Research Projects

Steel sheet, coil, and plate manufacturers are under constant pressure to enhance caster production rate while simultaneously maintaining its quality. This is due to the continuous quality demands imposed by the different customer ends. However, productivity and slab quality are inversely proportional, and the producer's bottom line faces a major impact due to more defects followed by rejections. The nature of fluid flow followed within tundish and moulds are the most important parameters to ensure cleaner steel and control defects such as slivers, pencil pipe, blister, etc. Physical and mathematical modeling is essential for understanding the process and optimizing fluid flow natures within moulds for this high-temperature phenomenon. With the advancement of AI-ML, an extensive study can easily be performed for this above process for a more robust study of process and mould parameters optimization and prediction with quality product developments. The current proposal will deal with the development of a digital twin of slab caster mould with the liquid metal flow and cleanliness. The project will be divided into three different sections, i.e. physical modeling, mathematical modeling, and machine learning. A digital twin will be developed by coupling the computational and AI model with the physical model (water model). A full-scale water model mould of standard Indian industries slab caster dimensions with a high-speed camera to record high-velocity argon gas bubbles will developed. Similarly, a computational fluid dynamic (CFD) DPM (discrete phase modeling) model (with more additions) will developed to validate water model results. An artificial neural network (ANN) ML-based model will be developed with these validated experimental conditions and output results such as argon bubbles average size, average velocity, and creation of a graphical user interface (GUI) window of input-output representation where a quick decision will be made instantly without doing any further experiments. The overall aim of this project is to implement a lab full-scale model for the steel industry to fulfill Industry 4.0. The project aim is to identify solution strategies for enhancing steel cleanliness in the mould and increasing the productivity for ultra-low carbon steel and drawn steel grades. Projected cost savings are expected to be more than 17 crores/yr by improving both liquid steel and solid steel quality. Results from this study will enhance knowledge that will facilitate better design and control of the continuous casting process. An industry approach to different Indian steel industries will be made for more advanced studies with this developed water model and CFD models. Several highly qualified personnel (HQP) including undergraduate and postgraduate students and PhD students will be trained in the course of the project in the area of steelmaking and casting and will eventually enter the steel industry or academia in India and globally.