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Passenger thermal comfort in high-speed train (HST) carriages presents unique challenges due to factors such as extensive operational areas, longer travel durations, larger spaces, and higher passenger capacities. This study aims to propose a new prediction model to better understand and address thermal comfort in HST carriages. The proposed prediction model incorporates skin wettedness, vertical skin temperature difference (ΔTd), and skin temperature as parameters to predict the thermal sensation vote (TSV) of HST passengers. The experiments were conducted with 65 subjects, evenly distributed throughout the HST compartment. Thermal environmental conditions and physiological signals were measured to capture the subjects' thermal responses. The study also investigated regional and overall thermal sensations experienced by the subjects. Results revealed significant regional differences in skin temperature between upper and lower body parts. By analyzing data from 45 subjects, We analyzed the effect of 25 variables on TSV by partial least squares (PLS), from which we singled out 3 key factors. And the optimal multiple regression equation was derived to predict the TSV of HST occupants. Validation with an additional 20 subjects demonstrated a strong linear correlation (0.965) between the actual TSV and the predicted values, confirming the feasibility and accuracy of the developed prediction model. By integrating skin wettedness and ΔTd with skin temperature, the model provides a comprehensive approach to predicting thermal comfort in HST environments. This research contributes to advancing thermal comfort analysis in HST and offers valuable insights for optimizing HST system design and operation to meet passengers' comfort requirements. [ABSTRACT FROM AUTHOR]

In this study, the sliding grid method is used to simulate a 350 km/h high-speed train passing through a 350 m standard single-line tunnel. The cross-sectional pressure distribution ahead of the train is investigated, the three-dimensional characteristics and propagation mechanism of pressure waves are described based on iso-pressure surfaces, and a newly accurate pressure sensor layout is proposed. The results show that the farther the cross-section is from the train, the smaller the cross-sectional pressure difference is. Influenced by the shape of the train nose and tunnel cross-section, the pressure waves are not simple planar waves, but spherical waves that vary in complexity over the propagation process. As the pressure difference of the 16.6 m cross-section before the train is within 1 Pa, the pressure waves behind this cross-section are defined as planar waves. Besides, the pressure peak-to-peak value difference between the wall and construction clearance reaches 13% at 70–90 m cross-sections, so the pressure sensors should be placed on the surface of the appurtenances rather than on the tunnel wall. In summary, this study is significant for understanding the formation and transmission mechanisms of pressure waves and guiding the scientific layout of pressure sensors in tunnels. [ABSTRACT FROM AUTHOR]