4.6 Article

Selection of the numerical formulation for modeling the effect of tool cutting edge microgeometries in machining of Ti6Al4V titanium alloy

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DOI: 10.1016/j.simpat.2023.102816

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Metal cutting; Tool cutting edge microgeometry; Modeling; Numerical formulation; Finite element method; Constitutive model

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This study investigates the influence of different tool edge microgeometries on the cutting of Ti6Al4V titanium alloy using the LAG and CEL approaches. The LAG-nSL model gives the best predictions of chip morphology, cutting force, and thrust force, while the LAG-SL model offers good predictions of the maximum compressive residual stress.
The Finite-element method (FEM) is often used to simulate the metal machining process. Currently, several formulations are used in metal cutting simulation, such as Lagrangian (LAG), Eulerian (EUL), Arbitrary Lagrangian-Eulerian (ALE), and Coupled Eulerian-Lagrangian (CEL). The selection of the numerical formulation that better reproduces the material separation in machining to form the chip is a critical issue. This is quite important when the ratio between the uncut chip thickness and the cutting edge microgeometry, often represented by a cutting edge radius, is very low. In this study, orthogonal cutting of Ti6Al4V titanium alloy using different tool edge microgeometries is investigated using LAG and CEL approaches. In the case of LAG approach, two types of cutting models were develop: one using a sacrificial layer (hereby called LAG-SL), and another without sacrificial layer (hereby called LAG-nSL). The cutting models have included a constitutive model (both plasticity and damage) considering the effects of strain, strain rate, temperature, and state of stress, which have proved to be accurate enough to represent the mechanical behavior of the Ti6Al4V alloy in machining. Comprehensive comparisons between CEL and LAG-based cutting models and experimental results are carried out in terms of chip morphology, forces, and residual stresses. When compared to the experimental results, LAG-nSL model gives the best predictions of the maximum chip compression ratio (CCRm) with an error of 9.5%, cutting force (12.8%) and thrust force (9.3%) than the other two models. In the case of the of residual stress profiles, LAG-SL offers good predictions of the maximum compressive residual stress by a preference ratio of 75%. Although CEL yields the worst predictions of chip morphology and forces, it is preferred from the perspective of the thickness of the layer affected by residual stress.

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