GPU-accelerated meshfree simulations for parameter identification of a friction model in metal machining. (15th June 2020)

• Record Type: Journal Article
• Authors: Afrasiabi, M.; Meier, L.; Röthlin, M.; Klippel, H.; Wegener, K.
• Is Part Of: International journal of mechanical sciences. Volume 176(2020)
• Publication Date: 2020-06-15
• Subjects: Friction -- Temperature -- Tribometer -- Orthogonal cutting -- Meshfree simulation -- GPU computing; Mechanical engineering -- Periodicals; Génie mécanique -- Périodiques; Mechanical engineering; Maschinenbau; Mechanik; Zeitschrift; Periodicals; 621.05
• DOI: 10.1016/j.ijmecsci.2020.105571
• Languages: English
• ISSNs: 0020-7403

Abstract

Highlights: Coefficient of friction in machining is generally a decreasing function of temperature. Available meshfree cutting solvers do not include temperature-dependent friction models. An enhanced Coulomb law with a temperature-dependent coefficient is taken into account. Hundreds of cutting simulations are carried out to determine the unknown friction parameters using an inverse method. Meshfree methods are employed for spatial discretizations and our code is run entirely on the GPU. Forces are predicted with a significantly lower error in enhanced cutting models. Graphical abstract: Abstract: In the analysis of metal machining processes using meshless methods, friction is usually modeled (if at all) by Coulomb's law with a prescribed constant coefficient. Experimental observations, however, show that the coefficient μ of friction in such processes is not constant but generally a decreasing function of temperature. In this study, an in-process tribometer experiment is initially conducted on a Ti6Al4V workpiece to acknowledge that μ is in fact temperature-dependent. Subsequently, an enhanced Coulomb law is proposed whose coefficient μ ( T ) is a decreasing function of temperature. The unknown parameters of μ ( T ) are determined by a force optimization of iterative simulations carried out on several configurations. To this end, the present article takes 5 different cutting geometries from the literature considering 3 alternative sets of Johnson-Cook parameters for the Ti6Al4V constitutive model. This combination leads to 15 case studies in total. To tackle the very expensive cost of computation associated with this massive load of simulations, a GPU-accelerated meshless implementation is employed. Results of the present investigation demonstrate that: (1) friction modeling at the tool-chip interface has a remarkable influence on the numerical simulations of machining; (2) reliability of the friction parameters is substantially interrelated with the choice and reliability of the constitutive model parameters. As a result of this work, the error of force prediction in meshfree cutting simulations can be significantly reduced by adopting an enhanced friction model.