Study on Detection Location of Average Gas Concentration in a Large Section Tunnel Based on Numerical Simulation - multiple Regression
(1. School of Resource & Environmental and Safety Engineering, Hunan University of Science and Technology, Xiangtan 411201;2.Work Safety Key Lab on Prevention and Control of Gas and Roof Disasters for Southern Coal Mines, Hunan University of Science and Technology, Xiangtan 411201)
Abstract：
The imprecision of gas concentration detection in the large cross-section tunnel can lead to significant de? viation between the measured absolute gas emission quantity and the actual value, ultimately affecting the division of gas working areas in the tunnel and posing a huge challenge to tunnel construction safety and cost control. In this study, the computational fluid dynamics software Fluent is used to simulate the distribution law of gas inside the tunnel. The influence of section width (A), section height (B), and section wind speed (C) on the average gas concentration in the tunnel section is qualitatively analyzed through the orthogonal test method. Furthermore, multiple linear regression is used to determine the optimal detection location for the average gas concentration. The research has shown that under stable ventilation conditions, the gas inside the gas tunnel exhibits a stable distribution, and there will be obvious layered distribution from top to bottom on the tunnel cross-section. There are differences in primary and secondary sequence of the influence of section width (A), section height (B), and section wind speed (C) on the average gas concentration of tunnel sections under different gas working area conditions. Through quantitative multiple linear regression analysis, a calculation model for the average gas concentration detection location on the crosssection of stable laminar flow areas under different gas working area conditions is obtained.
MIAO Huigui1 HUANG Fei1,
2 LI Shuqing1,
2 LUO Yafei1 etc
.Study on Detection Location of Average Gas Concentration in a Large Section Tunnel Based on Numerical Simulation - multiple Regression[J] MODERN TUNNELLING TECHNOLOGY, 2023,V60(5): 128-135
2023, Vol. 60 