Inverse Finite Element Modeling of the Barreling Effect on Experimental Stress-Strain Curve for High Temperature Steel Compression Test

Abstract

Thermomechanical properties used in the modeling of steel forming processes that are determined using high temperature cylindrical coupon compression testing are subject to errors due to barreling of the test specimen. Barreling caused by the friction between specimen and platens reduces the accuracy of the mechanical property determination. In this study, Gleeble hot compression testing was conducted to investigate material behavior for a low carbon structural steel over a range of temperatures (from 900 °C to 1200 °C) and strain rates (from 1 s-1 to 30 s-1). An inverse method combined with finite element analysis was developed to correct the experimental stress-strain curves for the observed barreling effect to obtain the actual stress-strain curves for the material. In deformation simulations, the revised stress-strain curves produced barreling shape predictions that agreed well with the barrel shapes observed in experiments. A comprehensive parametric study based on the revised stress-strain curves was performed to study barreling for a range of friction coefficients, temperatures, and strain rates. Results showed that the magnitude of barreling increases with increasing friction coefficient. For a specific friction coefficient, the magnitude of the barreling decreases with increasing temperature and varies non-linearly with strain rate.

Department(s)

Mechanical and Aerospace Engineering

Second Department

Materials Science and Engineering

Research Center/Lab(s)

Intelligent Systems Center

Second Research Center/Lab

Peaslee Steel Manufacturing Research Center

Third Research Center/Lab

Center for High Performance Computing Research

Keywords and Phrases

Barreling effect; Stress-strain curve; Inverse method; Finite element analysis; Hot compression

International Standard Serial Number (ISSN)

0924-0136

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2017 Elsevier

Publication Date

01 May 2017

Link to Full Text

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