Enhanced springback prediction for bending of high-strength spring steel using material data from an inverse modelling approach

被引:7
|
作者
Mertin, Chris [1 ]
Stellmacher, Thomas [1 ]
Schmitz, Roman [1 ]
Hirt, Gerhard [1 ]
机构
[1] Rhein Westfal TH Aachen, Inst Met Forming, Intzestr 10, D-52072 Aachen, Germany
关键词
Inverse modelling; Parameter identification; Finite Element Method; Bending; Spring steel; IDENTIFICATION; PARAMETERS;
D O I
10.1016/j.promfg.2019.02.120
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Springs for electrical components made from strip materials and flat wires are produced using stamping and forming technologies. The process design of multi-stage stamping and bending processes is still based on expert knowledge and experimental tests. The complexity of the forming processes and the high-strength materials used for springs make the FE simulation of those processes a challenging task. For the springback prediction in FEM, however, an accurate description of the elasto-plastic material behaviour is mandatory. Under process conditions such as bending of spring steel, the locally occurring strains are many times higher than the ultimate elongation of approx. 2 % that can be determined in tensile test. For those materials, standard tests fail to receive enhanced material data such as the influence of plastic deformation on the Young's modulus. The goal of this work is to determine the elasto-plastic material parameters of high-strength spring steel (X10CrNi18-8) using an inverse modelling approach by means of a 3-point bending test. The inverse approach is used for determining the Young's modulus and hardening parameters of Ludwik-Hollomon's law for bending of high-strength spring steel. Furthermore, this work focuses on the unloading at the end of the bending experiment and its effect on the elastic material parameters. The results demonstrate that the inversely determined material data show lower scattering compared to material data from tensile test. Furthermore, material data of high-strength spring steel from the inverse modelling approach significantly enhances the springback prediction under bending conditions compared to FE simulations using material data from tensile test. (C) 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the organizing committee of SHEMET 2019.
引用
收藏
页码:153 / 160
页数:8
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