Abstract
The sedimentary structure of tailings is of high significance to the engineering design and safety management of tailings dams. However, due to a lack of accurate measurement techniques for the flow field and hydrodynamic conditions of tailings reservoirs, it is challenging to study the complicated sedimentary structure of tailings dams from the perspective of fluid mechanics. This study focuses on developing a large-scale particle image velocimetry (LSPIV) system in a 20 m long and 2 m wide deposition model flume to measure the flow field characteristics during the ore-drawing process accurately. According to the surface flow field characteristics measured by LSPIV, the tailings in the flume can be divided into three zones, namely the fan-shaped zone, channel zone, and laminar flow zone. Then, a simple method for estimating the flow rate of the slurry was proposed using the surface velocities measured by LSPIV. The flow rate of iron tailings slurry in the flume displays a decreasing trend along the flow direction. The variation of the flow rate of tailings slurry can be described by an exponential function. After the deposition of tailings slurry, the sedimentary characteristics of tailings are investigated, and the distribution of iron tailings particles is discussed in combination with the flow field of the tailings slurry. The LSPIV system can be applied to further deposition model tests of different slurry concentrations, discharge flow rates, and tailings compositions to investigate the effects of these factors on the tailings flow and deposition.
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Acknowledgements
We would like to thank Professor W.L. Han (Dept. of Hydraulic Engineering, Tsinghua Univ.) for his unwavering support and guidance throughout this study.
Funding
This work was supported by the National Key R&D Program of China (Grants 2017YFC0804602) and the National Natural Science Foundation of China (Grant 51874260).
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Duan, Z., Shi, H., Li, Q. et al. Experimental study on the hydraulic characteristics of tailings dams through large-scale particle velocimetry. Environ Earth Sci 81, 308 (2022). https://doi.org/10.1007/s12665-022-10427-4
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DOI: https://doi.org/10.1007/s12665-022-10427-4