HEAL is part of the COMET IC-MPPE project “TransMet1”, which is dedicated to the transformation in metallurgy to recycled steel. The objective is to provide fundamentals and tools for the production of high-quality recycled and CO2-reduced strip steels.

Based on two use cases, a demonstrator of a material and process design and optimization software based on hybrid modeling techniques for offline use in steel sheet production will be established. Hybrid modelling combines physics-based models with machine learning models. The main strategy is to use a combination of physical and data-driven modeling approaches for the development of process planning tools for steel strip production.

Use case 1 focuses on hybrid model-based prediction of the phase transformation of well-recrystallized austenite into its child phases.

Use case 2 is devoted to hybrid model-based prediction of the deformation behavior.

The task of HEAL in the project is to develop symbolic regression algorithms that can be used for hybrid modeling in use case 1.

Important impacts of the project are the reduction of CO2 emissions due to a switch from the blast furnace route to an electric arc furnace route, an economical use of raw materials such as iron ore and coal due to a radical switch to circular economy and a more efficient steel strip production with lower rejection rates.