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Physical modelling of slope stability scenarios can provide new insights into failure mechanisms as well as assistance with interpretation of numerical modelling investigations. To increase the value of such experiments, algorithms that support rapid analysis and quantification of the slope deformation occurring in the experiment are needed. Feature based image analysis has advantages in this respect over area or patch based approaches but suffers from robustness issues. To this end, a new image processing algorithm for measurement of deformation of granular media in laboratory experiments is presented. Our novel algorithm combines a feature detector with model based constraints and outlier detection to achieve fast and robust particle tracking. Comparison with a high precision particle image velocimetry algorithm shows excellent results with much improved processing times. Application of the algorithm for analysis of a laboratory simulation of slope stability is demonstrated and comparison with numerical modelling confirms the algorithm’s flexibility and robustness. [ABSTRACT FROM AUTHOR]

Discrete element method (DEM) is a widely used simulation tool to model physical behaviour of granular materials. In this study 2D DEM simulation has been used to simulate the failure of a sand pile loaded at the crest. The model has been calibrated and validated using experimental force-displacement behaviour, angle of repose and particle velocity profile. The effects of numerical loading rates on simulation results have been investigated. The calibrated DEM model showed that the selection of loading rate is crucial in simulating particle assembly behaviour. In the quasi-static state a small change in loading rate does not change the force-displacement behaviour of the model. However, the system becomes unstable and force-displacement behaviour of the granular assembly diverges from the quasi-static state when the loading rate is higher than the quasi-static loading rate. [ABSTRACT FROM AUTHOR]