Indirect bridge health monitoring using artificial neural network (ANN)
Role: PhD Studentship
Start date: January 2020
Duration of award: 4 years
Supervisor: Assistant Professor Abdollah Malekjafarian
Stipend: €18,000 per annum plus UCD tuition fees at EU/Non-EU rates
Hours: Full time
Location: University College Dublin, Ireland
Contact: Dr. Abdollah Malekjafarian (abdollah.malekjafarian@ucd.ie)
Summary: Indirect health monitoring of a bridge is the process of assessing the condition of the structure through analysing the vibration data measured on a passing vehicle. In this project, a machine learning approach will be developed for drive-by damage detection. Machine learning is a relatively unexplored concept in the field of indirect damage detection but shows the potential to account for operational and environmental effects on the bridge response signal. Such variables have previously been major obstacles to the success of indirect detection methods.
Main tasks:
- Developing a numerical framework for the indirect bridge damage detection using ANN using 1D finite element
- Further studies of the algorithms using 3D finite element of vehicle bridge interaction
- Experimental validation of the algorithms using a laboratory-scale vehicle bridge interaction model
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Essential |
Desirable |
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Qualifications |
Candidates must have an honours Level 8 degree in science or engineering or a related discipline. |
Masters in Civil/Structural/Mechanical/Engineering. |
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Skills |
Good communication and writing skills. Good time management skills. Aptitude for multidisciplinary research approaches. |
Fieldwork ability. Ability to work with Matlab. |
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Knowledge |
Background in engineering (Civil Structural/Mechanical). |
Background in structural dynamics and vibrations with an emphasis on lab / field work.
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Language |
Fluent in English. |
Academic writing skills. |
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Behavioural competencies |
Ability to work as part of a team, including collaboration with other disciplines but also independently. Strives for high quality of work and demonstrates commitment to the project. Ability to communicate effectively to enable knowledge and technology transfer |
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For more information click "LINK TO ORIGINAL" below.
This opportunity has expired. It was originally published here:
http://www.euraxess.fr/jobs/funding/phd-scholarship-civil-engineering-indirect-bridge-health-monitoring-using-artificial