Remote Characterization of Ventilation Systems using Tracer Gas and CFD in an Underground Mine


Following an unexpected event in an underground mine, it is important to know the state of the mine immediately, in order to manage the situation effectively. Especially when part or the whole mine is inaccessible, remotely and quickly ascertaining the ventilation status is essential to mine personnel and rescue teams for making effective decisions. This study developed a methodology that combines tracer gas and CFD modeling to remotely analyze underground mine ventilation systems. The study was conducted in an underground mine with four different ventilation scenarios created intentionally for this study to simulate different ventilation damage scenarios. CFD models were built to simulate these ventilation scenarios and compared with the field experimental data to identify which scenarios had actually happened. The CFD model was also used to optimize tracer test parameters, guaranteeing that the status of a ventilation system can be identified more rapidly in an emergency situation. This work demonstrated that general determination of changes to a mine ventilation system is achievable through examination of tracer gas profiles and CFD modeling. Additionally, limitations of this approach are identified and discussed.


Mining Engineering


This publication was developed under Contract No. 200-2009-31933, awarded by the National Institute for Occupational Safety and Health (NIOSH). The findings and conclusions in this report are those of the authors and do not reflect the official policies of the Department of Health and Human Services, nor does the mention of trade names, commercial practices, or organizations imply endorsement by the U.S. Government.

Keywords and Phrases

Gas chromatography; Gases; Mine ventilation; Ventilation; CFD modeling; Emergency situation; Experimental data; Mine ventilation systems; Tracer gas; Underground mine ventilation; Unexpected events; Ventilation systems; Mine rescue; Air conditioning; Airflow; Article; Computational fluid dynamics; Emergency; Gas; Human; Mining; Remote sensing; Safety; Sampling; Simulation; Tracer gas; Underground mine

International Standard Serial Number (ISSN)


Document Type

Article - Journal

Document Version


File Type





© 2015 Elsevier, All rights reserved.

Publication Date

01 Apr 2015