Calibration of Mine Ventilation Network Models Using the Non-Linear Optimization Algorithm

Guang Xu, Jinxin Huang, Baisheng Nie, Duncan Chalmers and Zhuoming Yang
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Guang Xu: Department of Mining Engineering and Metallurgical Engineering, Western Australian School of Mines, Curtin University, Kalgoorlie 6430, Australia
Jinxin Huang: Department of Mining Engineering and Metallurgical Engineering, Western Australian School of Mines, Curtin University, Kalgoorlie 6430, Australia
Baisheng Nie: School of Resources and Safety Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
Duncan Chalmers: School of Mining Engineering, University of New South Wales, Sydney 2052, Australia
Zhuoming Yang: School of Resources and Safety Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China

Energies, 2017, vol. 11, issue 1, 1-9

Abstract: Effective ventilation planning is vital to underground mining. To ensure stable operation of the ventilation system and to avoid airflow disorder, mine ventilation network (MVN) models have been widely used in simulating and optimizing the mine ventilation system. However, one of the challenges for MVN model simulation is that the simulated airflow distribution results do not match the measured data. To solve this problem, a simple and effective calibration method is proposed based on the non-linear optimization algorithm. The calibrated model not only makes simulated airflow distribution results in accordance with the on-site measured data, but also controls the errors of other parameters within a minimum range. The proposed method was then applied to calibrate an MVN model in a real case, which is built based on ventilation survey results and Ventsim software. Finally, airflow simulation experiments are carried out respectively using data before and after calibration, whose results were compared and analyzed. This showed that the simulated airflows in the calibrated model agreed much better to the ventilation survey data, which verifies the effectiveness of calibrating method.

Keywords: mine ventilation network; model calibration; non-linear optimization; Ventsim (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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