Mahajan Pushkar Development of an algorithm to accelerate the simulation of roll forming process

Development of an algorithm to accelerate the simulation of roll forming process

 

Motivation

The roll forming process is emerged as one of the most important metal forming technologies. The design of the roll forming process is very complex and depends upon a large number of variables, which mainly relies upon experience based knowledge. In order to overcome these challenges and to optimize this process, numerical methods are used effectively. These numerical methods are time-consuming and depend on defined numerical parameters. However, computational time required can be reduced with the help of new algorithms.

Steady state in roll forming process
Figure 1: Steady state in roll forming process

Objective

The main objective of this project is to accelerate the simulation of roll forming process with the aid of steady state properties which are evolved during the process without reducing the quality of the results. A new algorithm developed in this project will take advantage of these steady state properties to map state variables on the sheet metal with the aid of a mathematical function, which can be determined by the finite element method. Furthermore, results of the simulation will be verified with experimental results.

Mapping of state variables on the metal sheet
Figure 2: Mapping of state variables on the metal sheet

Approach

The simulation will be performed using numerical method. A steady state zone in roll forming process occurs after each roll station as shown in [Figure 1]. This zone can be recognized with the help of longitudinal plastic strain at the sheet edge for two consecutive time intervals. After reaching steady state, simulation will be stopped and all state variables will be extrapolated until the sheet comes in contact with the next roll station. The mapping is expected to be carried out by a cubic polynomial as shown in [Figure 2]. The same procedure will be repeated until the process is finished.

 

Acknowledgment

This research project is funded by the German Research Foundation (DFG).