Summary
I am an Associate Professor at the University of Cincinnati, USA. I completed my MEng and PhD degrees in the Mechanical Engineering department at Imperial College London, where I was subsequently appointed a Research Associate and then Research Fellow. I maintain an Honorary Lecturer position at Imperial College, and am an active contributing academic in the Non-Destructive Evaluation group and the UK Research Centre in Non-Destructive Evaluation.
My research interests lie in the development of Structural Health Monitoring (SHM) systems, and their application for improved structural integrity assessment. I specialise in developing electromagnetic and ultrasonic monitoring systems focused on addressing real-world industrial challenges. My research into measurement and instrumentation extends to developing techniques to further fundamental understanding of material behaviour and damage mechanics; for example through the development of advanced potential drop measurement systems.
Increasingly, I have directed my attention to the use of monitoring data for improved structural integrity diagnostics and prognostics, encompassing data processing and interpretation techniques. This research links to work with the Structural Integrity group.
Publications
Journals
Jones E, Sciard J, Corcoran J, 2022, The Influence of Creep Induced Grain Boundary Separation on Electrical Non-destructive Evaluation Measurements, Journal of Nondestructive Evaluation, Vol:41, ISSN:0195-9298
Leung MSH, Corcoran J, 2021, Evaluating the Probability of Detection Capability of Permanently Installed Sensors Using a Structural Integrity Informed Approach, Journal of Nondestructive Evaluation, Vol:40, ISSN:0195-9298
Hey Leung MS, Corcoran J, 2021, A probabilistic method for structural integrity assurance based on damage detection structural health monitoring data, Structural Health Monitoring-an International Journal, Vol:21, ISSN:1475-9217, Pages:1608-1625
O’Dowd NM, Madarshahian R, Leung MSH, et al., 2021, A probabilistic estimation approach for the failure forecast method using Bayesian inference, International Journal of Fatigue, Vol:142, ISSN:0142-1123
Zhang Y, Cegla F, Corcoran J, 2020, Ultrasonic monitoring of pipe wall interior surface temperature, Structural Health Monitoring-an International Journal, ISSN:1475-9217