Modelling and data analytics
We use mathematical modelling as a tool for simulation of the behaviour of materials, processes and systems plays a significant role in contemporary science and research. Its potential for developing methods for numerical design and prediction of phenomena in physico-chemical and biological systems increases with the continuously increasing computer power, data storage and improved visualisation approaches. Mathematical models can be used as simulators of new processes and materials, providing ways for the efficient optimisation of their parameters. Such techniques can also be used for control and decision making at different levels – from physical performance to strategy building. The use of mathematical models to predict process behaviour and material properties responds to the increasing demand for digitalisation of the economy.
The Research Group integrates expertise in the mathematical modelling of chemical, physical and mechanical, processes and materials in the School of Chemical and Process Engineering. The research topics cover broad areas in materials science and particle technology and answer questions of importance to the industrial practice. Main industrial collaborators are Pfizer, Astra Zeneca, P&G, TOTAL, AbbVie and Atomising Systems Ltd.
The groups modelling expertise is contributing to the success of two EPSRC Future Manufacturing Research Hubs: Liquid Metal Engineering (LiME) and Manufacturing using Advanced Powder Processes (MAPP), and two EPSRC Programme Grants: Friction: the Tribology Enigma and the Virtual Formulation Laboratory.
The group members are involved in diverse applications of commercial software packages – Fluent, Aspen HYSYS, MatLab, Crystal Maker Suite, EDEM and ROCKY for Discrete Element Method, and also in developing original codes, such as DigiDEM. This includes the use of software in experiments for monitoring and control as well as for data analysis. Modelling tools for plant reconfigurability based on a modular and a network approaches have been developed. New approaches to modelling processes of crystallisation, milling, coating, cohesive powder flow and predicting particle size, shape and size distribution have been developed and applied to process optimisation. Models for the prediction of materials microstructures, using state-of-the-art numerical techniques including mesh adaptivity, implicit time-stepping, advanced multigrid solvers and parallel execution, have been developed and are being used to support solidification experiments on the International Space Station. The research in the group benefits from the modern facilities in the Leeds Electron Microscopy and Spectroscopy Centre (LEMAS).
View all members of our research group and publications.
We have opportunities for prospective postgraduate researchers. Find out more.
If you would like to discuss an area of research in more detail please contact the Research Group Leader: Dr Antonia Borissova Dimitrova.