关键词: 寒区倾斜巷道, 空气温度场, 现场监测, CFD 数值模拟, 温度预测模型, 标准化回归, 湍流对流修正

Abstract: The construction of inclined tunnels in extremely cold regions can deteriorate the construction environment and cause frequent frost damage inside tunnels due to cold-air intrusion. To address these challenges, field monitoring, theoretical derivation, and three-dimensional numerical simulation were employed to systematically investigate the spatiotemporal evolution of longitudinal airflow temperature in inclined tunnels subjected to cold-air intrusion through the portal and to identify the main factors controlling temperature distribution. Monitoring sections were arranged along a 0－1 000 m stretch of the tunnel to characterize the longitudinal distribution of air temperature. Based on the Boussinesq approximation and the assumption of quasi-steady turbulent natural convection, the governing equations for fluid flow and heat transfer are modified. Correlations involving the Rayleigh and Nusselt numbers were incorporated, and the buoyancy term was corrected to account for the tunnel inclination angle, yielding a longitudinal airflow temperature prediction model suitable for inclined tunnels. A full-scale, three-dimensional numerical model was established using FLUENT to dynamically simulate the cold-air intrusion process, and its accuracy was validated against field monitoring data. The maximum deviation between simulated and measured temperatures was 3 ℃, and the error in predicting the freezing length was 20%. Based on the prediction model, a parametric analysis was conducted under multiple conditions, and the standardized regression coefficient method was used to quantify the effects of inlet air velocity, inlet air temperature, wall temperature, tunnel inclination angle, and cross-sectional characteristics on longitudinal air temperature variations. The results show the following: (1) The airflow temperature in extremely cold tunnels exhibits an exponential recovery trend along the longitudinal direction. Cold air intrudes along the lower part of the tunnel cross section, forming a low-temperature zone at the bottom and a convective mixing zone in the middle. (2) Inlet air temperature and inlet air velocity have significant negative impacts on the rate of air temperature change, while wall temperature has a significant positive impact. In contrast, the effects of tunnel crosssectional dimensions and downward inclination are not significant. (3) The standardized regression analysis shows that the selected factors explain 95.1% of the variation in the rate of air temperature change, with inlet air temperature exerting the greatest influence. The proposed temperature prediction model demonstrates reliable accuracy and can accurately predict air temperature distributions in inclined tunnels in extremely cold regions. The findings provide a theoretical basis and technical support for construction ventilation design, the development of frost-prevention and thermal insulation measures, and safety management in underground engineering projects in cold regions.

Key words: inclined tunnel in cold region, airflow temperature field, field measurement, computational fluid dynamics numerical simulation, temperature prediction model, standardized regression, turbulent convection