<p>The flow of thickened mine tailings within a tailings storage facility is a complex interaction between unconstrained viscoplastic free surface flow and possible coarse particle settling within the flow depth. The broad focus of this work is developing a robust framework for modelling tailings beach flows. Modelling tailings flow evolution in three dimensions within a storage facility will ultimately provide greater understanding of beach slope formation, as well as the ability to optimize deposition sequencing.
This thesis focuses on the first step of developing a tailings model considering the transport and settling of mono-sized coarse particles within two dimensional (length and depth) laminar viscoplastic carrier fluid sheet flow. The 2D model consists of a semi-implicit finite difference shallow water sheet flow model for predicting the viscoplastic flow depth and discharge down the beach. The coarse particle transport and hindered settling within the flow are predicted using a scalar transport model. The scalar transport and shallow water flow model are coupled together using coarse particle rheology augmentation.
Two key novel advancements were made through the model development. The first is coupling the coarse particle rheology augmentation within the free surface flow to the coarse particle hindered settling behavior with depth. This coupling allows for the rheology augmentation due to the coarse solid fraction to be incorporated seamlessly into both the fluid flow solver and the particle settling model. The second advancement is expanding the rheology augmentation and hindered settling coupling to particle flows beyond the Stoke?s flow regime.
Ultimately, the 2D model results are compared against Spelay?s (2007) laminar settling experimental measurements for oil sand thickened tailings (TT) and composite tailings (CT) slurries, along with Spelay?s 1D settling model. The 2D model provides improved prediction of the particle concentration profiles within the fluid flow compared to the 1D model. The 2D model is also able to predict the increase in flow depth due to the particle accumulation on the bed, as well as the downslope particle transport and settling behavior.
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10267449 |
| Date | 02 June 2017 |
| Creators | Treinen, J.M. |
| Publisher | University of Colorado at Boulder |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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