Overview:

Structural Health Monitoring (SHM) has been identified as a key technology in damage tolerance design for the next generation of composite aircraft. However, there still remains a big gap to go from a laboratory based set-up to an established and certified Non-Destructive Technique (NDT) used for aircraft maintenance. This project will identify and address the required advances to close this gap and have a robust and reliable SHM system for damage detection and characterization in composite structures. The research is based on monitoring the response of the structure by actuating ultrasonic guided wave and sensing the propagated wave using surface-mounted piezoelectric transducers. The existence of damage (debonding, delamination, softening) will alter the propagational properties of the guided waves. By identifying the signal features related to the damage area, damage can be detected and characterized. Robust damage detection and identification methodologies will be developed for a network of sensors covering large areas and capable of functioning under real load conditions. The main focus at the methodology level will be on characterizing different damage scenarios in composites (various size and severity due to probable impact events) based on the reflection patterns of ultrasonic guided waves. Each damage scenario will have a different fingerprint and by relating the fingerprint to type and severity of damage, damage can be characterized. This will be done both experimentally and numerically. The focus of technical innovation will be on wireless sensing technology and energy harvesting. The student will contribute to the ongoing research at the department and have access to a highly equipped SHM lab dedicated to research.

Prerequisites:

Only the very best student will be considered for this position. Candidates should have (or expect to obtain) a good upper-second class or first class honours degree (or equivalent) in aeronautics or similar engineering disciplines. Strong background in numerical analysis (non-linear, dynamic) and excellent analytical and experimental skills are required. Signal processing and programming experience is an advantage (e.g. Matlab, Python, LabView).

Apply:

The studentship is for three years starting in 2015 and will provide full coverage of tuition fees and an annual tax-free stipend of circa £15,720. Due to the nature of the funding, students must be UK nationals, or EU nationals who have lived in the UK for the past 3 years. Other EU citizens are eligible for a fees-only award. Non-EU students are ineligible, unless they have been ordinarily resident in the UK for 3 years preceding the date of application for purposes other than education.

Interested applicants should make initial informal enquiries via email to Dr Zahra Sharif Khodaei (z.sharif-khodaei<στο>imperial.ac.uk) and then follow the standard College online application procedure (http://www3.imperial.ac.uk/pgprospectus/howtoapply).

For queries regarding the application process, please contact Ms Lisa Kelly by email to:l.kelly<στο>imperial.ac.uk or phone on +44 (0)20 7594 5056.

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