A two-dimensional revolving-axisymmetric model for assessing the wave effects inside the railway tunnel
JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS(2024)
Abstract
The overset grid technique and an improved delayed detached-eddy simulation (IDDES) model were utilized to simulate the passage of a scaled-down prototype train through a tunnel. These simulations were verified through a moving-model test. To simulate the transient pressure and flow field generated when the train enters the tunnel at a speed of 350 km/h, a two-dimensional revolving-axisymmetric train/tunnel model (2D-RATTM) was proposed. The 2D-RATTM's ability to predict the transient pressure and pressure gradient in the tunnel was compared to the simulation data obtained from the prototype train/tunnel model in terms of prediction accuracy, simulation resource requirements, and potential engineering application. The results demonstrate that the 2DRATTM achieves a prediction accuracy of over 91.3% for pressure amplitude and over 93.8% for the maximum pressure gradient in the tunnel. This confirms the reliability of the 2D-RATTM in predicting transient pressure and pressure gradient in the tunnel. Furthermore, the computational time required by the 2D-RATTM is reduced by 97.2%, leading to significant resource savings. This reduction in computational time is particularly beneficial for rapidly evaluating large-scale projects. Moreover, the prediction accuracy of pressure amplitude and maximum pressure gradient remains above 91.2% and 93.9% within a speed range of 300 km/h to 450 km/ h. Similarly, when considering different train and tunnel parameters, such as tunnel length ranging from 330 m to 1000 m, the prediction accuracy of pressure amplitude and maximum pressure gradient remains above 91.3% and 93.9%. This demonstrates the feasibility of performing calculations using the 2D-RATTM under various train and tunnel configurations. These advancements position the 2D-RATTM as a highly valuable tool for engineering applications in future train-tunnel scenarios characterized by higher train speeds and longer tunnel lengths.
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Key words
Axisymmetric model,Pressure waves,Railway tunnel,Prediction accuracy,Simulation cost
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