Analytical prediction of coal spontaneous combustion tendency: Velocity range with high possibility of self-ignition

Lin, Qi; Wang, Shugang; Liang, Yuntao; Song, Shaowen; Ren, Ting X

doi:10.1016/j.fuproc.2016.09.027

Cited by 52 publications

(21 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This new criterion also allows to rate the temperature of the self-heating hotbed by the amount of condensed liquid. Assuming that all the amount of liquid condensed at the control point was in the form of vapor at a humidity of 100% and using formulas (1), (2) and 3, we obtain a formula for determining the temperature of the heated coal…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Detecting Coal Self-heating by Condensation Aerosol Content in the Air

2019

View full text Add to dashboard Cite

The issues under consideration are spontaneous combustion of coal and the danger of endogenous fires for mining enterprises. The ways of detecting the hotbeds of spontaneous combustion which allow to increase the safety of mining works and to reduce economic damage from endogenous fires are analyzed. The temperature control is demonstrated to be ineffective due to thermal insulation properties of coal, and the gas analysis method - insufficient for detecting the initial stages of coal self-heating. It is proposed to detect the self-heating of coal by the condensation aerosol content formed at the cooling of the air heated in the source. The calculations of the condensation aerosol content in the air depending on the temperature of the coal self-heating spot are given. Dependences determining the temperature of coal self-heating spot, depending on the condensation aerosol content in the air passing through the coal have been obtained. Various sorbents for measuring condensation aerosol content in the air have been studied. The most effective sorbent of water vapor and condensation aerosol is macro-porous silica gel. A device detecting coal self-heating in mines, mine dumps, and coal storages has been developed. Tests in mine conditions proved the effectiveness of the method for detecting coal self-heating.

show abstract

Section: Resultsmentioning

confidence: 99%

“…A number of scientific researches are devoted to the study of spontaneous combustion [2][3][4][5][6][7][8][9]. The results obtained allow predicting the probability of endogenous fires.…”

Section: Introductionmentioning

confidence: 99%

Detecting Coal Self-heating by Condensation Aerosol Content in the Air

2019

View full text Add to dashboard Cite

show abstract

“…There are numerous methods used for early detection of spontaneous combustion in underground coal mines. These include the fuzzy logic method [ 6 , 15 ], monitoring of concentration of gases produced during spontaneous combustion [ [16] , [17] , [18] , [19] , [20] , [21] , [22] ], the electromagnetic radiation technique [ 23 ], temperature measurement [ [24] , [25] , [26] ], numerical modeling [ [27] , [28] , [29] ], statistical analysis [ 30 ], the gray model [ 31 ], the analytical method [ 32 ], remote sensing [ 33 ], and the radon detection method [ 34 ]. Out of these, the most widely used technique in initial prediction of spontaneous combustion and fire status is the gas indices, such as oxides of carbon ratio (CO/CO 2 ), Willet's ratio, Jones and Trickett ratio, Graham's ratio, Young's ratio, and so on.…”

Section: Introductionmentioning

confidence: 99%

Application of Fuzzy Logic for Predicting of Mine Fire in Underground Coal Mine

Danish

Önder

2020

Safety and Health at Work

View full text Add to dashboard Cite

Background Spontaneous combustion of coal is one of the factors which causes direct or indirect gas and dust explosion, mine fire, the release of toxic gases, loss of reserve, and loss of miners' life. To avoid these incidents, the prediction of spontaneous combustion is essential. The safety of miner's in the mining field can be assured if the prediction of a coal fire is carried out at an early stage. Method Adularya Underground Coal Mine which is fully mechanized with longwall mining method was selected as a case study area. The data collected for 2017, by sensors from ten gas monitoring stations were used for the simulation and prediction of a coal fire. In this study, the fuzzy logic model is used because of the uncertainties, nonlinearity, and imprecise variables in the data. For coal fire prediction, CO, O 2 , N 2 , and temperature were used as input variables whereas fire intensity was considered as the output variable.The simulation of the model is carried out using the Mamdani inference system and run by the Fuzzy Logic Toolbox in MATLAB. Results The results showed that the fuzzy logic system is more reliable in predicting fire intensity with respect to uncertainties and nonlinearities of the data. It also indicates that the 1409 and 610/2B gas station points have a greater chance of causing spontaneous combustion and therefore require a precautional measure. Conclusion The fuzzy logic model shows higher probability in predicting fire intensity with the simultaneous application of many variables compared with Graham's index.

show abstract

“…The accession of oxygen occurs with the emission of heat, which under certain conditions can cause the development of spontaneous combustion process. Considering that spontaneous combustion is a source of toxic gases, they can initiate explosions of a combustible gas; many studies have been devoted to the research of this process [1][2][3][4][5][6]. The danger of emission of various gases [7,8] and the dependence of the process on various factors [3,[9][10][11][12] were estimated.…”

Section: Introductionmentioning

confidence: 99%

Increasing Spontaneous Combustion Risk While Reducing the Coal Particle Size

et al. 2019

View full text Add to dashboard Cite

Extraction, storage and transportation of coal are complicated by the danger of spontaneous combustion centers due to toxic gases emission. At various technological processes, the formation of clusters consisting of coal particles of various sizes is possible. In the course of the research, the influence of the size of coal particles on the danger of spontaneous combustion of oxidizing material clusters was estimated. The studies of coal chemical activity have shown that for most seams of Kuzbass mines, the amount of absorbed oxygen increases significantly with decreasing particle size. Coal dust can be more active than coal in 3-8 times. For some seams, the coal breakage has almost no effect on its chemical activity in relation to oxygen. It is determined that the duration of incubation period of spontaneous combustion also varies depending on the size of particles forming the coal cluster. For the appearance of spontaneous combustion centers, the size of coal dust clusters may be in 2– 4 times smaller than for coal. In order to increase the safety of work for all the seams it is necessary to study the chemical activity in relation to oxygen, the tendency to spontaneous combustion, and the duration of the incubation period not only for coal samples, but also for coal dust.

show abstract

Analytical prediction of coal spontaneous combustion tendency: Velocity range with high possibility of self-ignition

Cited by 52 publications

References 47 publications

Detecting Coal Self-heating by Condensation Aerosol Content in the Air

Detecting Coal Self-heating by Condensation Aerosol Content in the Air

Application of Fuzzy Logic for Predicting of Mine Fire in Underground Coal Mine

Increasing Spontaneous Combustion Risk While Reducing the Coal Particle Size

Contact Info

Product

Resources

About