Effects of N and S Functionalities on Binary Gas Co-adsorption on a Coal Macromolecule

Fan, Chunhua; Li, Sheng; Luo, Ming‐Xing; Zhou, Lijun; Zhang, Haohao; Yang, Zhenhua

doi:10.1021/acs.energyfuels.8b04410

Cited by 26 publications

(16 citation statements)

References 53 publications

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“…where μ is a random number in the [−1, 1], A υ is the average of the pulse loudness of all bats at the current iteration number, and M is the dimension of search space. (5) In the iteration process, if the fitness F(S qM ) of bat q is superior to the fitness F(S * ) of optimal bat S * , the basic parameters of bat q should be updated: (6) If the iteration results satisfied the search termination conditions, the optimal solution was S * , the corresponding fitness function was F(S * ), and the corresponding parameters w and b were the optimal parameter values. Otherwise, go back to step (3) and continue iterating through the search until the termination condition was met.…”

Section: Bat Algorithm Optimizing Extreme Learning Machinementioning

confidence: 99%

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Prediction of Residual Gas Content during Coal Roadway Tunneling Based on Drilling Cuttings Indices and BA‐ELM Algorithm

Yang

Hong-wei

Sheng

et al. 2020

Advances in Civil Engineering

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In order to predict the residual gas content in coal seam in front of roadway advancing face accurately and rapidly, an improved prediction method based on both drilling cuttings indices and bat algorithm optimizing extreme learning machine (BA-ELM) was proposed. The test indices of outburst prevention measures (drilling cuttings indices, residual gas content in coal seam) during roadway advancing in Yuecheng coal mine were first analyzed. Then, the correlation between drilling cuttings indices and residual gas content was established, as well as the neural network prediction model based on BA-ELM. Finally, the prediction result of the proposed method was compared with that of back-propagation (BP), support vector machine (SVM), and extreme learning machine (ELM) to verify the accuracy. The results show that the average absolute error, the average absolute percentage error, and the determination coefficient of the proposed prediction method of residual gas content in coal seam are 0.069, 0.012, and 0.981, respectively. This method has higher accuracy than other methods and can effectively reveal the nonlinear relationship between drilling cuttings indices and residual gas content. It has prospective application in the prediction of residual gas content in coal seam.

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Section: Bat Algorithm Optimizing Extreme Learning Machinementioning

confidence: 99%

“…With depletion of shallow coal resources, the mining depth of coal mines in China increases. e coupling effect of great in situ stress and high gas pressure in deep coal seam increases the risk of gas outbursts [1][2][3][4][5]. e residual gas content is an important parameter for gas outburst prediction.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Residual Gas Content during Coal Roadway Tunneling Based on Drilling Cuttings Indices and BA‐ELM Algorithm

Yang

Hong-wei

Sheng

et al. 2020

Advances in Civil Engineering

Self Cite

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“…The presplitting blasting method has high risks during the implementation process, which is confronted to many governing policies and laws of China [15,16]. Gas injection will increase the content of injected gas (CO 2 or N 2 ), which may lead to new hazards after eliminating gas (methane) outburst risk [17][18][19][20]. This method has little utilization by now [21,22].…”

Section: Introductionmentioning

confidence: 99%

Investigation of Large-Diameter Borehole for Enhancing Permeability and Gas Extraction in Soft Coal Seam

Wang¹,

Yan

Ren

et al. 2020

Geofluids

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The efficiency of gas extraction from the soft coal seam with ultralow permeability is low. Gas extraction with large-diameter borehole is proposed to deplete gas content for preventing gas outburst disaster in this study. The fractures around the large borehole will enhance the permeability in the damage area to promote gas extraction. We established a damage-stress-seepage coupling model for large-diameter borehole gas extraction in soft coal seam. This mathematical model contains governing equations of gases sorption and transport, coal deformation, and damage, reflecting the coupling responses between gas and coal seam. The model is solved by the finite element method to simulate the gas drainage large-diameter borehole through roadway. Distributions of elastic modulus, damage area, and maximum principal stress in soft coal seam with different borehole diameters including 94 mm, 133 mm, 200 mm, and 300 mm are analyzed. The gas pressure, gas content, and effective extraction area in soft coal seam are discussed. Results show that the shear failure zone appears around the large-diameter borehole, and its permeability rises sharply. This opens up the gas transport channel and is conducive to the rapid extraction. It is confirmed that gas extraction using large-diameter borehole (300 mm) can greatly improve the efficiency of the gas preextraction in soft coal seam by increasing gas extraction rate. These provide a foundation for guiding the operation of gas extraction with large borehole from the soft coal seam in the field.

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“…Wang et al [17] investigated key mining technologies and equipment of LMTCCM in extra-thick coal seams and successfully applied to Tashan coal mine. By building numerical model and field measurement, Si et al [18] and Fan et al [19] determined the gas dynamics characteristics in multilevel longwall top coal caving of extra-thick coal seams.…”

Section: Introductionmentioning

confidence: 99%

The Key Stratum Structure Morphology of Longwall Mechanized Top Coal Caving Mining in Extra‐Thick Coal Seams: A Typical Case Study

et al. 2020

Advances in Civil Engineering

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Longwall mechanized top coal caving mining (LMTCCM) in extra-thick coal seams has its own characteristics. The law of mining pressure and overlying strata failure height in extra-thick coal seams are much larger than those of medium-thick and thick coal seams. The key stratum structure morphology also has an important influence on the law of overlying strata movement and stability of surrounding rock. Based on the engineering geological conditions, this paper used the method of theoretical analysis and numerical simulation to study the key stratum structure morphology of LMTCCM in extra-thick coal seams. The results show that under the condition of LMTCCM in extra-thick coal seams, the key stratum forms the structure of low cantilever beam and high hinged rock beam. With the increase of coal seam thickness, the breaking position of cantilever beam is closer to the coal wall. Through theoretical calculation, it is obtained that the breaking length of cantilever beam is 31.5 m and the breaking position of cantilever beam is 15.4 m away from coal wall. With the increase of cycle, key strata will undergo the evolution law from the generation of longitudinal cracks to the hinged structure and then to the cantilever beam structure. The breakage of key strata will cause the expansion of longitudinal cracks and the overall synchronous movement of overlying strata. With the increase of coal seam thickness, the distribution of longitudinal cracks will gradually transfer from the upper part of goaf to the deep part of coal body in space and increase in quantity. This research is of great significance for improving the stability of overlying strata and ensuring the safe and efficient mining of extra-thick coal seams.

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Effects of N and S Functionalities on Binary Gas Co-adsorption on a Coal Macromolecule

Cited by 26 publications

References 53 publications

Prediction of Residual Gas Content during Coal Roadway Tunneling Based on Drilling Cuttings Indices and BA‐ELM Algorithm

Prediction of Residual Gas Content during Coal Roadway Tunneling Based on Drilling Cuttings Indices and BA‐ELM Algorithm

Investigation of Large-Diameter Borehole for Enhancing Permeability and Gas Extraction in Soft Coal Seam

The Key Stratum Structure Morphology of Longwall Mechanized Top Coal Caving Mining in Extra‐Thick Coal Seams: A Typical Case Study

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