A new approach for selecting best development face ventilation mode based on G1-coefficient of variation method

Zhi-yong Zhou , Mehmet Kizil , Zhong-wei Chen , Jian-hong Chen

Journal of Central South University ›› 2018, Vol. 25 ›› Issue (10) : 2462 -2471.

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Journal of Central South University ›› 2018, Vol. 25 ›› Issue (10) : 2462 -2471. DOI: 10.1007/s11771-018-3929-y
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A new approach for selecting best development face ventilation mode based on G1-coefficient of variation method

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Abstract

The current popular methods for decision making and project optimisation in mine ventilation contain a number of deficiencies as they are solely based on either subjective knowledge or objective information. This paper presents a new approach to rank the alternatives by G1-coefficient of variation method. The focus of this approach is the use of the combination weighing, which is able to compensate for the deficiencies in the method of evaluation index single weighing. In the case study, an appropriate evaluation index system was established to determine the evaluation value of each ventilation mode. Then the proposed approach was used to select the best development face ventilation mode. The result shows that the proposed approach is able to rank the alternative development face ventilation mode reasonably, the combination weighing method had the advantages of both subjective and objective weighing methods in that it took into consideration of both the experience and wisdom of experts, and the new changes in objective conditions. This approach provides a more reasonable and reliable procedure to analyse and evaluate different ventilation modes.

Keywords

development face ventilation / G1 method / coefficient of variation method / comprehensive evaluation / optimization

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Zhi-yong Zhou, Mehmet Kizil, Zhong-wei Chen, Jian-hong Chen. A new approach for selecting best development face ventilation mode based on G1-coefficient of variation method. Journal of Central South University, 2018, 25(10): 2462-2471 DOI:10.1007/s11771-018-3929-y

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References

[1]

RenT, WangZ-w, GraemeCooper. CFD modelling of ventilation and dust flow behaviour above an underground bin and the design of an innovative dust mitigation system [J]. Tunnelling and Underground Space Technology, 2014, 41: 241-254

[2]

ZhangG, LiL-x, JiH-g, XiaoK-r, YinG-g, LiSong. In situ investigation of gaseous pollution in the ramp of an underground gold mine [J]. Indoor and Built Environment, 2014, 23(2): 293-298

[3]

ShahnaF G, BahramiA, FarasatiF. Application of local exhaust ventilation system and integrated collectors for control of air pollutants in mining company [J]. Industrial Health, 2012, 50: 450-457

[4]

ZhangY, WanZ-j, GuB, ZhouC-b, ChengJ-yi. Unsteady temperature field of surrounding rock mass in high geothermal roadway during mechanical ventilation [J]. Journal of Central South University, 2017, 24(2): 374-381

[5]

ChengJ, ZhouF, YangS. A reliability allocation model and application in designing a mine ventilation system [J]. Iranian Journal of Science and Technology-Transactions of Civil Engineering, 2014, 38(C1): 61-73

[6]

KurniaJ C, SasmitoA P, MujumdarA S. CFD simulation of methane dispersion and innovative methane management in underground mining faces [J]. Applied Mathematical Modelling, 2014, 38: 3467-3484

[7]

ChengJ-w, YangS-qiang. Data mining applications in evaluating mine ventilation system [J]. Safety Science, 2012, 50: 918-922

[8]

MalekiB, MozaffariE. Comparative study of the iterative numerical methods used in mine ventilation networks [J]. International Journal of Advanced Computer Science and Applications, 2016, 7(6): 356-362

[9]

BascomptaM, CastanonA M, SanmiquelL, OlivaJ. A GIS-based approach: Influence of the ventilation layout to the environmental conditions in an underground mine [J]. Journal of Environmental Management, 2016, 182: 525-530

[10]

MirhedayatianM J, JelodarM, AdnaniS, AkbarnejadM, FarzipoorS R. A new approach for prioritization in fuzzy AHP with an application for selecting the best tunnel ventilation system [J]. The International Journal of Advanced Manufacturing Technology, 2013, 68: 2589-2599

[11]

SaZ-y, WangY, ZhangH-ning. Optimization of mine ventilation system based on grey system theory [C]. 7th International Symposium on Safety Science and Technology, 201016831687

[12]

WuL-y, YangY-zhong. Improved grey correlative method for risk assessment on mine ventilation system [C]. 4th International Conference on Mechanical and Electrical Technology, 201226292633

[13]

WangH-deStudy on reliability theory and method for mine ventilation system based on artificial neural network [D], 2004, Fuxing, Liaoning Technical University

[14]

KaracanC Ö. Development and application of reservoir models and artificial neural networks for optimizing ventilation air requirements in development mining of coal seams [J]. International Journal of Coal Geology, 2007, 72: 221-239

[15]

KozyrevS A, OsintsevaA V. Optimizing arrangement of air distribution controllers in mine ventilation system [J]. Journal of Mining Science, 2012, 48(5): 896-903

[16]

DengL-j, LiuJian. New approach for ventilation network graph drawing based on Sugiyama method and GA-SA algorithm [J]. Computer Modelling and New Technologies, 2014, 18(8): 45-49

[17]

ShriwasM, CalizayaF. Application of genetic algorithms for solving multiple fan ventilation networks [C]. Application of Computers and Operations Research in the Mineral Industry-Proceedings of the 37th International Symposium, 2015488498

[18]

ZhangMei. The research of speed control system based on intelligent PID controller to mine local ventilator [C]. 2011 Second International Conference on Mechanic Automation and Control Engineering, 2011858861

[19]

LowndesI S, FogartyT, YangZ Y. The application of genetic algorithms to optimise the performance of a mine ventilation network: The influence of coding method and population size [J]. Soft Computing, 2005, 9: 493-506

[20]

ChengJ-wei. Assessment of mine ventilation system reliability using random simulation method [J]. Environmental Engineering and Management Journal, 2016, 15(4): 841-850

[21]

XuG, HuangJ-x, NieB-s, ChalmersD, YangZ-ming. Calibration of mine ventilation network models using the non-linear optimization algorithm [J]. Energies, 2018, 11(1): 31

[22]

MengB, ChiG-tai. New combined weighting model based on maximizing the difference in evaluation results and its application [J]. Mathematical Problems in Engineering, 2015

[23]

GuoY-junComprehensive evaluation theory and method [M], 2002, Beijing, Science Press

[24]

ZhuangP, LiY-xi. Appraisement model and empirical study of enterprise investment risk based on G1-coefficient of variation [J]. Soft Science, 2011, 2510107-112

[25]

GongJ, HuN-l, CuiX, WangX-dong. Optimization of drifting ventilation method for high-altitude mine [J]. Science & Technology Review, 2015, 33(4): 56-60

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