李琦, 曹宇翔, 唐玉秋,等.基于多因素耦合的高海拔隧道瓦斯体积分数预测模型研究[J].河南理工大学学报（自然科学版）,2026,45(4):86-94.

LI Q, CAO Y X, TANG Y Q,et al.Prediction model for gas volume fraction in high-altitude tunnels based on multi-factor coupling[J].Journal of Henan Polytechnic University(Natural Science) ,2026,45(4):86-94.

基于多因素耦合的高海拔隧道瓦斯体积分数预测模型研究

李琦1, 曹宇翔1, 唐玉秋2, 雷朋1, 李敏1

1.四川农业大学 建筑与城乡规划学院，四川 成都  611830;2.宜宾天原集团股份有限公司，四川 宜宾 644000

摘要: 目的为了探明高海拔瓦斯隧道施工过程中，海拔高度、瓦斯涌出量、送风口距掘进工作面距离、送风口风速对隧道内瓦斯气体扩散运移的影响，进行基于多因素耦合的高海拔隧道瓦斯体积分数预测模型研究。 方法采用计算流体力学软件建立三维数值模型，通过单因素控制变量法设置计算工况，分析各核心因素对隧道瓦斯运移的影响规律；结合4因素4水平正交试验与多元非线性拟合，构建多因素耦合的高海拔隧道瓦斯体积分数预测模型，并采用已有工程实测与数值模拟成果完成模型精度验证。  结果结果发现：（1）随着海拔高度升高，隧道内掘进工作面平均瓦斯体积分数呈指数增长，当海拔高度从0 km升至5 km时，隧道内稳定区域平均瓦斯体积分数从0.072%升至0.128%；（2）隧道瓦斯体积分数与瓦斯涌出量呈高敏感性线性正相关，当瓦斯涌出量由1 m³/min增至7 m³/min时，稳流区各截面平均瓦斯体积分数同步稳定至0.03%，0.23%；（3）当风管出风口距掘进工作面距离为10 m时，掘进工作面处瓦斯体积分数达到最小值；（4）瓦斯体积分数与风管出风口风速呈明显的幂数负相关，当风速大于16 m/s时，瓦斯体积分数下降率达到44.4%；（5）构建的多因素耦合预测模型决定系数达0.903，模型相对预测误差仅为2.79%~4.54%。  结论 本研究可有效预测不同海拔高度、瓦斯涌出量、通风风速和风管位置下掌子面的瓦斯体积分数，可为高海拔瓦斯隧道施工通风设计与瓦斯灾害防控提供科学支撑。

关键词:高海拔;施工通风;瓦斯运移;预测模型;数值模拟

doi:10.16186/j.cnki.1673-9787.2025120037

基金项目:国家自然科学基金资助项目（51908387）

收稿日期:2025/12/11

修回日期:2026/03/31

出版日期:2026/06/17

Prediction model for gas volume fraction in high-altitude tunnels based on multi-factor coupling

Li Qi1, Cao Yuxiang1, Tang Yuqiu2, Lei Peng1, Li Min1

1.School of Architecture and Urban-Rural Planning， Sichuan Agricultural University， Chengdu  611830，Sichuan，China;2.Yibin Tianyuan Group Co.， Ltd.， Yibin  644000， Sichuan，China

Abstract: Objectives To investigate the effects of altitude， gas emission rate，  distance between the air supply outlet and the tunnel face， and ventilation velocity on the diffusion and migration of gas in high-altitude gas tunnels during construction， a multi-factor coupled prediction model for gas concentration at the tunnel face was established. Methods A three-dimensional numerical model was established using computational fluid dynamics （CFD） software. Nineteen working conditions were designed using a single-factor control variable method to analyze the influence of each key factor on gas migration in the tunnel. Based on a four-factor， four-level orthogonal experimental design and multivariate nonlinear regression analysis， a multi-factor coupled prediction model for gas concentration at the tunnel face was constructed. Field measurements and numerical simulation results were used to validate the model accuracy.  Results The results show that the gas concentration at the tunnel face increases exponentially with altitude. When altitude increases from 0 km to 5 km， the average gas concentration in the stable flow region rises from 0.072% to 0.128%. A strong positive linear correlation exists between gas concentration and gas emission rate. When the gas emission rate increases from 1 m³/min to 7 m³/min， the average gas concentration at different sections in the stable flow region stabilized within the range of 0.03%-0.23%. The minimum gas concentration at the tunnel face occurs when the distance between the air duct outlet and the face is 10 m. Gas concentration shows a clear inverse power-law relationship with ventilation velocity， and a reduction of up to 44.4% is observed when velocity exceeds 16 m/s. The proposed model achieves a coefficient of determination of 0.903， and the relative prediction error is within 2.79%-4.54%.  Conclusions The proposed model can effectively predict the gas concentration at the tunnel face under varying altitudes， gas emission rates，  ventilation velocities， and air duct positions， providing a scientific basis for ventilation design and gas hazard prevention in high-altitude gas tunnels.

Key words:high altitude;construction ventilation;gas migration;prediction model;computational fluid dynamics