Study On Ventilation Of Fume After Blasting In High-Altitude Railway Tunnel By Inclined Shaft

In order to promote the growth of the western region and establish a new framework for the modern era,it is imperative to significantly enhance the infrastructure’s capacity for ensuring security and optimize the railway network architecture in the region.However,the construction of railway tunnels in the western regions is difficult due to ventilation challenges caused by the region’s high altitude and low air pressure.The problem becomes significantly more complicated in inclined shaft work regions of long and huge tunnels,where multiple working faces must be simultaneously blasted.As a result,studying blasting construction ventilation in a high-altitude railway tunnel by inclined shaft may optimize the ventilation scheme in the inclined shaft work area,enhance ventilation efficiency,and assure tunnel environmental safety.This study examines the ventilation design,CO migration patterns,ventilation time rule,and ventilation scheme optimization of the inclined shaft work area of a high-altitude railway tunnel in Tibet using theoretical research,numerical simulation,and machine learning.The main research results and conclusions are as follows:(1)The migration and dispersion of CO in a high-altitude railway tunnel with an inclined shaft are investigated in this work.To accomplish this goal,a computer model of Tibet’s high-altitude railway tunnel is created,and the diffusion and transit of CO following the blasting construction process are simulated under various scenarios using Fluent software.The simulation results show that the fan opening mode and the initial CO concentration distribution have an effect on CO diffusion and transport.The presence of a vortex zone can dramatically reduce the tunnel’s ventilation efficiency.However,the influence of this zone can be reduced by fully using the high-speed airflow in the inclined shaft.It is recommended to focus on monitoring the CO concentration in the vortex zone under different working conditions to ensure construction safety.(2)This study also analyzes the impact of various factors on the ventilation time of the inclined shaft region.The altitude,fan air volume,and explosives mass are selected for analysis.The simulation results indicate that the ventilation time in the inclined shaft work area is influenced by various working conditions.However,the curve depicting the relationship between the peak mass concentration of CO and time in the horizontal portion of the tunnel follows a three-stage decrease pattern.By using the gray correlation degree approach,it is possible to determine the relative importance of the three variables,with fan air volume having the most impact on ventilation time and altitude having the least.(3)In addition,this study applies machine learning techniques to perform multivariate function fitting of the CO peak concentration with time data.A CO concentration-time function model is derived using machine learning techniques.However,the study also highlights the limitations of applying this model to the inclined shaft work area.In order to process 247 numerical simulation data sets,the elastic network regression algorithm is used.Linear functions are generated to predict the CO peak concentration with respect to ventilation time,altitude,wind speed of the air duct,and explosive usage in the inclined shaft work area.These functions can help estimate the effective ventilation duration and provide valuable references for similar projects in the future.