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Velocity field and outflow discharge behavior in overtopping dam-break of an iron mine tailings dam: a model test

Landslides in mining engineering mainly occur in tailings dams. The evolution of monitoring indexes is important for the improvement of warning accuracy in tailings dam breaks. The velocity field and outflow discharge behavior in overtopping dam-break of an iron mine tailings dam were studied. There...

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Bibliographic Details
Published in:Bulletin of engineering geology and the environment 2024-06, Vol.83 (6), p.232, Article 232
Main Authors: Ma, Changkun, Guo, Xiaogang, Yang, Chunhe, Zhang, Chao, Ma, Lei, Li, Xueting
Format: Article
Language:English
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Summary:Landslides in mining engineering mainly occur in tailings dams. The evolution of monitoring indexes is important for the improvement of warning accuracy in tailings dam breaks. The velocity field and outflow discharge behavior in overtopping dam-break of an iron mine tailings dam were studied. There were two stages of the tailings flow in the model test, corresponding to two types of flow state, granular flow and viscous flow, respectively. The absolute vorticity vertical line | w | vertical line was measured to reveal the influence of terrain on the velocity. An estimation equation for the maximum velocity was proposed, in which vorticity and the height difference of terrain were taken into account. The standard deviation of the velocity stack e ¯ with minus on top was used to distinguish the dam-break flow into “collision” and “non-fluctuating” regions. The velocity profiles of the transversal section were concluded to be three patterns based on the positions of the peak velocities. The three patterns well described the velocity field at different flow states. Estimation equations were proposed for the transversal section velocity profile. Based on the velocity profile equations, the estimation method of the outflow discharge was developed. This study provides a reference for improving the accuracy of tailings dam break warnings by non-intrusive monitoring methods.
ISSN:1435-9529
1435-9537
DOI:10.1007/s10064-024-03733-7