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    Numerical investigation of the impact of wall boundaries on aerodynamic noise in high-speed trains
    (2026-01-01)
    Ma, Zhi Yuan
    ;
    Feng, Qing Song
    ;
    Prapamonthon, Prasert
    ;
    Cheng, Gong
    ;
    Sun, Zhen Xu
    As the operating speed of high-speed trains continues to rise, aerodynamic noise has become a critical factor influencing train performance and passenger comfort, especially in confined environments like tunnels. In this study, a comprehensive simulation of the aerodynamic noise generated during the entire ‘open air-tunnel-open air’ transition at 450 km/h was performed using the improved delayed detached eddy simulation (IDDES) turbulence model and overset grid method, with results validated against field measurements. The findings reveal that, compared to open-air conditions, the tunnel environment induces higher-flow velocities around the train, stronger pressure fluctuations on the train surface, and more pronounced vortex shedding in the wake. Sound pressure levels (SPLs) at surface measurement points are typically about 10 dB(A) higher in the tunnel, with the primary differences observed in the 100–300 Hz frequency range, while both scenarios exhibit spectral peaks near 530 Hz. In the bogie region, tunnel noise is dominated by pressure-wave coupling and wall reflections, which amplify low- and mid-frequency components, whereas under open-air conditions, local vortex shedding and wake instabilities prevail, resulting in more high-frequency noise. The web structure contributes to the reduction of aerodynamic noise from the bogie area, with a particularly significant decrease observed in tunnel conditions. Along the tunnel wall, the SPL initially increases and then decreases, reaching a peak of 125.7 dB(A). After exiting the tunnel, the measurement points at Section L in the open air show a reduction of approximately 10 dB(A) compared to the corresponding tunnel-wall points. This study highlights the substantial amplification of low-frequency noise caused by wall confinement and demonstrates the noise-reduction potential of the web structure. The results provide valuable theoretical insights and numerical evidence for aerodynamic noise control in higher-speed train tunnels, offering significant engineering implications.
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    Optimization-Based Train Timetables Generation with Demand Forecasting for Thailand High Speed Rail System
    (2021-09-01)
    Khwanpruk, Somkiat
    ;
    U-tapao, Chalida
    ;
    Khwanpruk, Kankanit
    ;
    Laokhongthavorn, Laemthong
    ;
    Suwannatrai, Arkom
    In this paper, we propose a timetable optimizer (TO) consisting of the following parts: 1) Demand Forecasting Module 2) Train Optimization Module 3) Timetable Generator Module. TO is a specialized system for planning the train timetable which designed to help solve the problem of determining the number of trains that are suitable and scheduling the train suitably according to the number of trains designated by the system. TO integrates the passenger data from the latest round trip or historical information and forecasts a number of passengers of high-speed trains based on historical data in order to find the optimal number of trains by using a mixed integer programing model. Lastly, the TO system can applies the number of trains to calculate the appropriate train schedule so that the planning cycle is complete. A case study of high-speed railway system in Thailand with 36 trains to satisfy demand of 35,000 passengers/ each direction is conducted. The results show that the proposed system can quickly generate a timetable having an optimal number of train with suitable time interval according to a demand forecasting.
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    A Study on High-Speed Rail Pricing Strategy for Thailand Based on Dynamic Optimal Pricing Model
    (2021-06-30)
    Khwanpruk, Somkiat
    ;
    U-tapao, Chalida
    ;
    Khwanpruk, Kankanit
    ;
    Laokhongthavorn, Laemthong
    ;
    Moryadee, Seksun
    The Bangkok–Nong Khai high-speed railway is the first high-speed line in Thailand and is currently under construction. The project is due to be completed by 2023, with ticket prices starting at 80 baht plus 1.8 baht per km which can be considered as a straight-line fare set with a fixed rate increase. Different from the current price policy, this paper examines the application of dynamic pricing to Thailand’s HSR. Dynamic Pricing Optimizer proposed in this paper is a unique system of dynamic pricing by considering the changes in the amount of service requirements and the time of purchasing tickets designed to solve the problem of pricing that is appropriate. First, The Dynamic Pricing Optimizer (DPO) system will integrate the user data from the latest trip or historical information. After that, there will be a forecast for users of high-speed trains based on historical data in order to create a demand function that is linear. After that, the price will be determined by the optimization method to find the most suitable price in order to maximize the revenue. Lastly, we compare both fare policies and found that The Dynamic Pricing policy can increase revenue up to 6.5%.