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Study on Ventilation Energy Efficiency in High-altitude Tunnels Based on Traffic Flow Characteristics
（1. Key Laboratory of Highway Bridge and Tunnel in Shaanxi Province，Chang′an University，Xi′an 710064； 2. Shaanxi Provincial Key Laboratory of Highway Bridges and Tunnels, Chang′an University，Xi′an 710064； 3. China Railway First Survey and Design Institute Group Co., Ltd, Xi′an 710064）
Abstract To study the vehicle pollutant emission characteristics and the ventilation efficiency of mechanical venti? lation system in high-altitude road tunnels, an on-site smoke emission test was conducted on three types of diesel vehicles in the Tianshan Shengli Tunnel on the Urumqi-Yuli Highway. A random forest model was established to predict the smoke emission of single diesel vehicle based on parameters such as vehicle model, longitudinal gradient,speed, and altitude. The correlation between the measured values of single-vehicle smoke emission and the calculated values from the Guidelines for Design of Ventilation of Highway Tunnels was analyzed. The Monte Carlo method was used to study the impact of tunnel traffic flow characteristic parameters on traffic wind-induced boosting efficiency and mechanical ventilation pressure. The results show that the random forest model has good predictive accuracy for single-vehicle smoke emissions, with a root mean square error of 0.251 3 in the test set. The measured single-vehicle smoke emissions are lower than the calculated values from the "Guidelines," and they are highly linearly correlated when the speed is less than 70 km/h. The required mechanical ventilation boost pressure in the tunnel increases linearly with the increase in mixed vehicle traffic flow, while the traffic wind boost efficiency decreases exponentially with the increase in traffic flow and decreases with the increase in single-vehicle smoke emissions. The primary influencing factors of single-vehicle smoke emissions in descending order are the longitudinal gradient, vehicle model,speed, and altitude. Therefore, the longitudinal gradient should be appropriately controlled in the design of high-altitude road tunnels.
Abstract：
To study the vehicle pollutant emission characteristics and the ventilation efficiency of mechanical venti? lation system in high-altitude road tunnels, an on-site smoke emission test was conducted on three types of diesel vehicles in the Tianshan Shengli Tunnel on the Urumqi-Yuli Highway. A random forest model was established to predict the smoke emission of single diesel vehicle based on parameters such as vehicle model, longitudinal gradient,speed, and altitude. The correlation between the measured values of single-vehicle smoke emission and the calculated values from the Guidelines for Design of Ventilation of Highway Tunnels was analyzed. The Monte Carlo method was used to study the impact of tunnel traffic flow characteristic parameters on traffic wind-induced boosting efficiency and mechanical ventilation pressure. The results show that the random forest model has good predictive accuracy for single-vehicle smoke emissions, with a root mean square error of 0.251 3 in the test set. The measured single-vehicle smoke emissions are lower than the calculated values from the "Guidelines," and they are highly linearly correlated when the speed is less than 70 km/h. The required mechanical ventilation boost pressure in the tunnel increases linearly with the increase in mixed vehicle traffic flow, while the traffic wind boost efficiency decreases exponentially with the increase in traffic flow and decreases with the increase in single-vehicle smoke emissions. The primary influencing factors of single-vehicle smoke emissions in descending order are the longitudinal gradient, vehicle model,speed, and altitude. Therefore, the longitudinal gradient should be appropriately controlled in the design of high-altitude road tunnels.
.Study on Ventilation Energy Efficiency in High-altitude Tunnels Based on Traffic Flow Characteristics[J] MODERN TUNNELLING TECHNOLOGY, 2024,V61(4): 51-59
2024, Vol. 61 