University of Warwick
Project Objectives
The PhD project focuses on developing computational models to better understand material failure under dynamic loading, particularly in ductile fractures. Using phase-field techniques, it will explore processes such as strain localisation, void growth, and crack propagation. AI-driven tools will support efficient parameter calibration and uncertainty quantification, ensuring improved accuracy and practical applications in engineering.
Outcomes
- Developed a phase-field model for simulating high-rate ductile fractures under dynamic loading conditions.
- Enhanced understanding of the interplay between strain localisation, void formation, and crack propagation.
- Developed AI-enhanced tools for efficient parameter calibration and uncertainty quantification.
- Continuum mechanics theory.
- AI and machine learning fundamentals for scientific applications.
- Programming for scientific computing (e.g., Python, C++/Fortran).
Skills that the student will acquire
- Continuum mechanics theory.
- AI and machine learning fundamentals for scientific applications.
- Programming for scientific computing (e.g., Python, C++/Fortran).
How to apply
For full details of the funding available and how to apply follow this link. This is an open-ended deadline and will close upon identification of a suitable student.
More Information
For more information contact Dr Emmanouil Kakouris (Emmanouil.Kakouris@warwick.ac.uk)