Optimal location of water level sensors for monitoring mine water inrush based on the set covering model

Wu, Qiang; Du, Zhili; Zhao, Yingwang; Xu, Hua; Zhang, Xiaoyan

doi:10.1038/s41598-021-82121-7

Cited by 11 publications

(8 citation statements)

References 36 publications

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“…When using the SWMM software to simulate disastrous water inrush, the value of water inrush is set according to the drainage capacity of the mining area where each water inrush point is located [43] . The drainage capacity of mining areas I to IV in Beiyangzhuang coal mine is 800 m 3 /h, 1000 m 3 /h, 1200 m 3 /h, and 2000 m 3 /h.…”

Section: Fig 4 Comprehensive Zoning Evaluation Of Water Inrush Risk O...mentioning

confidence: 99%

WITHDRAWN: Study on multi-constraint and multi-objective optimization layout method of monitoring network for mine water inrush

Qiang

Zhao

et al. 2022

Preprint

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Disastrous water inrush often causes heavy property losses and even casualties, while the current theory and technology of mine water prevention and control can not accurately predict the time and place of disastrous water inrush in mine, so monitoring disastrous water inrush has become an urgent problem to be solved. Through the networked deployment of water level sensors in the roadway, this paper proposes a monitoring network for catastrophic water inrush in coal mine, and studies a multi-constraint and multi-objective optimal deployment method for the monitoring network. By setting three practical constraints of mining area, risk level of water inrush and installation at specified location, and constructing two objective functions of minimum total cost and minimum average monitoring time, a mathematical model is established, and then NSGA - Ⅱ multi-objective genetic algorithm is designed to solve the model. As results, the method can optimize the monitoring network for mine water inrush from two dimensions of time and space. The proposed method is then verified in the Beiyangzhuang coal mine in the North China. The results show that the average time of the catastrophic water inrush monitored can be controlled within 916 seconds by using only 28 water level sensors, and the higher the risk level of water inrush, the shorter the monitoring response time. Due to the constraints of installation at specified location, the monitoring network can also take into account monitoring the daily water inflow in the Beiyangzhuang coal mine.

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Section: Fig 4 Comprehensive Zoning Evaluation Of Water Inrush Risk O...mentioning

confidence: 99%

WITHDRAWN: Study on multi-constraint and multi-objective optimization layout method of monitoring network for mine water inrush

Qiang

Zhao

et al. 2022

Preprint

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show abstract

“…Earlier, on June 2, 1984, two mines were submerged due to a water-inrush accident at Fangezhuang coal mine in Hebei Province. To prevent water inrush, significant research has been devoted to examining its mechanisms (Sammarco 1986;Shi et al 2017;Li et al 2018), water sources (Guo et al 2015;Jiang et al 2019;Wu et al 2019;Zhang et al 2020), and how to predict it (Meng et al 2012;Hao et al 2017;Wu et al 2021). However, water inrush accidents are still frequent and difficult to accurately predict because of increasingly complex hydrogeologic conditions that occur with increasing mining depth.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal modeling of water inrush spreading in mine roadway networks

Zhang

Zhao

et al. 2022

Water Science and Technology

Self Cite

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Water inrush accidents seriously threaten underground mining production, so the accurate prediction of the spreading process of water inrush is essential for the formulation of water-inrush-control plans and rescue schemes. This paper proposes a spatiotemporal model based on pipe-flow theory to simulate the spreading process of water inrush in mine roadway networks. The energy-loss term is added to this model to improve the simulation accuracy in bifurcated roadways, and pumps and water-blocking equipment are considered in controlling the spreading process of water inrush. Through experimental case studies, the simulation results and the function of the energy-loss term are verified. A sensitivity analysis is then carried out to assess the impact of the model parameters. The results show that the model outputs are most sensitive to the roadway length, cross-section width, and energy-loss coefficient. The model exhibited maximal sensitivity to the geometric parameters compared with the hydraulic parameters. Furthermore, the spreading process of a real water inrush in a coal mine in North China is simulated, and the water-inrush-control measures are evaluated. The overall results indicate that the proposed spatiotemporal model accurately predicts the spreading process of water inrush and is thus applicable to large-scale mine roadway networks.

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“…From the perspective of coal mine production accidents, water hazards are the second most serious threat after gas accidents 1 – 3 . Ascertaining the hydrological situation and the exact location of water source is the fundamental work of advanced water exploration in coal mine.…”

Section: Introductionmentioning

confidence: 99%

Application of TEM and HDRM in hydrogeophysical surveys in Meisibulake coal mine

Zhang

Zheng

et al. 2022

Sci Rep

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Water disaster is one of the major disasters threatening the safety production of coal mine, which is rank only second to gas disaster. And Meisbluke Coal Mine is seriously affected by water disasters. In order to find out the scope and location of water-bearing areas in Meisbluke Coal Mine. The comprehensive geophysical exploration method combining transient electromagnetic method (TEM) and high-density resistivity method (HDRM) is used to carry out this research. Firstly, the measuring area is determined and the relevant measuring points are arranged, and 73 TEM survey lines and 10 HDRM survey lines were arranged according to the requirements. Then, the principle, data processing method and main parameters of TEM and HDRM are introduced. The TEM detection results show that the thickness of Quaternary inferred by TEM is consistent with the geological conditions revealed by boreholes, and the thickness is about 50–80 m. And the water enrichment of the bedrock is obviously recharged by the Quaternary aquifer. Besides, the water-enriched areas in each elevation are marked and the water inrush runoff channel is deduced based on the 3D scenario inverted by TEM. And the detection results of the water-bearing areas by the two methods are in good agreement with each other, which can confirm and complement each other, and the interpretation of the data is scientific and reasonable with high reliability. Besides, the detection depth of HDRM is larger than that of TEM.

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Optimal location of water level sensors for monitoring mine water inrush based on the set covering model

Cited by 11 publications

References 36 publications

WITHDRAWN: Study on multi-constraint and multi-objective optimization layout method of monitoring network for mine water inrush

WITHDRAWN: Study on multi-constraint and multi-objective optimization layout method of monitoring network for mine water inrush

Spatiotemporal modeling of water inrush spreading in mine roadway networks

Application of TEM and HDRM in hydrogeophysical surveys in Meisibulake coal mine

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