Mechanical Performance‐Based Optimum Design of High Carbon Pearlitic Steel by Particle Swarm Optimization
Ling Qiao, Zibo Wang, Yuan Wang, Jingchuan Zhu
Abstract
Herein, particle swarm optimization is used to quickly acquire the optimal composition range for pearlitic steel. Four groups within the obtained composition range are selected to prepare the steel. Microstructural and mechanical analyses of pearlitic steel are performed, and the results emphasize the significant impacts of elemental Si. The refinement of pearlite interlamellar spacing with degenerated morphology is found to be more prominent for samples with higher Si concentration. The benefit of micro‐alloying on increasing microhardness can be achieved by additive elemental Si, which correspondingly brings about the improving tensile strength and yield strength. Then, a correlation between the evolving microstructure and the resulting mechanical properties is made that satisfies the Hall–Petch relationship. For a full pearlite microstructure, the failure mechanisms are also identified, where the fracture morphology is characterized by a mixed mechanism of brittle and quasi‐cleavage features. However, a thermodynamic analysis is performed to reveal the characteristics of phase transformation induced by elemental Si. Simulation and experimental results show that this approach can effectively generate promising performance features.