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Computer vision techniques for forensic engineering and damage assessment in structures

This research will develop high-end technology based on computer vision for structural health monitoring and damage localisation in structures. more...

Supervisor(s): Dias-da-Costa, Daniel (Dr)

Non-destructive techniques for detecting damage in structures

The purpose of this research is to develop non-destructive techniques for assessing, measuring and characterising the structural response of structures.  more...

Supervisor(s): Dias-da-Costa, Daniel (Dr)

Concrete and rock hydro-cracking

The purpose of this research is to identify the micro-mechanisms governing the permeability of concrete and rocks featuring cracks, and those governing the crack opening induced by more...

Supervisor(s): Dias-da-Costa, Daniel (Dr)

Development of apps for designing concrete structures

The purpose of this project is to develop a platform to support the design of concrete structures.  more...

Supervisor(s): Dias-da-Costa, Daniel (Dr)

A predictive framework for the behaviour of concrete structures

This research will aim at developing a computational framework based on the discrete crack approach that can be efficiently used in engineering.  more...

Supervisor(s): Dias-da-Costa, Daniel (Dr)

XFEM methods for fracture propagation

The purpose of this research is to develop a FEM method for simulation of fracture. more...

Supervisor(s): Dias-da-Costa, Daniel (Dr)

Simulation of dynamic fracture propagation

The purpose of this research is to develop a computational method for dynamic fracture propagation associated with impact and blast. more...

Supervisor(s): Dias-da-Costa, Daniel (Dr)

Computational modelling of fibre-reinforced concrete and other composites

The purpose of this research is to develop high-end computational tools for the design of fibre-reinforced concrete and other composites. more...

Supervisor(s): Dias-da-Costa, Daniel (Dr)

Development of constitutive models for self-healing cementitious and soil materials

This research will develop constitutive models to handle the mechanics of self-healing materials. more...

Supervisor(s): Dias-da-Costa, Daniel (Dr)

Identification of genetic drivers of ovarian cancer

This project will use insertional mutagenesis in mice to identify and investigate potential genetic drivers of ovarian carcinogenesis. more...

Supervisor(s): Howell, Viive (Dr), Colvin, Emily (Dr)