Elimination mechanism of coal and gas outburst based on geo‑dynamic system with stress–damage–seepage interactions

Coal and gas outburst is a complex dynamic disaster during coal underground mining.Revealing the disaster mechanism is of great signifcance for accurate prediction and prevention of coal and gas outburst.The geo-dynamic system of coal and gas outburst is proposed.The framework of geo-dynamic system is composed of gassy coal mass,geological dynamic environment and mining disturbance.Equations of stress–damage–seepage interaction for gassy coal mass is constructed to resolve the outburst elimination process by gas extraction with boreholes through layer in foor roadway.The results show the occurrence of outburst is divided into the evolution process of gestation,formation,development and termination of geo-dynamic system.The scale range of outburst occurrence is determined,which provides a spatial basis for the prevention and control of outburst.The formation criterion and instability criterion of coal and gas outburst are established.The formation criterion F1 is defned as the scale of the geo-dynamic system,and the instability criterion F2 is defned as the scale of the outburst geo-body.According to the geo-dynamic system,the elimination mechanism of coal and gas outburst—‘unloading+depressurization’is established,and the gas extraction by boreholes through layer in foor roadway for outburst elimination is given.For the research case,when the gas extraction is 120 days,the gas pressure of the coal seam is reduced to below 0.4 MPa,and the outburst danger is eliminated efectively.

Highly reinforce the interface stability using 2-Phenyl-1H-imidazole-1-sulfonate electrolyte additive to enhance the high temperature performance of LiNi_(0.8)Co_(0.1)Mn_(0.1)O_(2)/graphite batteries

This work develops 2-Phenyl-1H-imidazole-1-sulfonate(PHIS)as a multi-functional electrolyte additive for H2O/HF scavenging and film formation to improve the high temperature performance of LiNi_(0.8)Co_(0.1)Mn_(0.1)O_(2)/graphite batteries.After 450 cycles at room temperature(25℃),the discharge capacity retentions of batteries with blank and PHIS-containing electrolyte are 56.03%and 94.92%respectively.After 230 cycles at high temperatures(45℃),their values are 75.30%and 88.38%respectively.The enhanced electrochemical performance of the batteries with PHIS-containing electrolyte is supported by the spectroscopic characterization and theoretical calculations.It is demonstrated that this PHIS electrolyte additive can facilitate the construction of the electrode interface films,remove the H2O/HF in the electrolyte,and improve the electrochemical performance of the batteries.This work not only develops a sulfonate-based electrolyte but also can stimulate new ideas of functional additives to improve the battery performance.

Reasonable start time of carbon dioxide injection in enhanced coalbed methane recovery involving thermal-hydraulic-mechanical couplings

Injection of gas (CO_(2)) into coal seams is an effective method to benefit from both CO_(2) geological storage and coalbed methane recovery. Based on the dual pore structure of coal mass, and the Weibull distribution of fracture permeability, a menmal-hydraulic-mechanical (THM) coupling mathematical model is proposed involving the non-isothermal adsorption of binary gases, dynamic gas diffusion between matrix and fractures, multiphase seepage, coal deformation, heat conduction and heat convection. This mathematical model is applied to study the process of CO_(2)-enhanced coalbed methane recovery (CO_(2)-ECBM). Results show that the CH4 content of CO_(2)-ECBM in coal seam decreases significantly when compared with that of regular drainage, and decreases rapidly in the early stage but slowly in the later stage. Coal seam permeability evolution is triggered by changes in gas adsorption/desorption, temperature and effective stress. For regular drainage, the early permeability shows a decreasing trend dominated by the increase of effective stress, while the later permeability shows an increasing trend dominated by the CH4 desorption caused shrinkage of coal matrix. For CO_(2)-ECBM, the permeability in coal seam generally shows a downward trend due to both matrix swelling induced by gas adsorption and thermal expansion, particularly near injection well. There appears an increased and delayed peak production rate of CH4. The CH4 production rate of CO_(2)-ECBM is always higher than that of regular drainage. The CH4 cumulative production and CO_(2) cumulative storage linearly increase with time, and the CH4 cumulative production of CO_(2)-ECBM increased by 39.2% in the duration of 5000 d compared with regular drainage. Reasonable CO_(2) injection starting time can overcome the issue of early CO_(2) breakthrough and ineffective increase of CH4 production. In the studied case, the optimal injection starting time is 2500 d. Compared with the simultaneous CH4 extraction and CO_(2) injection, the CH4 cumulative production of optimal time has increased by 30.1%. The research provides a reference for determining the reasonable CO_(2) injection time under similar conditions.

Coal and gas outburst prediction model based on principal component analysis and improved support vector machine

In order to predict the coal outburst risk quickly and accurately,a PCA-FA-SVM based coal and gas outburst risk prediction model was designed.Principal component analysis(PCA)was used to pre-process the original data samples,extract the principal components of the samples,use firefly algorithm(FA)to improve the support vector machine model,and compare and analyze the prediction results of PCA-FA-SVM model with BP model,FA-SVM model,FA-BP model and SVM model.Accuracy rate,recall rate,Macro-F1 and model prediction time were used as evaluation indexes.The results show that:Principal component analysis improves the prediction efficiency and accuracy of FA-SVM model.The accuracy rate of PCA-FA-SVM model predicting coal and gas outburst risk is 0.962,recall rate is 0.955,Macro-F1 is 0.957,and model prediction time is 0.312s.Compared with other models,The comprehensive performance of PCA-FA-SVM model is better.