Debris flows are fast landslides, occurring regularly in mountainous areas around the world. They consist of saturated debris and sediments mobilized by rainfall, and surging at high speed down slopes and natural channels. Due to the combination of large volumes, high speeds, and lack of premonitory signs, they count as one of the most destructive hazards in nature. Especially in highly urbanized areas, they claim thousands of lives every year, and pose a serious threat to settlement development and infrastructure management.
Because of that, it is common practice to install mitigation structures (barriers) along the flow path, with the goal of dissipating the flow energy and preventing it from increasing in size. However, the process by which a barrier can effectively stop a debris flow from growing in size and speed are very poorly understood. Barriers that completely halt the flow are typically over-designed, and tend to fill up after a single event, requiring unmanageable maintenance efforts.
This project envisions the combined use of numerical models and experimental modelling, with the ultimate goal of optimizing the geometry and structural characteristic of debris-resisting barriers. The numerical model is a multiphase DEM-LBM code, which is available in-house at the University of Sheffield. The code is able to simulate in great detail the interaction between the fluid and the solid constituents of the flow. It can also reproduce accurately the mechanisms behind bed erosion and material entrainment. The numerical analysis is supported by experiments performed in the geotechnics laboratory in the university. The lab features the only transparent-soil flume in the UK, which allows observing the flow internal structure thanks to a projected laser sheet, and a smart use of materials with similar refractive indices. Collaborations with partner research organizations located in the Alps (France or Italy) can also be explored as part of the research programme.
The project start date will be 25 September 2023.
Applicants must hold a Master-level degree in Civil Engineering, Geosciences, or related disciplines. Previous experience with scientific computing, or an interest in it, are desirable.
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