Micro-scale analysis of Backward Erosion
Lead Research Organisation:
University of Glasgow
Department Name: School of Engineering
Abstract
Internal erosion is the removal of granular material used to construct dams and flood defences by
seepage, and is the most common cause of dam failure worldwide[1, 2]. Backward erosion, shown
in Figure 1, is one of the most common forms of internal erosion, initiating with a sand on the
downstream side of a dam, and progressing backwards to the reservoir/river, at which point a
catastrophic failure occurs.
Backward erosion most commonly occurs in fine sands and can be considered a type of granular
flow. Some high quality laboratory and field work has been done to formulate expressions to assess
the risk of backward erosion occurring [3].
An example of a small-scale test for backward erosion is shown in Figure 2. These tests show
interesting phenomena like a dependency on particle size, angle of friction, porosity or erosion exit
geometry, and fingering patterns of erosion. To date numerical modelling of backward erosion has
been quite basic, typically involving increasing permeability where a certain seepage velocity is
exceeded [4]. The models do not generally account for micro-scale variables, such as particle
diameter and therefore do not contribute to improving our understanding of the what governs
backward erosion. This project will seek to make micro-scale insights into backward erosion using
particle-scale numerical modelling (DEM-CFD and related continuum modelling). Open source DEMCFD codes will be used (most likely LIGGGHTS) and coarse-graining will be carried out to create
continuum fields.
Research objectives
Use DEM-CFD to model backward erosion including determination of the most effective method for
modelling and validation of the model against experimental data.
Investigation into how particle properties (mean diameter, size distribution, friction) and initial
inhomogeneity affect how backward erosion initiates and progresses.
Use coarse-grained DEM-CFD data to create continuum models which can capture the micromechanics of backward erosion.
seepage, and is the most common cause of dam failure worldwide[1, 2]. Backward erosion, shown
in Figure 1, is one of the most common forms of internal erosion, initiating with a sand on the
downstream side of a dam, and progressing backwards to the reservoir/river, at which point a
catastrophic failure occurs.
Backward erosion most commonly occurs in fine sands and can be considered a type of granular
flow. Some high quality laboratory and field work has been done to formulate expressions to assess
the risk of backward erosion occurring [3].
An example of a small-scale test for backward erosion is shown in Figure 2. These tests show
interesting phenomena like a dependency on particle size, angle of friction, porosity or erosion exit
geometry, and fingering patterns of erosion. To date numerical modelling of backward erosion has
been quite basic, typically involving increasing permeability where a certain seepage velocity is
exceeded [4]. The models do not generally account for micro-scale variables, such as particle
diameter and therefore do not contribute to improving our understanding of the what governs
backward erosion. This project will seek to make micro-scale insights into backward erosion using
particle-scale numerical modelling (DEM-CFD and related continuum modelling). Open source DEMCFD codes will be used (most likely LIGGGHTS) and coarse-graining will be carried out to create
continuum fields.
Research objectives
Use DEM-CFD to model backward erosion including determination of the most effective method for
modelling and validation of the model against experimental data.
Investigation into how particle properties (mean diameter, size distribution, friction) and initial
inhomogeneity affect how backward erosion initiates and progresses.
Use coarse-grained DEM-CFD data to create continuum models which can capture the micromechanics of backward erosion.
Organisations
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/R513222/1 | 01/10/2018 | 30/09/2023 | |||
2441642 | Studentship | EP/R513222/1 | 01/10/2020 | 31/03/2024 | Joshua Gorham |
EP/T517896/1 | 01/10/2020 | 30/09/2025 | |||
2441642 | Studentship | EP/T517896/1 | 01/10/2020 | 31/03/2024 | Joshua Gorham |