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  A New Generation of Dam Assessment: An Artificial Intelligence Approach

   School of Science, Engineering and Environment

  Dr Eda Majtan, Dr Alireza Ahangar Asr  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Information on this PhD research area can be found further down this page under the details about the Widening Participation Scholarship given immediately below.

Applications for this PhD research are welcomed from anyone worldwide but there is an opportunity for UK candidates (or eligible for UK fees) to apply for a widening participation scholarship.

Widening Participation Scholarship: Any UK candidates (or eligible for UK fees) is invited to apply. Our scholarships seek to increase participation from groups currently under-represented within research. A priority will be given to students that meet the widening participation criteria and to graduates of the University of Salford. For more information about widening participation, follow this link: [Scroll down the page until you reach the heading “PhD widening participation scholarships”.] Please note: we accept applications all year but the deadline for applying for the widening participation scholarships in 2024 is 28th March 2024. All candidates who wish to apply for the MPhil or PhD widening participation scholarship will first need to apply for and be accepted onto a research degree programme. As long as you have submitted your completed application for September/October 2024 intake by 28 February 2024 and you qualify for UK fees, you will be sent a very short scholarship application. This form must be returned by 28 March 2024. Applications received after this date must either wait until the next round or opt for the self-funded PhD route.


Project description: A significant number of dams are in service to supply domestic and industrial water, generate hydroelectric power as well as control flood effects on the society they serve. Tens of thousands of large dams were built in the 20th century, approximately 58,700 large dams worldwide, with a design life of 50 to 100 years. Many of them are operating beyond their design life and are expected to be decommissioned considering their ageing signs, increasing environmental loads and associated dam failures. To prevent their sudden damage and failure, there is a need to detect early structural damage and provide warning of potential progressive structural integrity problems which could lead to potential failure. In this project data from operating and failed dams will be collected and synthetic data will be created using appropriate finite element modelling. A comprehensive data set will then be created and implemented to develop and validate Artificial intelligence-based models to predict damage occurrence and/or progression in operating dams to assess their operation ensuring they continue operating safely to the end of any extended lifetime.

Computer Science (8) Engineering (12) Geology (18)

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