Yadvendra Yadvendra
Using industry research skills gained when modelling of hot rolling, Yadvendra will continue on this path and address the challenges in new product development cycle of micro alloyed steels. These new product development processes currently lack input from rigorous mathematical modeling techniques. New modeling techniques will be developed and integrated with databases to enable more rapid product development and more efficient product production processes.
What were you doing before joining Steel for a Fossil Free Future?
Before joining Steel for a Fossil Free Future, I worked as a researcher in the R&D division at Tata Steel after completing my master’s degree. My work primarily focused on developing models for steel plants, particularly for hot rolling mills. Additionally, I was involved in a multiscale modeling project, where information was integrated across different length scales—from atomic to macroscopic levels. This included working with Density Functional Theory (DFT), Kinetic Monte Carlo (KMC), and phase field modeling techniques. I was also part of a team that developed a heat transfer model for the wire rod mill and the run-out table in the hot rolling mill.
What will you be doing as a PhD/Post Doc?
As part of my PhD project, I will be modeling the microstructure evolution during the hot rolling process in a steel plant. My focus will be on the precipitation kinetics of carbonitrides in microalloyed steels. The shape, size, volume fraction, and distribution of these precipitates play a crucial role in determining the final mechanical and electrical properties of the rolled steel. Additionally, my research will explore the effects of temperature variations and applied stress on the precipitation kinetics.
What challenges will your PhD/Post Doc work contribute to solving?
My PhD work aims to address challenges in the new product development cycle of microalloyed steels, which currently lacks rigorous mathematical modeling techniques. As a result, developing new steel grades requires extensive time, multiple experiments, and numerous plant trials. Industrial R&D researchers often do not have access to reliable models that could help reduce the number of experiments and optimize plant trials. Without accurate predictive models, these trials can decrease work efficiency and generate excessive scrap, which is undesirable from both operational and sustainability perspectives.
While some commercial software exists for modeling precipitation kinetics, these tools are often difficult to integrate with other models used in the steel industry. My research will focus on developing a specialized program tailored for researchers and steel manufacturers to streamline new grade development. A key challenge will be building a robust model that accounts for strain effects on materials while integrating seamlessly with thermodynamic databases. Addressing these challenges will contribute to a more efficient, cost-effective, and environmentally sustainable steel production process.
How can your research contribute to address those challenges?
My research aims to tackle these challenges by conducting an in-depth review of precipitation kinetics literature, selecting or developing a suitable model, and integrating it with thermodynamic databases. By creating a reliable and adaptable model, the efficiency of the hot rolling mill can be improved, leading to reduced scrap generation and more optimized processing conditions. Additionally, this research will contribute to shortening the new product development cycle, making the process more cost-effective and sustainable for the steel industry.
The name of my research project is…
The current working title of my research project is “Simulation and Analysis of Carbonitride Precipitation in Hot Rolling Processes.” This project focuses on modeling the precipitation kinetics of carbonitrides in microalloyed steels and their impact on the final properties of rolled steel.