Experimental and Numerical Thickness Analysis of TRIP Steel under Various Degrees of Deformation in Bulge Test

Abstract

To design a reliable forming process it is necessary to determine the mechanical and formability properties of the processed material, which are used as input parameters for forming simulations. High-strength steel is irreplaceable as a material for producing the deformation zones of current automobiles. This type of steel can be processed by conventional or unconventional forming methods. In the sheet forming process, the material is usually under uniaxial and biaxial stress. The bulge test is utilized for determination of biaxial stress–strain curves, which are often used as input material data for forming simulations. In this work, numerical simulations of bulge tests using TRIP RAK 40/70 steel were performed to study the impact of yield criteria and hardening laws on the accuracy of thickness prediction of the deformed steel sheet. Additionally, the impact of different solvers and integration schemes on the thickness prediction was tested. Furthermore, the impact of various degrees of deformation (various dome heights) on thickness prediction accuracy was evaluated. Numerical results showed a good correlation with experimental data. When the Hill90 yield criterion was used, the software with implicit solver was more accurate in predicting thickness compared to software with explicit integration scheme, in most cases. In addition, the thickness prediction of parts with lower deformation was more accurate compared to parts with greater deformation (higher dome height).

Impact of Blank Holding Force and Friction on Springback and Its Prediction of a Hat-Shaped Part Made of Dual-Phase Steel

“…Different steels, hence, behave differently and have specific properties during plastic deformation because of their microstructure [ 30 , 31 , 32 , 33 ]. It is important to know the properties and characteristics of the material, especially when performing a numerical simulation of forming processes [ 34 , 35 ]. The uniaxial tensile tests on standardized specimens were performed to obtain mechanical and plastic properties for the tested material.…”

“…Kinematic hardening rules describe yield surface translation in stress space; the shape of the yield surface does not change for this type of rule. The last, so-called combined hardening rule uses a combination of isotropic and kinematic hardening to define the behavior of the material under plastic strain [ 34 , 42 ].…”

Current Trends in Metallic Materials for Body Panels and Structural Members Used in the Automotive Industry

“…Transformation-induced plasticity steels are first-generation steels with a fine-grained structure, which are characterised by high strength and high plasticity [91]. TRIP steels are defined as steels with increased ductility due to the phase transformation of retained austenite into martensite during the forming process [92,93]. The properties of TRIP steel are constituted by many strengthening mechanisms: solution, dispersion, work hardening, and phase transformation.…”

EXPERIMENTAL DETERMINATION OF THE DRAW BEAD COEFFICIENT OF FRICTION OF CuZn SHEETS IN SHEET METAL FORMING PROCESSES

“…Among the factors influencing tribological phenomena in plastic forming processes, the following should be mentioned: geometry of contact, kinematics of tool movement, load dynamics, physicochemical phenomena on the contact surface and temperature [1,2]. Friction forces occurring on the contact surface of metals have a significant impact on the course of the sheet metal forming process [3,4].…”

“…Determining the influence of the friction process parameters on the value of the coefficient of friction is difficult due to the complexity of the relationship between the individual parameters [13,14]. Many parameters are correlated with each other, causing a synergistic effect [1]. As qualitative analysis of the friction process is difficult, analytical tools are used, such as analysis of variance, artificial neural networks, machine learning methods, genetic algorithms and the Taguchi method.…”