Designing the Multiphase Microstructure of Steel for Optimal TRIP Effect: A Multiobjective Genetic Algorithm Based Approach

Abstract

A genetic algorithm-based analysis for the primary microstructural requirements of optimal transformation induced plasticity (TRIP) behavior of the multiphase steel is attempted. Design of primary multiphase microstructure of steel for maximum TRIP effect is perhaps the most important job in TRIP-aided steel design. The quantitative and qualitative control over the complex composite behavior of the different constituent phases present in these steels such as polygonal ferrite, bainitic ferrite, and martensite–austenite constituent is still a challenging task. In this work, the tensile behavior of the steel has been simulated using pertinent models proposed earlier. Necessary assumptions are made using domain knowledge to generalize the tensile model for the considered realm of the problem. Based upon the conflicting nature of the tensile strength and ductility of the steel, the problem is considered here as multiobjective optimization problem. The optimization constraints are inherently taken care by the typical formulation of the problem. The Pareto front results are found quite convincing for TRIP-aided steel design.

Keywords:

• Genetic algorithm
• Microstructure
• Multiobjective optimization
• Pareto front
• Strength–ductility balance
• Tensile property
• TRIP-aided steel