Knowledge-driven material design platform based on the whole-process simulation and modeling

In order to realize the agility, collaboration and visualization of alloy material development process, a product development platform based on simulation and modeling technologies is established in this study. In this platform, the whole-process simulation module builds multi-level simulation models based on metallurgical mechanisms from the production line level, the thermo-mechanical coupling field level and the microstructure evolution level. The design knowledge management module represents the multi-source heterogeneous material design knowledge through ontology model, including customers' requirement knowledge, material component knowledge, process design knowledge and quality inspection knowledge, and utilizes the case-based reasoning approach to reuse the knowledge. The data-driven modeling module applies machine learning algorithms to mine the relationships between product mechanical properties, material components, and process parameters from historical samples, and utilizes multi-objective optimization algorithms to find the optimal combination of process parameters. Application of the developed platform in actual steel mills shows that the proposed method helps to improve the efficiency of product design process.