PhD Studentship: Artificial Intelligence-Assisted Modelling of High-Rate Ductile Fracture

Supervisors: Dr Emmanouil Kakouris, Prof. James Kermode, Project Partner AWE-NST

Find out more: https://warwick.ac.uk/fac/sci/hetsys/themes/projects2025

High-rate ductile fracture, particularly in scenarios such as shock loading, poses a significant challenge in engineering, as existing models often fail to represent the complex interplay of plastic deformation, strain localisation, and void formation.

This project seeks to enhance the phase-field method, enabling more accurate predictions of fracture under dynamic conditions. State-of-the-art computational techniques combined with insights from advanced physics will be employed to improve the robustness and applicability of fracture modelling.

Artificial intelligence will support this effort, accelerating parameter calibration and facilitating uncertainty quantification for greater accuracy and reliability.

Material failure is a critical area of study in engineering, as understanding how materials behave under stress is essential for designing safe and reliable structures. Dynamic loading conditions, such as impacts or high strain rates, present unique challenges as materials often fail through complex processes such as ductile fracture. In such cases, the material deforms significantly before breaking, involving mechanisms such as strain localisation, where stress concentrates in specific regions, void formation as cavities develop within the material, and crack propagation as these voids link to form larger fractures.

Traditional damage modelling techniques, often struggle to capture these intricate behaviours accurately, particularly in dynamic scenarios. Phase-field modelling offers a powerful alternative, providing a unified framework to simulate fracture processes without the need for explicit crack tracking. Incorporating AI-driven tools further enhances these models by enabling efficient parameter calibration and uncertainty quantification, making simulations more accurate and broadly applicable in engineering contexts.

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. Please note that due to the nature of our project partner's work, nationality restrictions apply to applications for this project.

About us:

The EPSRC Centre for Doctoral Training in Modelling of Heterogeneous Systems (HetSys), based at the University of Warwick, offers an exceptional opportunity for students from physical sciences, life sciences, mathematics, statistics and engineering backgrounds who are passionate about applying their mathematical expertise to tackle complex, real-world problems.

By fostering these skills, HetSys trains the next generation of experts to challenge the cutting-edge of computational modelling in diverse, heterogeneous systems. These systems span a wide range of exciting research areas, including nanoscale devices, innovative catalysts, superalloys, smart fluids, space plasmas, and more.

HetSys offers a vibrant and supportive research environment, ideal for nurturing creativity and academic growth. Our interdisciplinary student community spans multiple cohorts, each at different stages of their PhD journey, creating a rich, collaborative atmosphere.

Funding Details

Additional Funding Information

Awards for both UK residents pay a stipend to cover maintenance as well as paying the university fees and a research training support. The stipend is at the standard UKRI rate.

For more details visit: https://warwick.ac.uk/fac/sci/hetsys/apply/funding/

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