Application of rheology to the post-deposition behaviour of tailings is important for the design of the slope of the impoundment, control of layering for purposes of strength enhancement through desiccation, properly describing the mixing of different tailings streams and for dam breach consequence analysis.This paper aims to advance the understanding of tailings rheology in the post-deposition context to aid all of these applications.Firstly, thixotropy and its quantitative implications for beach slope and layer geometry are explored using a simple treatment.Secondly, method dependency in yield stress measurement is discussed, along with how such uncertainty can be practically handled by considering the appropriate stress path and timescale for a particular application.Finally, numerical simulation using a thixotropic rheology of channel flow down a beach and runout from a dam breach experiment, conducted in a centrifuge, is used to highlight the utility of advanced rheology to such problems.The paper uses data collected from published work on both hard rock and oil sands tailings over the last 15 years.
In the digital era, the mining industry benefits from powerful tools that can help to optimise underground backfilling operations and to increase overall safety.Indeed, with current progress in artificial intelligence (AI), machine learning (ML) creates state-of-the-art techniques in the mining sector that could significantly improve the productivity and efficiency of mining operations.The purpose of this study is to apply ML algorithms, including the gradient boosting regressor (GBR), the XGBoost regressor (XGBR), and the support vector regressor (SVR) to predict the uniaxial compressive strength (UCS) of cemented paste backfill (CPB).A total of 1,587 UCS data were used to train the ML algorithms, considering different variables such as the types of tailings, binder and their proportion, solid mass concentration, slump height, water quality, and curing time.The raw data were pre-processed before training the models, as well as their hyperparameters tuning was made by a random search method followed by 4-fold cross-validation.The prediction results show that the GBR algorithm is the most powerful one which has a coefficient of correlation (R) between predicted and experimental values equal to 0.99 and a root-mean-square error (RMSE) equal to 0.16.This prediction is validated through new-lab prepared CPB specimens.
The conventional method of segregated disposal of tailings and waste rock is associated with several environmental problems, especially acid rock drainage (ARD) which is a challenging and crucial issue.Previous studies have shown that mixing tailings and waste rock can potentially decrease ARD potential.However, there are limited studies that quantify the effect of mixture ratio of waste rock and tailings on the water quality.This study presents a developed methodology to design and test different waste rock and tailings mixture ratios through leveraging particle packing theory for binary mixtures.The mineralogy and chemical properties of the mixtures is first presented.Three columns of mixture materials were mounted for a series of leaching tests over a period of about two years to experimentally simulate the impact of different mixture ratios on the water quality.The preliminary results of the leach column tests demonstrate that the ratio of waste rock and tailings of the commingling mixtures influences the unsaturated hydrogeological behaviour and the water quality.The study also provides fundamental data to investigate the hydrogeological and geochemical behaviour of the tailings and waste rock mixtures.The approach used in this study can be implemented to determine an optimised mixture ratio to minimise ARD and alleviate the damaging environmental impacts of segregated disposal.
A key component of underground distribution system (UDS) design for paste backfill is a pressure indicating transmitter (PIT), which allows the pressure at the instrument's location to be measured and used to provide several useful diagnostic functions.These functions include the determination of friction losses and overpressures as well as the detection of pipe breakage or blockage and confirmation of flushing progress.Unfortunately, the usefulness of these PITs can be compromised due to the demanding nature of the application in which the cemented paste will fill up any dead leg in the instrument mounting branch of the pipe spool and prevent pipeline pressures from being accurately measured by the sensor.This requires mounting the PIT close to the pipe's inside diameter, which can lead to sensor damage.PIT accuracy has been found to be unreliable due to these issues, and PITs frequently require cleaning or replacement.This paper discusses a planned PIT mounting spool design that uses a protective liner on the inside diameter of the pipe.The liner allows pressures to be transmitted to the PIT while avoiding the sensor head damage or dead leg build-up problems that currently make PIT usage unreliable.
Lundin Gold's Fruta del Norte project, which is currently the largest gold deposit in Ecuador, achieved commercial production in February 2020.The project includes a mine plan that incorporates both bulk and selective mining methods.Most areas mined will use conventional transverse stoping and will be supported by the drift-and-fill mining method in zones of smaller dimension or with poor geotechnical quality.Backfill is used as a ground support medium with the majority of voids to be filled using cemented paste fill.A paste plant, used to supply the required backfill tonnage, has been constructed directly over the orebody.The design of the paste plant is unique, accounting for challenges in topography, a sensitive local environment and challenging feed tailings.The paste plant was successfully commissioned in quarter three 2020.In this case study, the design is described in how it caters for the unique requirements of the project.Further to this, construction and commissioning challenges faced and lessons learned are documented.
