High density (HD) tailings are tailings that have been sufficiently dewatered, where they exhibit a yield stress upon deposition, and therefore naturally form gently sloped deposits that do not requires dams for containment. It is essential to comprehend and model the flow behaviour during deposition to predict the final geometry of the stack and control storage capacity; which are important design elements to HD tailings technology.As HD tailings exhibit a yield stress, modelling stack geometry constitutes, in part, a problem of non-Newtonian flow with a free surface. This research investigated modelling the flow behaviour of HD tailings, using an open-source Smoothed Particle Hydrodynamics (SPH) code. The results indicated that two-dimensional simulations using SPH agreed well with experimental data for single and multi-layer flume tests. SPH has the advantage over simpler methods, such as Lubrication Theory, as SPH better predicts the geometry when inertia influences the flow of tailings. iii I would like to thank Ms. Payal Chadha for her kind assistance.Finally, I would like to thank to my family, my boyfriend and my friends for their constant encouragement and support.
Consolidation parameters are required to support the disposal management of soft soils or mine tailings. The estimation of these parameters from simple correlations using easily measured properties can be advantageous, and considerable work has been done on this topic. This paper proposes two innovations that advance this work: (1) hydraulic conductivity-void ratio (k-e) estimation can be substantially improved by using a single measured value at a high-void ratio, and (2) the compressibility curve itself can be a useful predictor of k-e. Using these findings, general equations are derived that describe k-e using a power law, where the power is either 4 or 5. Examining 79 k-e data sets from clays, clayey tailings, and dredged materials, 94% of all predicted k values are within an order of magnitude of measured k-e values. This level of accuracy, coupled with the advantage of anchoring the k-e function by a measured value at a high-void ratio, is shown to result in robust predictions of settlement in large strain consolidation analyses.
Large strain consolidation (LSC) behaviour of mineral slurries regulates the performance of tailings management and reclamation plans. The hydraulic conductivity-void ratio relationship primarily influences this behaviour, dominating the long-term performance of fine-grained slurries with higher initial water contents. However, the determination of this function can be very challenging and time-consuming, considering the long duration of the conventional tests and significant variation in hydraulic conductivity values with the wide range of void ratios.This study focuses on identifying or creating a rapid method to evaluate the large strain consolidation parameters, especially the k-e relationship, of fine-grained soils by (i) establishing a relationship between the consolidation parameters and more easily measured properties and (ii) designing a self-weight consolidation setup to evaluate the k-e relationship using Instantaneous Profiling Method (IPM). For part (i), a total of 79 k-e data sets of fine-grained soils are examined. Using some of the above innovations, equations are found that require only a single measurement of hydraulic conductivity at a single void ratio. When applying these new equations to the k-e data set, 94% of the predicted k values are within an order of magnitude of the measured data points. This is likely sufficient for this method to be used as a screening tool for tailings treatments. For part ii), the design of a prototype consolidometer is introduced, and the consolidation behaviours of various finegrained soils are evaluated. The prototype is designed as an alternative experimental setup to conventional laboratory tests and aims to rapidly assess the k-e equation for fine-grained soils. The test column was instrumented with tensiometers and capacitance-based sensors c
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