Key Takeaways & Executive Findings
- •• Developed a mechanistic model for interior pressure fluctuations in high-speed trains using non-ideal gas state equation and polytropic process, improving accuracy over ideal gas assumptions. • The model accurately predicts pressure variations in both overall trends and local details, validated by root mean square error, coefficient of determination, peak-to-peak error, and pressure change rate. • Demonstrated practical applicability across various train types and tunnel scenarios, providing a foundation for evaluating passenger pressure comfort in high-altitude regions. • Enables real-time pressure comfort control strategies by balancing computational accuracy and efficiency, crucial for high-speed train operations.
Abstract
The pressure comfort of passengers and crew in high-speed trains faces significant challenges under alternating open-tunnel conditions. To better understand the mechanism of pressure transmission and control interior pressure fluctuations in high-altitude regions, this study develops an interior pressure fluctuation model. By establishing the frameworks of the non-ideal gas state equation and the polytropic process equation, gas heat transfer and mass transfer were expressed through the first law of thermodynamics and the continuity equation. Simulation results, evaluated by root mean square error, coefficient of determination, peak-to-peak error, and pressure change rate, show that the proposed model closely aligns with measured signals in both overall trends and local details. Data from various train types and tunnel scenarios further demonstrate the model's accuracy and practical applicability. This study provides a critical foundation for evaluating interior pressure comfort for high-speed trains in high-altitude regions.
1. Introduction
High-speed railways have been widely adopted worldwide due to their significant social and economic benefits. Beyond fundamental concerns such as stability and smooth operation, passenger comfort is considered a critical factor in high-speed train operations [1, 2]. To overcome elevation challenges or unfavorable geological conditions, constructing tunnels has proven to be an effective or even indispensable solution [3]. When high-speed trains pass through tunnels, the surrounding air undergoes rapid changes, as illustrated in Figure 1. The compressibility of air and the piston effect result in complex aerodynamic interactions between the train and the tunnel [4, 5].
The study of train-tunnel coupled aerodynamics focuses on key phenomena, including variations in air pressure inside tunnels [6, 7], micro-pressure waves at tunnel portals [8], and interior air pressure fluctuations that impact passenger comfort [9]. Among these, the significant air pressure changes inside tunnels, transmitted through onboard air conditioning systems, exhaust units, and structural gaps in the train body, can induce notable pressure variations inside the train carriage, as shown in Figure 1. These pressure fluctuations may cause discomfort in passengers' ears and, in extreme cases, lead to physiological ailments [10, 11]. Finite element modeling of the human middle ear indicates that auditory discomfort induced by tunnel pressure fluctuations correlates positively with train speed and distance from the driver's carriage of the leading car, and negatively with sealing index and tunnel length [12]. The pressure comfort standard inside trains is generally based on whether the maximum pressure variation within a specific time period meets the required threshold, with this period determined by the physiological characteristics of the human ear.
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MU Bo-yuan, CHEN Chun-jun, YANG Lu, XIA Yu-tao, LIU Jia (2025). Modeling interior pressure fluctuations of high-speed trains considering the non-ideal properties of gases. Journal of Central South University. https://doi.org/10.1007/s11771-025-6149-2
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Frequently Asked Questions
What is the main contribution of this paper?
The paper develops a mechanistic model for interior pressure fluctuations in high-speed trains that accounts for non-ideal gas properties, improving accuracy over ideal gas assumptions and providing a foundation for evaluating passenger pressure comfort in high-altitude regions.
How does the model account for non-ideal gas properties?
The model uses the non-ideal gas state equation and the polytropic process equation, expressing gas heat transfer and mass transfer through the first law of thermodynamics and the continuity equation.
What validation metrics were used?
The model was evaluated using root mean square error, coefficient of determination, peak-to-peak error, and pressure change rate, showing close alignment with measured signals.
What is the practical significance of this research?
The model enables real-time pressure comfort control strategies by balancing computational accuracy and efficiency, crucial for high-speed train operations in high-altitude regions.
What are the limitations of existing models that this paper addresses?
Existing empirical models lack precision, while CFD simulations demand substantial computational resources. This mechanistic model balances accuracy and efficiency, making it suitable for rapid pressure environment evaluations and real-time control.
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