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Stochastic Simulation of Tailings Consolidation Process
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- Author(s) / Creator(s)
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A system dynamics (SD) model was developed in the Tailings Management Simulator (TMSim) to simulate consolidation processes under quiescent conditions. A top-down iterative approach guides the overall philosophy of the modelling process. The GoldSim software was used as the main simulation environment to implement various stock-flow relationships and causal loop diagrams. For quiescent consolidation, an explicit finite difference scheme was used to solve the governing equation for one-dimensional large-strain consolidation process. The SD consolidation model was calibrated with a commercial software FSCA under a variety of tailings parameter input and deposit geometry. The model was also validated against past case histories and experimental data. Simulation results demonstrated that the SD model is capable of preserving key physics of the large-strain consolidation process while exposing important variables in a simplified and transparent manner. Once the deterministic base case is successfully simulated, stochastic processes are incorporated. Uncertainties are addressed by assigning probability distributions to selected input parameters. Nested Monte Carlo techniques will be used to explicitly model the two types of uncertainties: those due to inherent randomness (i.e. fines content) and those due to lack of knowledge (i.e. insufficient data collection or ignorance).
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- Date created
- 2018-09-23
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- Subjects / Keywords
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- Type of Item
- Conference/Workshop Presentation