Application of Mean Modulus in Three-Point Bending and Roll Forming

Area of Science:

• Materials Science
• Mechanical Engineering
• Computational Mechanics

Background:

• Nonlinear unloading significantly impacts springback prediction accuracy in plastic forming.
• Precision forming requires reliable springback prediction for guiding manufacturing processes.

Purpose of the Study:

• To enhance the accuracy of springback prediction in the plastic forming of SUS304 stainless steel.
• To validate a novel finite element modeling approach incorporating nonlinear unloading effects.

Main Methods:

• Conducted uniaxial tensile and loading-unloading-loading tests on SUS304 stainless steel.
• Calibrated flow stress and chord modulus mathematical models based on experimental data.
• Developed and compared constant elastic modulus finite element models (E0FEM) with mean modulus finite element models (E¯cFEM) for three-point bending and roll forming simulations.

Main Results:

• The mean modulus finite element models (E¯cFEM) demonstrated a close agreement with experimental results from three-point bending and roll forming tests.
• Simulation outcomes from E¯cFEM showed minimal differences compared to actual test data.
• The study verified the feasibility and suitability of the E¯cFEM approach for springback prediction.

Conclusions:

• The mean modulus finite element model (E¯cFEM) is a feasible and accurate method for predicting springback in plastic forming.
• Incorporating nonlinear unloading behavior through a mean modulus is crucial for precision forming applications.
• The validated E¯cFEM approach provides a reliable tool for guiding the precision forming of SUS304 stainless steel.