LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Using FEM simulations of cutting for evaluating the performance of different johnson cook parameter sets acquired with inverse methods

Photo from wikipedia

Abstract Material model parameters are the primary source of error in the finite element analysis (FEM) of cutting processes. Expensive and time consuming material testing is required in order to… Click to show full abstract

Abstract Material model parameters are the primary source of error in the finite element analysis (FEM) of cutting processes. Expensive and time consuming material testing is required in order to describe the material's behavior in high temperature and high strain rate conditions during cutting. An alternative approach has been suggested in research papers; inverse analysis using cutting experiments together with FE analysis or analytical models. The latest approach is to combine an analytical model together with a material model capable of describing flow stress in terms of strain, strain rate and temperature, and using cutting experiments to acquire input parameters for inverse analysis, from which the material model parameters can be solved. In this paper, performance evaluation is done for five different sets of Johnson Cook parameters for AISI 1045, acquired with materials testing, inverse analysis with FEM, and the proposed combined inverse analysis with an analytical model and cutting experiments. The performance is evaluated by running simulations with a wide range of cutting parameters and comparing the simulated results of cutting forces and temperature to known experimental results found in literature. It was found that the proposed inverse method produces better performing model parameters than those found in literature.

Keywords: analysis; inverse analysis; model; performance; johnson cook

Journal Title: Robotics and Computer-integrated Manufacturing
Year Published: 2017

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.