Correlating variability of the leakage characteristics with the hydraulic performance of an auxiliary ventilation system

Abstract Ventilation is one of the key factors in controlling underground working environment by providing sufficient amount of fresh air for breathing, dispersing harmful gasses and dust and to some extent for heating/cooling. Insufficient airflow is dangerous for the working face and can lead to fatalities. Duct leakage is the most common reason for the insufficient fresh air in underground working and has been the subject of many studies in the literature. However, the main focus has been on ascertaining its impact on the ventilation requirements of the underground environment. This study aims to identify key variables associated with duct leakage that significantly impacts the power consumption levels of auxiliary fans which form an integral part of the underground ventilation system. A three-dimensional Computational Fluid Dynamics (CFD) modeling approach is undertaken in conjunction with Monte Carlo simulations and multiple regression analysis to quantify the effect of duct leakage on the fan operating point and discharge flow rate towards the working face. Various cases involving the positioning, orientation, and size of the rupture in the ventilation duct are simulated, and their respective effects on fan operating point and power levels are determined. Results indicate that the operating point of a fan for ventilation ducts is strongly correlated with the position and size of the rupture, resulting in reduced delivery of ventilation air towards the working face for different levels of fan power consumption.

[1]  Jonq-Keh Lee,et al.  Effects of stopping leakage on coal mine ventilation systems , 1984 .

[2]  David Hargreaves,et al.  The computational modeling of the ventilation flows within a rapid development drivage , 2007 .

[3]  Lluís Sanmiquel Pera,et al.  Ventilation management system for underground environments , 2015 .

[4]  J. H. Zar,et al.  Significance Testing of the Spearman Rank Correlation Coefficient , 1972 .

[5]  Kyuro Sasaki,et al.  Predicting gas dispersion in large scale underground ventilation: A particle tracking approach , 2016 .

[6]  George Keith Batchelor,et al.  An Introduction to Fluid Dynamics. , 1969 .

[7]  C. Méndez,et al.  Numerical and experimental analysis of different ventilation systems in deep mines , 2006 .

[8]  Richard A. Johnson,et al.  Applied Multivariate Statistical Analysis , 1983 .

[9]  Mustafa Önder,et al.  Statistical model for the volume rate reaching the end of ventilation duct , 2008 .

[10]  Targo Kalamees,et al.  Air tightness and air leakages of new lightweight single-family detached houses in Estonia , 2007 .

[11]  Javier Toraño,et al.  Auxiliary ventilation in mining roadways driven with roadheaders: Validated CFD modelling of dust behaviour , 2011 .

[12]  Targo Kalamees,et al.  Air leakage levels in timber frame building envelope joints , 2017 .

[13]  Arun S. Mujumdar,et al.  Computational evaluation of thermal management strategies in an underground mine , 2015 .

[14]  Arun S. Mujumdar,et al.  CFD simulation of methane dispersion and innovative methane management in underground mining faces , 2014 .

[15]  I. Diego,et al.  Influence of the pile shape on wind erosion CFD emission simulation , 2007 .

[16]  R. Whalley,et al.  The dynamics of cyclic ventilation systems , 2011 .

[17]  Targo Kalamees,et al.  Building leakage, infiltration, and energy performance analyses for Finnish detached houses , 2009 .

[18]  Steven J Schatzel,et al.  A study of leakage rates through mine seals in underground coal mines , 2016, International journal of mining, reclamation and environment.

[19]  Gary Auld,et al.  An estimation of fan performance for leaky ventilation ducts , 2004 .

[20]  Vittorio Verda,et al.  Calculation and design of tunnel ventilation systems using a two- scale modelling Approach , 2009 .

[21]  Monika Woloszyn,et al.  Multizone air leakage measurements and interactions with ventilation flows in low-energy homes , 2016 .

[22]  Baris Ozerdem,et al.  Air leakage measurement and analysis in duct systems , 2006 .

[23]  Mustafa Önder,et al.  The influence of ventilation variables on the volume rate of airflow delivered to the face of long drivages , 2006 .

[24]  Javier Toraño,et al.  Conventional and numerical models of blasting gas behaviour in auxiliary ventilation of mining headings , 2013 .

[25]  Hua Ge,et al.  Experimental and numerical investigations of the effects of air leakage on temperature and moisture fields in porous insulation , 2015 .

[26]  Arun S. Mujumdar,et al.  Simulation of a novel intermittent ventilation system for underground mines , 2014 .

[27]  Kiyoshi Yamaoka,et al.  Application of Akaike's information criterion (AIC) in the evaluation of linear pharmacokinetic equations , 1978, Journal of Pharmacokinetics and Biopharmaceutics.

[28]  Malcolm J. McPherson,et al.  Subsurface Ventilation and Environmental Engineering , 1993 .

[29]  J. Hair.  Multivariate data analysis , 1972 .

[30]  Arun S. Mujumdar,et al.  Dust dispersion and management in underground mining faces , 2014 .

[31]  R. O’Brien,et al.  A Caution Regarding Rules of Thumb for Variance Inflation Factors , 2007 .

[32]  Arun S. Mujumdar,et al.  Some approaches to improve ventilation system in underground coal mines environment – A computational fluid dynamic study , 2013 .

[33]  Sreenidhi Krishnamoorthy,et al.  Impacts of duct leakage on central outdoor-air conditioning for commercial-building VAV systems , 2016 .

[34]  John D. Hunter,et al.  Matplotlib: A 2D Graphics Environment , 2007, Computing in Science & Engineering.