DC11: Dynamic modelling of submarine landslides and induced tsunami propagation

Doctoral Candidate

Mohammadreza Rabinezhad

My name is Mohammadreza Rabinezhad, and I am from Gorgan, Iran. I earned my B.Sc. in Civil and Environmental Engineering from Amirkabir University of Technology (Tehran Polytechnic) and my M.Sc. in Geotechnical Engineering from Sharif University of Technology, where my research focused on Discrete Element Method (DEM) modeling of the behavior of uncemented and cemented coarse-grained soils in triaxial test.

Currently, I am working as a doctoral candidate in the POSEIDON network at the University of Liverpool, supervised by Professor Xue Zhang. My research focuses on the numerical modeling of submarine landslides, aiming to enhance our understanding of their behavior and impacts on offshore infrastructure and coastal safety.

Contact:

Project Details

Host Institutions
University of Liverpool
Secondments

University of Twente
[3 months]
OPTUM
[3 months]

Contact
Mohammadreza Rabinezhad
Supervisors

Dr Xue Zhang
Prof Kristian Krabbenhoft

Dynamic modelling of submarine landslides and induced tsunami propagation

Submarine landslides pose significant risks to offshore infrastructure, such as gas and oil pipelines, offshore wind farms, and electricity grids, as well as coastal communities due to the tsunamis they can generate. This research aims to develop cutting-edge numerical models and solution algorithms to predict and analyze submarine landslides’ evolution and consequences.

Specific objectives include:

  1. Developing models to simulate the coupled interactions between sliding geomaterials and water in submarine landslides.
  2. Creating an open-source PFEM (Particle Finite Element Method) software package with high-performance parallel computing for modeling submarine landslides and tsunami generation.
  3. Quantitatively validating the developed tools through experimental physical modeling.
  4. Investigating the sliding mechanisms of submarine porous mass and their role in hazardous wave generation.

Expected outcomes: This project will contribute to the timely prediction of submarine landslides, enabling mitigation strategies to minimize risks to offshore infrastructure and coastal communities.

 

This project has received funding from the European Union under Grant Agreement No. 101120236
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