Determination of the sensitivity index and its critical value for outburst risk prediction: A case study in Fuxiang mine, China

Wang, Fakai; Sun, Zhongguang; Li, Lei; Li, Xuelong

doi:10.1177/0263617420963735

Cited by 8 publications

(3 citation statements)

References 32 publications

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“…The gas desorption indices K 1 and Δ h 2 are always selected as the methane desorption indices for the prediction of the outburst risks of mining coal seams. , The desorption index K 1 represents the amount of gas desorption within the first minute ( Q 1 ), and the index Δ h 2 is a gas desorption parameter expressed by the pressure differences of water column caused by the intrusion of the desorbed gas into a U-shaped instrument within the third to fifth minutes ( Q 3–5 ). , The relationships between the initial desorption amounts Q 1 and Q 3–5 and the moisture content are shown in Figure . The two desorption parameters decrease exponentially with the moisture content.…”

Section: Analysis and Discussionmentioning

confidence: 99%

Experimental Study of the Pore Structure and Gas Desorption Characteristics of a Low-Rank Coal: Impact of Moisture

Chen

Zhang

et al. 2022

ACS Omega

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Coal–water interactions have a prominent impact on the prediction of coal mine gas disasters and coalbed methane extraction. The change of characteristics in the microscopic pores of coal caused by the existence of water is an important factor affecting the diffusion and migration of gas in coal. The low-pressure nitrogen adsorption experiments and gas desorption experiments of a low-rank coal with different equilibrium moisture contents were conducted. The results show that both the specific surface area and pore volume decrease significantly as the moisture content increases, and the micropores (pore diameter <10 nm) are most affected by the water adsorbed by coal. In particular, for a water-equilibrated coal sample at 98% relative humidity, micropores with pore sizes smaller than 4 nm as determined by the density functional theory model almost disappear, probably due to the blocking effects of water clusters and capillary water. In this case, micropores with a diameter less than 10 nm still contribute most of the specific surface area for gas adsorption in coal. Furthermore, the fractal dimensions at relative pressures of 0–0.5 (D 1) and 0.5–1 (D 2) calculated by the Frenkel–Halsey–Hill model indicate that when the moisture content is less than 4.74%, D 1 decreases rapidly, whereas D 2 shows a slight reduction as the moisture content increased. In contrast, when the moisture content exceeds 4.74%, further increases in the moisture content cause D 2 to decrease significantly, while there is nearly no change for D 1. The correlation analyses show that the ultimate desorption volume and initial desorption rate are closely related to the fractal dimension D 1, while the desorption constant (K t) mainly depends on the fractal dimension D 2. Therefore, the gas desorption performances of coal have a close association with the pore properties of coal under water-containing conditions, which indicate that the fluctuation in moisture content should be carefully considered in the evaluation of gas diffusion and migration performances of in situ coal seams.

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Section: Analysis and Discussionmentioning

confidence: 99%

Experimental Study of the Pore Structure and Gas Desorption Characteristics of a Low-Rank Coal: Impact of Moisture

Chen

Zhang

et al. 2022

ACS Omega

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“…This kind of CGO disaster is generally referred to as the low-index coal and gas outburst (LI-CGO) [7,8]. Therefore, in order to obtain a more accurate critical size of the prediction index to predict LI-CGO, scholars have carried out research on sensitive indexes and critical values for LI-CGO prediction from different coal seams [7,9,10]. However, this is difficult not only because it needs a large number of field tests but also because different coal geological conditions have different sensitive indexes and critical values [11].…”

Section: Introductionmentioning

confidence: 99%

Study on the Prediction of Low-Index Coal and Gas Outburst Based on PSO-SVM

Mao

Zheng

et al. 2023

Energies

Self Cite

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Low-index coal and gas outburst (LI-CGO) is difficult to predict, which seriously threatens the efficient mining of coal. To predict the LI-CGO, the Support Vector Machine (SVM) algorithm was used in this study. The Particle Swarm Optimization (PSO) algorithm was used to optimize the parameters of the SVM algorithm. The results show that based on the training sets and test set in this study, the prediction accuracy of SVM is higher than that of Back Propagation Neural Network and Distance Discriminant Analysis. The prediction accuracy of the SVM model trained by the training set T2 with LI-CGO cases is higher than that of the SVM model trained by the training set T1 without LI-CGO cases. The prediction accuracy gets better when the SVM model is trained by the training set T3, made by adding the data of the other two coal mines (EH and SH) to the training set T2, that only contains the data of XP and PJ. Furthermore, the PSO-SVM model achieves a better predictive effect than the SVM model, with an accuracy rate of 90%. The research results can provide a method reference for the prediction of LI-CGO.

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“…Currently, although the casualties caused by coal mine disasters have been effectively controlled, coal and gas outburst is still one of the most serious disasters associated with coal mine (Fu et al 2020;Wang et al 2014b;Zhai et al 2016). A coal and gas outburst is closely related to the methane desorption capacity of coal, and many methane desorption indices are used to predict the outburst risk (Wang et al 2020b;Xue et al 2020). Therefore, understanding the methane desorption characteristics of coal is critical for the prediction of coal and gas outburst.…”

Section: Introductionmentioning

confidence: 99%

Experimental Study on Pore Structure and Gas Desorption Characteristics of a Low Rank Coal: Impact of Moisture

Yang

Chen

Tian

et al. 2021

Preprint

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Coal and gas outburst is one of the most serious disasters for underground coal mining. The water adsorbed on coal can leads to that the pore structure of moist coal is different from that of dry coal, thereby affecting methane desorption characteristics of coal for the outburst risk prediction. In this paper, the impact of moisture on pore structure and methane desorption performance were investigated. The analysis on low-temperature nitrogen gas adsorption tests show that the micropores (pore diameter < 10 nm) are most affected by the adsorbed water. In particular, for water-equilibrated coal sample at 98% relatively humidity, the micropores less than 4 nm analyzed by DFT pore size distributions almost disappear probably due to the blocking effect of the formed water clusters and capillary water. In this case, the micropores can still contributes most sites for gas adsorption. Furthermore, the fractal dimension at relative pressure of 0–0.5 (D1) and 0.5–1 (D2) calculated by the Frenkel-Halsey-Hill model indicates that, when moisture content is less than 4.74%, D1 decreases rapidly while D2 shows a slight change; whereas, further increases in moisture content results in that D2 decreases significantly and D1 remains at about 2.32. Further investigation shows that, below the equilibrium moisture content, the ultimate desorption volume (A) and initial desorption rate (V0) are closely related to D1, while the desorption constant (Kt) mainly depends on D2. Therefore, the adsorbed moisture has significant negative impact on methane desorption performances by affecting characteristics of coal’s pores.

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Determination of the sensitivity index and its critical value for outburst risk prediction: A case study in Fuxiang mine, China

Cited by 8 publications

References 32 publications

Experimental Study of the Pore Structure and Gas Desorption Characteristics of a Low-Rank Coal: Impact of Moisture

Experimental Study of the Pore Structure and Gas Desorption Characteristics of a Low-Rank Coal: Impact of Moisture

Study on the Prediction of Low-Index Coal and Gas Outburst Based on PSO-SVM

Experimental Study on Pore Structure and Gas Desorption Characteristics of a Low Rank Coal: Impact of Moisture

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