Debris flows are fast flowing landslides, i.e., mixtures of coarse grains and mud. They are extremely destructive. Engineers thus regularly seek to stop them with barriers. This involves complex granular and viscoplastic fluid mechanics’ interactions.
So far, debris flows are modelled either with pure fluid mechanics approaches (e.g., depth-averaged models, smooth particle hydrodynamics or material point method) or with granular approaches e.g., using discrete elements.
This project seek to explore the process of debris flow stopping using advanced numerical models coupling discrete element techniques with computational fluid dynamics. The discrete element technique enable to capture the behaviour of coarse grains, i.e., rocky boulders transported by debris flows, while coupling it with computational fluid dynamics will allow, for the first time, to explore how non-Newtonian properties of interstitial fluid located between coarse grains influences the bulk dynamics of debris flows. The complex interplay between angular coarse grains of various sizes and the viscoplastic interstitial fluid during debris flow propagation and stopping remains generally poorly explored.
This work will be the first comprehensive exploration of:
1. How do coupled discrete element model–computational flow dynamics perform in computing debris flows propagating under regimes actually observed in the field?
2. How does the interplay between force chains within the granular skeleton and viscoplastic interstitial fluid dynamics drive the fluid–solid transition and thus the flowing and eventual stopping of debris flow surges during impact with an obstacle?
Using state-of-the-art coupled modelling approaches will enable us to explore the process at unprecedented accuracy and will shed a new light on simpler approaches modeling only one phase (solid or fluid), helping to improve contact laws, depth-averaged models and laws describing how debris flows pass through singularities as slits, weirs and orifices.
- PI: Guillaume Piton
- Co-PI: Vincent Richefeu
- PhD: Suzanne Lapillonne
- INRAE Grenoble