Work

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

Year: 2021

Type: conference-paper

Abstract: A modular computational framework for the identification of friction parameters in metal machining applications is presented. Numerical simulation of such processes using mesh-based techniques (usually) necessitates the re-meshing procedure, which is time-consuming and 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 thermomechanical 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. We found good agreement between the numerical results and experimental data through a quantitative-qualitative comparison.

Source: WCCM-ECCOMAS Congress

DOI: 10.23967/wccm-eccomas.2020.273

Authors: M. Afrasiabi, H. Klippel, M. Roethlin, K. Wegener

Institutions: ETH Zurich, Institute of Machine Tools and Manufacturing, Federal Office of Meteorology and Climatology MeteoSwiss

Language: English

Topic: Advanced machining processes and optimization

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Funders: National Science Foundation, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Awards: GPU-Enhanced Metal Cutting Simulation using Advanced Meshfree Methods, G993971353