Coal spontaneous combustion prediction in gob using chaos analysis on gas indicators from upper tunnel

Hu, Xiangming; Yang, Shengqiang; Zhou, Xiuhong; Yu, Zhiwei; Hu, Chunya

doi:10.1016/j.jngse.2015.06.047

Cited by 51 publications

(22 citation statements)

References 13 publications

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“…Accidents caused by the spontaneous combustion of coal could be severe, and the resulting losses of high-quality coal are financially significant. In view of the serious harm caused by the spontaneous combustion of coal, scholars worldwide have extensively studied the mechanisms of this spontaneous combustion (Chou, 2012;Dacka SW et al, 1984;Deng et al, 2015a;Hu et al, 2015;Ma et al, 2019;Qi et al, 2018;Shen and Zeng, 2021;Zhao et al, 2021a;Zhao et al, 2021b;Zhou and Tang, 2018;Zhu et al, 2019). Sulfur is a harmful element in coal, and it not only produces hydrogen sulfide (H 2 S) and sulfur dioxide (SO 2 ) in the combustion process, causing environmental pollution, but is also important in restricting the utilization of coking coal resources (Li et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Effects of organic sulfur on oxidation spontaneous combustion characteristics of coking coal

Gao

Jia

Qin

et al. 2021

Energy Exploration & Exploitation

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Research on the spontaneous combustion of coal caused by sulfur has always been focused on pyrite in coal but has rarely considered the influence of organic sulfur. In this paper, coal samples, rather than model compounds, were used to study the influence of organic sulfur content in coal on its spontaneous combustion process. The results of X-ray photoelectron spectroscopy and thermogravimetry, differential scanning calorimetry, and mass spectrometry indicate that organic sulfur in Shuiyu clean coal exists in forms of mercaptan, thioether, sulfone (sulfoxide), and thiophene. With the decrease of organic sulfur content, the characteristic temperature points and the peak values of the exothermic curves in the process of coal oxidation spontaneous combustion all shifted toward higher temperatures. The ignition activation energy of coal also increased, and the initial and peak gas evolution temperatures of the oxidation products shifted toward higher temperatures. These findings suggest that the reduction of organic sulfur content can inhibit the oxidation process and spontaneous combustion tendency of coal. This effectively reveals the mechanism of the spontaneous combustion of coal and is of great significance to future studies in this field.

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Section: Introductionmentioning

confidence: 99%

Effects of organic sulfur on oxidation spontaneous combustion characteristics of coking coal

Gao

Jia

Qin

et al. 2021

Energy Exploration & Exploitation

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“…Explosions due to gas, coal dust, and water coal gas and smoke poisoning cause interruptions in operations and may lead to casualties [1][2][3]. Spontaneous coal combustion is a major global disaster that leads to serious environmental pollution ( Figure 1) [4][5][6]. In particular, the risk of spontaneous combustion of the gob in underground coal mines is greater [7,8].…”

Section: Introductionmentioning

confidence: 99%

Experimental Study and Application of LASC Foamed Concrete to Create Airtight Walls in Coal Mines

Zhang

Wang

Deng

et al. 2020

Advances in Materials Science and Engineering

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If an airtight wall in a coal mine leaks air, it may cause spontaneous combustion of residual coal in the gob and even cause a full-blown fire or gas explosion. In this study, we developed a new type of foamed concrete, low-alkalinity sulphoaluminate cement (LASC), to control air leakage. The performance of filling materials that were prepared by adding various dosages of foam to LASC was studied. The longer the curing period for the foam filling material of LASC, the better the crystallinity of the hydrated product. With an increasing foam dosage, the initial setting time gradually extends while the fluidity of the foam slurry decreases. The bubble rate of the filling material increases and the density decreases with increasing foam dosage. The compressive strength of the LASC filling material decreases with increasing foam dosage and increases with increasing curing time. In the LASC filling materials, the optimal volume ratio of foam dosage to gel slurry is 2. The crystallinity, initial gel time, and compressive strength of the LASC foaming materials are better than those of ordinary Portland cement (OPC) foaming materials. When the crossheading is filled with LASC foam cement, the deformation of the surrounding rock is less than 19 cm, and the air leakage prevention is better than that achieved with loess and fly-ash-cement foam. Thus, the proposed LASC foam material can be applied to the filling of the crossheading to efficiently prevent leakage in underground coal mines.

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“…The on‐site detection method estimates the tendency for spontaneous combustion, mainly through measuring and analyzing the temperature and the gas concentration inside the coal pile. [ 21–24 ] This method has a certain lag and cannot accurately predict the spontaneous combustion of coal. The mathematical model can predict in advance the spontaneous combustion tendency by summarizing the law of coal spontaneous combustion, including traditional polynomial regression and modelling prediction, such as back‐propagation artificial neural network (BPNN), random forest (RF) approach, DSC inflection point (DSCIP), and so on.…”

Section: Introductionmentioning

confidence: 99%

Prediction of BP neural network and preliminary application for suppression of low‐temperature oxidation of coal stockpiles by pulverized coal covering

Wan

Chu

et al. 2020

Can J Chem Eng

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We have developed a new method to suppress spontaneous combustion of coal piles by covering the surface of coal piles with pulverized coal. Experimental studies of three type of coal samples from China (YJL, CYW, and SW) with particle size ratio of 10:1 were performed to investigate the low-temperature oxidation of coal pillars. In this work, we have also demonstrated that the distributions of oxygen concentration, the temperature field, as well as the spontaneous combustion of three typical Chinese coal samples can be predicted accurately using back-propagation neural network (BPNN) by MATLAB. Pearson correlation analysis showed that temperature and oxygen concentration highly depend on the ratio of pulverized coal thickness to coal piles thickness, activation energy, void ratio, wind speed, and low-temperature oxidation time. Three-layer BPNN models with five input factors were developed to predict the low-temperature oxidation process under pulverized coal. The prediction data of BPNN are fitting better with our experimental data, which confirms that BPNN modelling can accurately predict the low temperature oxidation process of coal.

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Coal spontaneous combustion prediction in gob using chaos analysis on gas indicators from upper tunnel

Cited by 51 publications

References 13 publications

Effects of organic sulfur on oxidation spontaneous combustion characteristics of coking coal

Effects of organic sulfur on oxidation spontaneous combustion characteristics of coking coal

Experimental Study and Application of LASC Foamed Concrete to Create Airtight Walls in Coal Mines

Prediction of BP neural network and preliminary application for suppression of low‐temperature oxidation of coal stockpiles by pulverized coal covering

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