The Project The projects’ goal is to create versatile basic models that can be used in larger scale models to model optimal material composition and find better process parameters to produce the new green steel of the future. The project results will help to reduce energy and material wastage by providing a more solid foundation for models used to develop new processes.
The two PhD projects are part of a wider consortium:
link General: Within the Production theme, pellets take a basic role at the start of many processes and understanding them better, their material properties as well as the variations thereof, is of ultimate importance for better, cleaner and greener production. This includes the major long-term goal of developing predictive numerical models, i.e. the digital twin, to be used for process development and optimisation. The micro-ingredient are the particles/pellets and their contacts, the main subject of the project(s). During preparation and high-temperature processing, this includes also micro-mechanics like melting and chemical reactions. Every larger scale elementary process (e.g. REF or DRI) model needs this as basic input, as will be developed and tested on the pellet or coarse grain level of a few pellets, to facilitate the larger scale modeling approaches in the consortium.
This is a joint project between the University of Twente and Tata Steel, combining expertise from fundamental science, granular material modeling, software development, calibration, machine learning, and particulate processes with the applied, industrial experience on metallurgy and steel-making processes.
You will work closely together with the other PhD at UTwente, and with several PhDs from TUDelft and TU-Eindhoven, who will be responsible for developing the larger scale model environment, while you will focus on developing the fundamental basic contact- and particle-models, with physical properties (like mechanics, sintering/melting, and chemical reactions) to be accounted for. Together, you will work on creating a comprehensive virtual twin for basic ingredients of these processes, namely pellets and scrap. Supporting this position is an academic team consisting of two PhD supervisors as well as additional academic staff members with expertise that covers particle modeling, programming and basic experimentation, complemented e.g. by partners at Tata Steel with their vast expertise on steel-making, metallurgy, etc.