Assessment of Uncertainty Performance of a Mine Fans by Ventilation Network Design
Mithilesh Kumar Rajak1, Kaushik Dey2
1Mithilesh Kumar Rajak*, Department of Mining Engineering, Amet University, Chennai, India.
2Dr. Kaushik Dey, Department of Mining Engineering, IIT Kharagpur, West Bengal, India.
Manuscript received on November 11, 2019. | Revised Manuscript received on November 20 2019. | Manuscript published on 30 November, 2019. | PP: 11501-11507 | Volume-8 Issue-4, November 2019. | Retrieval Number: D4301118419/2019©BEIESP | DOI: 10.35940/ijrte.D4301.118419
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Abstract: The objective of ventilation network system to provide the desire quantity to fair flows throughout the mine such the workers cant work underground in at safe and healthy environment at the level specified by the mining regulations. In coal mines the ventilation network system stat greater impact on safety and production. The selection stof mine fan and air quantity calculation at different working places are generally deci-ded by solving the ventilation network using iterative Hardy Cross method In this tresearch an approach was tad opted to simulating the ventilation network considering the air way sresistances a stuncer taintvari ables. At Monte-Carlo simulation-based approach was followed to generate trandomtset of resistance value st from the distribution functions of the airway stresistances. The VENTSIM software was used to solve the Hardy Cross method for ventilation network simulation tusingonese of random resistance values. The Monte Carlo simulation based approach the lps to tanaly sis the uncertainty to ftair quantity at specific working face sast well as total quantity required for ventilating the mine. The major focus of the the st s towards the quantity of air in the working face generated by the mine main fan and the risk in volve with the selection of mine main fan for at coal mine. The methodology for the ventilation network design proposed in this the sis was applied in a under ground coal mine in Eastern part of India. The airway stre sistance starecal culated by measuring the value stat different place stint same airways. The mean and standard deviation used fort Monte-Carlo simulation assuming the distribution is Gaussian. A total number of 71 airways are simulated in the case study mine. A risk analysis of quantity of air reaching at face was performed at wo working faces by generating 200 realizations The result sin this the sis was validated my measuring quantity at different measuring station in this mine.
Keywords: Mine Fan, Ventiltion, Ventilation Network, Air Quantity, Hardy-Cross Method,
Scope of the Article: Measurement & Performance Analysis.