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DOCTORAL CANDIDATE 06

PROJECT TITLE

Advanced Numerical Simulations for SHM of Smart Aerospace FRP Composites

Host Institution:

Politecnico di Torino (POLITO)

PhD enrolment:

Politecnico di Torino (POLITO)

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MYKA MITSIKO ARQUERO ABAQUIN

EDUCATION

MEng in Aeronautical Engineering - Imperial College London​, UK
PhD in Aerospace Engineering - Politecnico di Torino, Italy

ABOUT

Prior to joining the ASSESS Project Myka studied Aeronautical Engineering at Imperial College London, where her master's project focussed on using acoustic emission techniques to identify and monitor flexural fatigue damage in composite coupons. This research project deepened her knowledge and experience regarding PZTs, CFRP manufacturing, laboratory testing compliant with ASTM standards and structural health monitoring. As part of her integrated master's degree, she also completed a year in industry at Cummins, where she designed and performed FEA on diesel engine components in the design team. 

Since working on the experimental aspect of SHM during her undergraduate studies, she have since become fascinated by the simulation and numerical side of this field. The project's dedication to translating innovative research to real-world applications resonates deeply with her personal ambitions to bridge the gap between academia and industry. The transformative potential of SHM technology motivates her and she is eager to contribute meaningfully to the advancement of this field of research.

Objectives

- Research advanced numerical modelling techniques for FRP composite laminates and smart structures.​
- Perform CUF-based FEM simulations to analyse GW propagation in pristine and damaged structures and investigate damage failure characterisation to support RUL estimation​.

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Expected results:

- Advanced FE models for sandwich panels and wind turbine blades​.
- Coupled solutions for smart structures with integrated PZTs​.
- Methodologies to characterise vibration properties and GW propagation of smart FRP composites​.
- Accurate modelling of failure analysis for RUL prognosis​.
- Experimental verification of simulation results​.

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