Computational method for convective heat transfer coefficients along sizable air-intake tunnel passages based on empirical data

In the context of the rapid expansion of large-scale subterranean engineering projects, such as underground hydropower stations, mines, and deeply buried subway stations, optimizing heat exchange between air-intake tunnel rock and air has become crucial for enhancing the overall energy efficiency of these underground structures. This study addresses the gap in calculating tunnel heat exchange, particularly the lack of reference values for convective heat transfer and mass transfer coefficients. By analyzing empirical data collected over the past two decades from 14 extensive air-intake tunnels of underground buildings, this paper introduces a novel approach for solving fitting formulas for convective heat transfer coefficients along air-intake tunnels, utilizing empirical data. This methodology utilizes an improved center-moving average data smoothing technique, a comprehensive slope data filtering method, and a novel fitting formula model. It effectively eliminates noise and accurately represents general convective heat transfer behavior within tunnels, especially in the entry segments. Using this method, a fitting formula for the convective heat transfer coefficient along the air-intake tunnel was obtained based on data from 14 tunnels, which can explain 72.3% of data variability. Its reliability was proven using independent measured data. It is tailored for large-scale air-intake tunnels, taking into account actual geometries, wall roughness, entrance effects, and a broad range of wind speeds. The study also presents a dependable method for calculating convective mass transfer coefficients using the proposed fitting formula. The findings provide more precise and practical methods for computing convective heat transfer and mass transfer coefficients in large-scale air-intake tunnels, demonstrating significant practical engineering value.