Description
This paper presents a comprehensive investigation into the impact of turbulence models on predicting the installation efficiency of jet fans within tunnel environments. Recognizing the critical role of jet fans in enhancing ventilation and maintaining air quality in tunnels, the study focuses on selecting appropriate turbulence models to accurately simulate the complex airflow patterns associated with these installations. The conventional jet fan configuration has been chosen as the focal point for this research, reflecting the widely used design in transportation tunnels. The methodology employs advanced computational fluid dynamics (CFD) simulations to model the aerodynamic behaviour of conventional jet fans in tunnels. A key aspect of the study is the comparative analysis of turbulence models, including commonly used Reynolds-Averaged Navier-Stokes (RANS) models (i.e., k-epsilon 2 equations, k-omega 2 equations, k-omega SST 4 equations, and Reynolds Stress 7 equations). This analysis seeks to understand the details of predicting airflow patterns, pressure distributions, and overall system efficiency, specifically tailored to the conventional jet fan design.
Furthermore, the research extends its investigation to assess the impact of wall boundary layer roughness on the predictive accuracy of turbulence models. The consideration of this factor adds an additional layer of complexity to the study, as it reflects real-world conditions and the diverse surfaces found within tunnel environments. By systematically exploring the interplay between turbulence models and wall boundary layer roughness, the study aims to provide a holistic understanding of the factors influencing the efficiency of conventional jet fan installations. Additionally, the analysis of skin friction coefficients along the tunnel length offers insights into shear stress and resistance, further informing the selection of appropriate turbulence models. The outcomes of this research have broad implications for the field of tunnel ventilation, offering insights into the optimal selection of turbulence models and the influence of wall boundary layer roughness on predictive accuracy. Understanding these factors is crucial for refining numerical simulations, optimizing design parameters, and ultimately improving the safety and operational efficiency of transportation tunnels equipped with conventional jet fan systems.
