Rationalisation of steel grades and specifications
One of the adverse consequences of excessive use of metallic materials is that there are currently thousands of grades of metallic materials in commercial use. Many of them differ only slightly in composition, processing conditions or origin of production, offering essentially the same performance. Unnecessary alloying elements and excessively tight alloy specifications increase production costs, reduce resource productivities, cause more environmental damage, and make the end-of-life products difficult (if not impossible) to recycle. This is not compatible with Circular Economy principles. Recycling can be improved significantly with materials rationalised and products engineered from the start for this purpose. For instance, the current 3500 grades of steel (WSA) can be reduced to 50-100 without compromising engineering applications.
This project aims to apply most advanced methods of accelerated discovery (machine learning, artificial intelligence, optimisation) to the rationalisation of steel grades to facilitate full metal circulation. The project contributes to slowing the resource loop by design for standardisation and compatibility. The specific research activities may include: (1) development of machine-learning techniques and algorithms for classification of alloy systems based on their compositions, thermomechanical history, levels of performance and fields of application; (2) application of the developed approaches to (a) standardisation of alloy compositions, by using commonly available alloying elements and avoiding the recyclability-limiting elements, and (b) optimisation of thermomechanical treatments for high performance; (3) validation of the developed approaches with the aid of process modelling and in view of the existing experimental data.
The funded studentship is £88,918 for up to 4 years duration. Studentship starts from the 1st of October 2021.
The project will be aligned with the newly established Circular Metals Hub hosted by Brunel Centre for Advanced Solidification Technology (BCAST) at Brunel University London. You will be interacting daily with researchers and academics in BCAST, Brunel University London and in partner academic and industrials organisations. In this close collaboration lies the foundation for your promising career path.
Enquiries should be directed to Professor Hamid Assadi at hamid.assadi@brunel.ac.uk
Eligibility
For non-UK nationals a proof of English proficiency (IELTS 6.5 and more) or the eligible proof of undergraduate education received in English is required.
You should have or expect to receive by the beginning of this PhD study a first degree (BSc) at 2:1 or above in a suitable engineering and science discipline, e.g., materials science, mechanical engineering, physics or applied mathematics. A MSc level qualification is desirable.
A strong background in materials science and applied mathematics is desirable as the project includes mathematical modelling and optimisation.
How to apply
Please email the following to hamid.assadi@brunel.ac.uk and cedps-pgr-office@brunel.ac.uk by the 30 June 2021:
Your up-to-date CV.
Your single A4 statement on why would you like to do this project and why do you believe you qualify to do so.
Copies of your degree(s) certificates(s) and transcripts.
Evidence of your English proficiency (if applicable).
Names and contact info of three academic referees.
Meet the Supervisor: Prof Hamid Assadi
Prof Hamid Assadi is the Head of Virtual Engineering Centre and Professor of Solidification at Brunel University London. He studied Materials Engineering at Shiraz University, and received his PhD in Materials Science and Metallurgy from University of Cambridge in 1996. His work experience includes a professorship at Tarbiat Modares University, as well as several visiting appointments at Helmut Schmidt University, Max Planck Institute for Iron Research, and German Aerospace Centre (DLR).
Research Interests
I am interested in modelling and simulation of materials and manufacturing processes, ranging from solidification and diffusion bonding to metal forming and cold spraying, with a focus on microstructure development under dynamic or non-equilibrium conditions.
I have been using the finite element method to simulate thermomechanical processes, as well as a combination of phase-field, cellular automata and lattice Boltzmann models to simulate microstructure development in thermal and electrochemical processes.