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Nojus Plungė

PhD Title: Blending ultrasound data with physics-based models to predict damage in structural systems

PhD Supervisor: Emmanouil Kakouris

Monitoring of damage degradation in materials is vital as any cracks will reduce local stiffness, accelerating the ageing process of the physical assets. In-situ ultrasonic monitoring data is valuable for giving the inspectors information on the level of what may be wrong with the structural systems. However, purely data-driven representations do not always give inspectors enough information and the ability to predict how the system will behave in the future. This can be achieved by utilising some knowledge of the physics that underpins the system. This project will use the fusion of experimental data and physical models for failure prediction of materials, by taking measurements and developing models that are hybrid in nature.

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