The effects of magma intrusion on localized stress distribution and its implications for coal mine outburst hazards

Wang, Liang; Liu, Shimin; Wang, Chenghao; Yin, Guang; Guo, Pin kun; Mou, Jun hui

doi:10.1016/j.enggeo.2017.01.002

Cited by 38 publications

(18 citation statements)

References 30 publications

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“…In the D-S theory of evidence [24][25][26][27], the set of all possible propositions is defined as a universe X={x1,x2,…,xn}, and the basic belief assignment function is defined as m:…”

Section: Decision-level Fusion Based On D-s Theory Of Evidencementioning

confidence: 99%

A Gas Outburst Prediction Model Based on Data Mining and Information Fusion

He¹

2019

RIA

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The gas outburst in coalmines is influenced by multiple factors. These influencing factors are highly uncertain and have complex nonlinear relationships. Considering these features, this paper puts forward a gas outburst prediction model based on data mining and information fusion. On the feature level, the backpropagation neural network (BPNN) was selected to set up a gas outburst identification model, thanks to its strong self-learning ability, and then optimized by the improved particle swarm optimization (IPSO); then, the outputs of the optimized BPNN were taken as the identification results, and used to establish a feature database. On the decision level, the Dempster-Shafter (D-S) theory of evidence was introduced to fuse the identification results in the time domain and the spatial domain, and make decisions on the gas state of the coalmine based on the fused data. Finally, the proposed model was applied the predict the gas outburst in a coalmining area of a coalmine in Shanxi Province, China, using the data collected from the workface, intake airway, return airway and transport roadway. Our model fuses the data on two layers, namely, the time domain and the spatial domain, and reduces the prediction uncertainty to zero. The results show that our model can optimize the prediction parameters, enhance the accuracy of gas monitoring information, and improve the correctness of decisions concerning gas outburst in the coalmine.

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“…In the D-S theory of evidence [24][25][26][27], the set of all possible propositions is defined as a universe X={x1,x2,…,xn}, and the basic belief assignment function is defined as m:…”

Section: Decision-level Fusion Based On D-s Theory Of Evidencementioning

confidence: 99%

A Gas Outburst Prediction Model Based on Data Mining and Information Fusion

He¹

2019

RIA

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“…The mining area covers roughly 1.68 km 2 . The No.7 coal seam of the No.86 mining area is one of the coal seams seriously affected by tectonic movement in the Huaibei coal field (Guo et al., 2016), and also presents the highest levels of outburst risk (Wang et al., 2017). The coal is mostly crushed and it is difficult to find large lumps of coal in the working face.…”

Section: Overview Of the Abnormal Index Workfacementioning

confidence: 99%

“…7 coal seam of the No. 86 mining area has been subjected to extremely high degrees of pulverization, and abnormally high risks of coal and gas outbursts have been detected by in situ stress distribution and outburst indexes measurements (Wang et al., 2017). During mining of coal in this area, gas pressure and content decreased to 0.2 MPa and 3.35 m 3 /t, respectively.…”

Section: Introductionmentioning

confidence: 99%

Pulverization characteristics of coal affected by magmatic intrusion and analysis of the abnormal gas desorption index on drill cuttings

Chen

Wang

et al. 2017

Adsorption Science & Technology

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The gas desorption index of drill cuttings is a basic index that measures the initial desorption capacities of coal seams and predicts coal seam gas outbursts. Following a long period of gas drainage in the No.7 coal seam of the No.86 mining area in the Haizi coal mine, the gas desorption index of drill cuttings was still found to be much higher than the threshold value for outburst risks. This abnormal phenomenon led to the present study of the rational selection of test methods and objects in this context. In this study, particle size distribution, pore structure and gas desorption characteristics of coal samples in anomalous areas were analyzed. We found that desorption characteristics are related to particle size and particle size varies in relation to tectonic stress and magmatic intrusions. It appears that the anomalous readings are related to particle size of the coal, resulting from tectonic/magmatic pulverization. Furthermore, measured particle size of drill cuttings is not actually reflective of coal particle size-larger particles may be comprised of multiple smaller particles. The results show that coal samples with particle size <1 mm accounts for 76.3% of total samples and coal samples with particle size >1 mm only accounts for 23.7% of total samples. The porosity and total pore volume increase as the particle size decreases. The specific surface area increases with decreasing pore diameter. Transitional pores and micropores increase the specific surface area of the coal sample

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“…It is important to understand the stress drop considering both the accumulated plasticity and crack connection (Kong et al 2014;Wang et al 2016Wang et al , 2017. The generation of increasing plasticity is due partly to the local crack connection.…”

Section: Introductionmentioning

confidence: 99%

On the excavation-induced stress drop in damaged coal considering a coupled yield and failure criterion

Xue

Zhou

Liu

et al. 2020

Int J Coal Sci Technol

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Investigating the stress drop of abutment pressure is the key to a deep quantitative analysis of the discontinuous stress redistribution under mining. In the present study, uniaxial and triaxial compression tests are carried out separately to determine the bulk and shear moduli, the cohesion, and the internal friction angle of the coal samples. By extending the meaning of Mohr's circle referring to yield stress instead of the maximum principal stress, a yield line is introduced to illustrate the stress drop of Mohr's circle referring to yield stress instead of the maximum principal stress at the elastoplastic boundary. Furthermore, a theoretical solution of the stress drop as a function of the damage is proposed to investigate how the abutment pressure differs considering the yield line and failure line. In addition, applying the stress drop at the yield line in non-pillar mining, top coal mining, and protective coal mining shows that the damage has a nonlinearly positive influence on the stress drop. The results shows that the bulk modulus and internal friction angle have a more sensitive influence on the stress drop than do the shear modulus and cohesion. Finally, the stress drop is divided into a discontinuous stress drop at the yield line and a structural stress drop at the failure line. The stress drop is effective in describing the discontinuous stress redistribution and shows a clear difference in the movement direction of Mohr's circle considering the unloading pressure.

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The effects of magma intrusion on localized stress distribution and its implications for coal mine outburst hazards

Cited by 38 publications

References 30 publications

A Gas Outburst Prediction Model Based on Data Mining and Information Fusion

A Gas Outburst Prediction Model Based on Data Mining and Information Fusion

Pulverization characteristics of coal affected by magmatic intrusion and analysis of the abnormal gas desorption index on drill cuttings

On the excavation-induced stress drop in damaged coal considering a coupled yield and failure criterion

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