A Numerical-Experimental Study on Orthogonal Cutting of AISI 1045 Steel and Ti6Al4V Alloy: SPH and FEM Modeling with Newly Identified Friction Coefficients

Numerical simulation of metal cutting with rigorous experimental validation is a profitable approach that facilitates process optimization and better productivity. In this work, we apply the Smoothed Particle Hydrodynamics (SPH) and Finite Element Method (FEM) to simulate the chip formation process...

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Autores principales: Mohamadreza Afrasiabi, Jannis Saelzer, Sebastian Berger, Ivan Iovkov, Hagen Klippel, Matthias Röthlin, Andreas Zabel, Dirk Biermann, Konrad Wegener
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
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FEM
Acceso en línea:https://doaj.org/article/8ce121abca3e4dfea441431e36b56fb3
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Sumario:Numerical simulation of metal cutting with rigorous experimental validation is a profitable approach that facilitates process optimization and better productivity. In this work, we apply the Smoothed Particle Hydrodynamics (SPH) and Finite Element Method (FEM) to simulate the chip formation process within a thermo-mechanically coupled framework. A series of cutting experiments on two widely-used workpiece materials, i.e., AISI 1045 steel and Ti6Al4V titanium alloy, is conducted for validation purposes. Furthermore, we present a novel technique to measure the rake face temperature without manipulating the chip flow within the experimental framework, which offers a new quality of the experimental validation of thermal loads in orthogonal metal cutting. All material parameters and friction coefficients are identified in-situ, proposing new values for temperature-dependent and velocity-dependent friction coefficients of AISI 1045 and Ti6Al4V under the cutting conditions. Simulation results show that the choice of friction coefficient has a higher impact on SPH forces than FEM. Average errors of force prediction for SPH and FEM were in the range of 33% and 23%, respectively. Except for the rake face temperature of Ti6Al4V, both SPH and FEM provide accurate predictions of thermal loads with 5–20% error.