Artificial Intelligence and Optimisation in multi-pass Weld Modelling and Additive Manufacturing of Thick-Section Ferritic Steel Components
- Organisation: The University of Manchester
- Funding: fees + UKRI standard rate stipend
- Supervisors: Dr Anastasia Vasileiou and Professor Mike Smith
This PhD project aims to use a state-of-the-art, multi-scale weld modelling approach combined with optimisation methodologies and artificial intelligence techniques, to develop tools and provide guidelines for efficient weld modelling of ferritic steels. The framework that will be developed will be transferred to modelling and validating additive manufacturing processes, and its applicability will be assessed.
This project will benefit from the experience, the experimental data, models and code accumulated through various successful research projects, including the EPSRC-funded New Nuclear MANufacturing (NNUMAN) programme, the BEIS-funded MATTEAR project, the H2020 ATLAS+ project the EUREKA funded projects SIMCAST and MAJEPCAST and the NET European Network on Neutron Techniques Standardization for Structural Integrity. This project will also benefit from the direct collaboration and support from academic and industrial partners.
The project is multi-disciplinary and requires a good understanding of engineering principles, continuum mechanics, finite element analysis, material science, artificial intelligence, deep learning, machine learning, optimisation, programming.
For full details of the project and to apply, click here