Rock parameters inversion for estimating the maximum heights of two failure zones in overburden strata of a coal seam

Lu, Haifeng; Yuan, Baoyuan; Lin, Wei

doi:10.1016/j.mstc.2010.12.008

Cited by 10 publications

(3 citation statements)

References 3 publications

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“…To verify the outputs of the current study, obtained results are compared with the results of in-situ measurements conducted by other researchers (Haifeng et al, 2011;Zhimin et al, 2010;RafiqulIslam et al, 2009) Rezaei et al (2015a).…”

Section: Results Verificationmentioning

confidence: 78%

Study of the roof behavior in longwall gob in long-term condition

Rezaei¹,

Majdi²,

Hossaini³

et al. 2018

J. Geol. Min. Res.

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Assessment of the roof behavior in longwall gob and estimation of the occurrence of caving and fracturing zones above mined panels are the main factors used in evaluating abutment stresses, ground subsidence, face support and adjacent structures design. The combined height of caving and fracturing zones is taken as equivalent to the height of destressed zone (HDZ) in this study. The longterm estimation of this height plays a key role in accurate determination of maximum ground surface subsidence and the amount of transferred loads towards the neighboring solid sections. In this paper, the roof behavior in longwall gob has been studied in long-term condition. For this purpose, a timedependent model based on the energy balance in longwall mining combined with a rheological model of caved materials with time-varying parameters was used to calculate HDZ. Also, parametric study was conducted to evaluate the effects of geometrical and geomechanical parameters on the roof caving and fracturing. Moreover, the calculated HDZ from the current study is compared with the results of the existing numerical, analytical and empirical models and the in-situ measurements reported in literatures. Comparative study confirms a good agreement that exists between the results of the present study with those of the in-situ measurements and empirical models. It can be concluded that the results of this research can be successfully used to evaluate HDZ in longwall gob in long-term condition to determine the induced stress and surface subsidence in longwall mining.

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Section: Results Verificationmentioning

confidence: 78%

Study of the roof behavior in longwall gob in long-term condition

Rezaei¹,

Majdi²,

Hossaini³

et al. 2018

J. Geol. Min. Res.

View full text Add to dashboard Cite

show abstract

“…For example, most physical models cannot reproduce the irregular falling of caved zones, as shown in Figure 13(a irregular shapes of various sizes. Under certain unfavorable conditions, the immediate roofs cannot rupture into fragments, but horizontally separate and fall onto the floor with sparse vertical fractures [130]. Regular-shaped fragments and poorly fragmented pieces result in a smaller bulking factor of the caved material, indicating that the physical model could produce a larger caved zone and overestimate the height of the fractured zone.…”

Section: Laboratory Physical Modeling Physical Modeling Hasmentioning

confidence: 99%

A General Review on Longwall Mining-Induced Fractures in Near-Face Regions

Bai

2019

Geofluids

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It is believed that underground longwall mining usually produces fractures in the surrounding rocks. On the one hand, mining-induced fractures not only degrade the strength of the rock mass but also serve as main channels for fluids (e.g., water and methane). Fractures facilitate the failure of the rock mass and fluid inrush into working spaces. Therefore, mining-induced fractures are significant for the safety evaluation of underground structures and finding feasible solutions. On the other hand, the fractures are also beneficial for methane collection and coal fragmentation, which are essential for the successful operation of longwall top coal caving mining. Therefore, determining the characteristics of induced fractures is significant for underground longwall mining. From a global perspective, longwall mining-induced fractures in the overburden have been well studied, which improves the understanding of the mining pressure and ground control. However, induced fractures near the longwall face, which have more significant effects on mining activities, have not been summarized. The goal of this review paper is to provide a general summary of the current achievements in characterizing mining-induced fractures in near-face regions. The characteristics of mining-induced fractures in the coal wall, chain pillar, immediate roofs and top coal, and floors are reviewed and summarized. Remarks are made on the current progress of, fundamental problems with, and developments in methodologies for characterizing mining-induced fractures using methods such as field observations, small-scale laboratory tests, physical modeling, and numerical modeling. Based on a comprehensive analysis, the advantages and disadvantages of each method are discussed, and the ideal conditions for applying each of these methods are also recommended.

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“…Singh and Singh (2009) proposed a numerical simulation method to predict the progressive collapse behavior of strata and the performance of dynamic roof support in a given geological mining operation. Lu et al (2011) conducted a physical similarity simulation test based on the geological and technical conditions, and found that the ratio of maximum FWCZ height to mining height was 9.25. Both numerical and physical simulations can predict the height of FWCZ, but they are difficult to achieve a high degree of similarity between the reality and the model.…”

Section: Introductionmentioning

confidence: 99%

Using swarm intelligence optimization algorithms to predict the height of fractured water-conducting zone

Zhao

Feng

et al. 2023

Energy Exploration & Exploitation

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The accurate calculation of the height of fractured water-conducting zone (FWCZ) is of great significance for mine optimization design, water disaster prevention, and safety production of the coal mines. In this article, a height-prediction model of FWCZ based on extreme learning machine (ELM) is proposed. To address the issues of low prediction accuracy and challenging parameter optimization, we optimized the ELM model using the gray-wolf optimization algorithm (GOA), whale optimization algorithm (WOA), and salp optimization algorithm (SOA). These optimization algorithms mitigate the issues of slow convergence, poor stability, and local optimality associated with traditional neural networks. The mining depth, mining height, overburden strata structure, working face length, and coal seam dip angle are selected as the main controlling factors for the height of FWCZ. A total of 42 fields-measured samples are collected and divided into 2 subsets for training and validating with a ratio of 36/6. The prediction capability of GOA-ELM, WOA-ELM, and SOA-ELM models are evaluated and compared, and the results show that the calculation results of the three models are optimized compared with the ELM model. The prediction capability of GOA and WOA are similar, while the prediction results of SOA-ELM are better than the other two models, and the relative errors of the test sets are all less than 10%. Therefore, the SOA-ELM model is finally applied to predict the height of FWCZ formed after the mining of No.15 coal seam in Xinjian Coal Mine. Finally, we verified the prediction results using measured data from the borehole television detection instrument, which showed good consistency. This provides further evidence of the effectiveness of the swarm intelligence optimization algorithm in predicting the height of FWCZ.

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Rock parameters inversion for estimating the maximum heights of two failure zones in overburden strata of a coal seam

Cited by 10 publications

References 3 publications

Study of the roof behavior in longwall gob in long-term condition

Study of the roof behavior in longwall gob in long-term condition

A General Review on Longwall Mining-Induced Fractures in Near-Face Regions

Using swarm intelligence optimization algorithms to predict the height of fractured water-conducting zone

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