari<sup>3

1</sup>  Department of Mechanical Engineering, University Carlos III of Madrid, Avda. de la Universidad 30, 28911 Leganés, Madrid, Spain
²  Department of Continuum Mechanics and Structural Analysis, University Carlos III of Madrid, Avda. de la Universidad 30, 28911 Leganés, Madrid, Spain
³  Laboratory of Physics and Mechanics of Materials, UMR CNRS 75-54, University of Metz, Ile du Saulcy, 57045 Metz Cedex, France

Published online: 26 July 2006

Abstract
Chip formation is a high strain rate process studied with analytical and numerical models. Analytical models have the advantage of a small calculation time, however, they are often based on some assumptions which are difficult to verify. Finite element modelling (FEM) of chip formation process provides more details on the chip process formation, such as plastic strain, strain rate or stress fields. FEM can be used to improve the analytical models' assumptions. There is still a wide dispersion of formulations and numerical parameters adopted in order to obtain accurate results in numerical models. In the Lagrangian approach, it is of crucial importance to establish realistic criteria for element deletion, allowing chip separation from original workpiece. In the arbitrary Lagrangian Eulerian (ALE) formulation no element deletion is needed. This work is focused in modelization of orthogonal cutting. A comparison between both numerical approaches, Lagrangian and ALE is shown. The effects of geometrical parameters, erosion criterion and cutting speed are evaluated. Comparisons between numerical and theoretical results are performed, and the results obtained from the numerical approach are used as an input of analytical model, improving its accuracy.

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