Parameter Identification of a Friction Model in Metal Cutting Simulations with GPU-Accelerated Meshfree Methods

A modular computational framework is presented for the identification of friction parameters in metal machining applications. Numerical simulation of such processes using mesh-based techniques (usually) necessitates the cumbersome re-meshing procedures and is hard to parallelize. Therefore, the present framework synthesizes the advantages of mesh-free methods with GPU parallel computing, offering an efficient tool for the optimization procedures in thermo-mechanical modeling of cutting problems. The proposed approach employs an inverse method to determine the unknown coefficients of a temperature-dependent friction model in high-speed metal cutting. Good agreement between our numerical results and experimental data is found, providing both quantitative and qualitative assessments.

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