Aerodynamic phenomena in evacuated tube transportation systems can induce severe deviations in internal environmental parameters, which in turn may give risks to both transportation safety and the structural integrity of the tube. This study aims to reveal the dynamic spatiotemporal changes in the internal environment of an experimental platform, specifically, the pressure and temperature variations inside the tube by employing the Shear Stress Transport k-omega (SST k-omega) model combined with dynamic mesh technology. The established model is based on an unfinished test platform to guide subsequent experimental work. In this study, the changes in pressure, temperature, and piston wind both inside the tube and on its inner wall are analyzed, considering the complex phenomena that occur throughout the entire operational process. The results indicate that when researching the internal environment of evacuated tube transportation systems, the impact of radiation must be incorporated into the analysis. And throughout the operational process, the pressure distribution inside the tube and on its inner wall remains relatively uniform. In contrast, due to the presence of a temperature boundary layer, the temperature distribution on the tube wall varies much more gently than that in the tube's internal flow field. It is noteworthy that the formation and dissipation of shock waves lead to drastic changes in the flow field surrounding the train. The choked flow front exhibits steeper pressure and temperature gradients. Additionally, the aforementioned complex phenomena also affect the piston wind inside the tube, resulting in temporal variations in its direction.

Aerodynamic noise from high-speed trains passing underground stations significantly affects the platform environment. This study investigates its generation mechanism and spatial distribution. An improved delayed detached-eddy simulation (IDDES) method captures the transient flow structures. Aerodynamic noise sources are predicted using the Ffowcs Williams-Hawkings (FW-H) equation, followed by far-field propagation via ray acoustics methods (RAM). Results indicate that the dominant frequencies of train components remain consistent across different operating stages. While train entry into the enlarged cross-section does not alter the distribution of surface sound pressure levels (SPLs), the overall source intensity significantly decreases. Train's surface aerodynamic sources are the primary contributors to platform noise, with the maximum SPL reaching 77.9 dBA. The contribution of the train body (including head, middle, and tail cars) to platform noise ranges from 11.9% to 13.2%, making it the dominant source. Platform noise exhibits no dominant frequency, with its energy primarily concentrated below 1 kHz.

The micro-pressure waves (MPWs) generated by a high-speed train entering a tunnel are a significant noise source affecting the acoustic environment near tunnel exits. Accurate prediction of MPW noise strongly depends on the selection of turbulence models and the treatment of transient impulsive sources. In this study, the generation of MPWs induced by a high-speed metro train was numerically simulated using delayed detached eddy simulation (DDES), based on the k-epsilon (k-ε), Shear stress transport k-omega (SST k-ω), Spalart-Allmaras (S-A) turbulence models, and large eddy simulation (LES). The comparison indicates that the DDES (SST k-ω) model achieves an appropriate balance between computational accuracy and efficiency, accurately reproducing the waveform and pressure gradient characteristics of MPWs. Furthermore, based on these results, the far-field radiation from MPW noise was computed using the acoustic finite element method (FEM). In the MPW noise, dipole noise dominated, with its energy concentrated below 20 Hz and a peak frequency of 4 Hz. An optimal time window method was also proposed, encompassing 95

The vacuum tube transportation system will be essential in the future global economy. However, the thermal environment inside the vacuum tube is complex during train operation. This study establishes a numerical calculation model of the vacuum tube train based on an under-construction model test platform. The aerothermal characteristics of the vacuum tube train are researched during uniform acceleration, uniform motion, uniform deceleration, and static processes. The results show that the aerothermal phenomena generated by trains are significant in each process. During uniform acceleration, aerodynamic heating induced by the blockage effect generates a high-temperature region at the train head. The temperature at the train rear fluctuates significantly due to the influence of shock and expansion waves. During the uniform motion process, the normal shock waves generated by the head train continuously raise the temperature of the blockage region and increase the temperature gradient. The maximum air temperature inside the tube appears at the stagnation point of the head train, peaking at 132.2°C. And the maximum temperature of the train surface is 125.5°C. During uniform deceleration, shock waves in front of the head train progressively dissipate, the high-temperature region diminishes, and the maximum temperature declines. During the static process, the air within the tube oscillates back and forth due to the effects of the piston wind, and the position of the maximum temperature inside the tube constantly changes. After two hours of stationary conditions, the average temperature within the vacuum tube rises to 28.29°C, which is 1.44°C higher than the initial temperature.

Metro train fires represent complex transportation emergencies where hazardous fire effluent propagation and collective pedestrian dynamics are tightly coupled in space and time. Conventional safe egress assessment methods, such as static ASET/RSET timeline approaches and region-averaged dose evaluations, struggle to capture the dynamic hazard exposure experienced by moving occupants in spatio-temporally heterogeneous environments. To address this challenge, this study proposes a hierarchical assessment framework that dynamically integrates transient fire dynamics with occupant evacuation dynamics. By establishing a spatio-temporal mapping algorithm in a discretized spatial domain, continuous Fractional Effective Dose (FED) accumulation is calculated along microscopic individual evacuation paths. Based on trajectory-based computation, multi-level indicators are established across the person, region, and scenario scales to characterize individual exposure, dynamic spatial hazard contributions, and overall risk evolution. Application to a representative metro train fire scenario demonstrates that fire hazards propagate dynamically from train interiors to evacuation platforms, while heat release rate, fire location, and ventilation strategies significantly alter spatial risk distributions. The proposed framework provides a physically consistent, simulation-based methodology for evaluating collective evacuation safety and human-environment interactions in complex subterranean systems.

Modern high-speed train compartments contain intricate internal configurations. In the event of a fire emergency, the propagation velocity of flames through the passenger cabin is determined by multiple factors, including compartment design, ignition source characteristics, and airflow conditions. This study employed computational fluid dynamics (CFD) and large eddy simulation (LES) to investigate the effects of fire source power, fire source location, and longitudinal ventilation velocity on the rate of flame progression. Unlike simplified homogeneous fuel models, this study incorporates the specific heterogeneous material layout of the CR400AF to capture realistic flame spread dynamics. The simulation results reveal that, under forward ventilation conditions, the magnitude of fire power has a minimal influence on flame propagation speed. However, stronger fire sources lead to earlier initiation of flame spread along the carriage. Central positioning of the ignition source results in bidirectional flame movement toward both ends of the carriage, with faster propagation rates than those of fires originating at the extremities. Longitudinal airflow patterns significantly influence the fire dynamics. When the airflow speed within the tunnel remains below 3 m/s, the impact of longitudinal ventilation on fire propagation speed in the train is minimal under forward ventilation conditions. Conversely, in reverse-ventilation scenarios, the rate of flame advancement shows a positive correlation with increasing ventilation speed. Nevertheless, once tunnel ventilation velocities exceed 3 m/s, combustion propagation within high-speed rail carriages becomes impossible due to intact windows, which create oxygen-deficient conditions that prevent the development of fire. This paper investigates the heat release rate and spread process of vehicle fires. It comprehensively considers the effects of fire source power, fire source location, and longitudinal ventilation rate on the rate of spread. The research results provide data support for the fire-resistant design of rail transit vehicles and for the formulation of emergency evacuation strategies for different fire scenarios, which are vital for enhancing rail vehicle fire safety and ensuring personnel evacuation safety.

The load-influencing factors and variation patterns of train air-conditioning systems in plateau environments are extremely complex, leading to long-term operation under load mismatch and seriously affecting the energy-saving control effect. This study focuses on the predictive control of train air-conditioning systems in plateau environments. Using neural network technology, a load prediction model for the train air-conditioning system is established. Then, a predictive control method for the train air-conditioning system is established based on fuzzy PID control. Based on joint simulation in AMESim and Simulink, the energy consumption of the air-conditioning system is simulated under predictive control mode, and the impact of advanced time in predictive control on the control effectiveness of the air-conditioning system is analyzed. The results demonstrate that incorporating a temperature feedback correction loop into the predictive control mode can enhance the control effectiveness of the air-conditioning system. Compared with the feedback control mode, the daily energy-saving rate of the air-conditioning system under predictive control reached 13.44%. In predictive control mode, the temperature fluctuation amplitude inside the carriage is reduced, resulting in a more comfortable interior environment. This research result can provide a reference for developing energy-saving control strategies for train air-conditioning systems in complex environments, particularly in plateau areas.

Due to concentrated heat loads and confined spaces, equipment rooms in urban rail transit systems face increasing challenges in maintaining suitable thermal conditions. This study establishes a steady-state temperature prediction model driven by thermal buoyancy to address this issue. It further evaluates the effects of ventilation opening parameters, equipment heat load, and train operation on natural ventilation performance through numerical simulations. First, a temperature calculation formula is derived based on thermal balance analysis, clarifying the physical significance of the empirical coefficients a, b, and the vent velocity v. A series of three-dimensional steady-state simulations are then conducted to investigate how variations in the vent area, height, and layout affect the temperature and velocity fields within the equipment room. Representative data are extracted to analyze airflow characteristics and steady-state temperatures under various conditions. The coefficients are obtained through regression fitting, and the wind speed term is simplified using a near-constant approximation to develop a rapid prediction model. Results show that the temperature prediction model maintains a relative error within +/- 8 % under typical working conditions. Further analysis reveals that the piston wind effect generated by train operation significantly influences the room temperature, providing a critical basis for model refinement and optimization.

Abstract Deep-buried water conveyance tunnels play a crucial role in regional water transfer and security. During maintenance periods, the decay of mussels attached to tunnel walls releases hazardous gases such as ammonia (NH 3 ), which poses safety risks to maintenance personnel. This study develops and evaluates optimized ventilation strategies aimed at removing such gaseous pollutants in deep-buried tunnels. A Computational Fluid Dynamics (CFD) approach, incorporating the RNG k-ε turbulence model and species transport equation, was utilized to simulate airflow patterns and ammonia dispersion. The results demonstrate that the designed longitudinal ventilation system effectively maintains an average airflow velocity of 1.02 m/s and keeps NH 3 concentration below the occupational exposure limit of 20 mg/m 3 . Additionally, localized ventilation strategies were proposed, which involve activating only the fans in the vicinity of the maintenance section to save energy. These findings provide a validated and energy-efficient ventilation framework that ensures both personnel safety and reduced operational energy consumption during tunnel maintenance.

Supersonic Hyperloop operation in a low-pressure tube can generate bow shocks, reflected shocks, boundary-layer separation and choking, causing aerodynamic heating and long-duration heat accumulation in the vehicle skin. To predict this structural response efficiently, a CFD-based one-way coupled structural heat-transfer method with hot-wall correction is proposed and applied to unchoked and choked flows. The CFD solver is validated, and comparisons between adiabatic and isothermal wall conditions show that wall thermal conditions mainly change the near-wall temperature gradient and heat flux, while the main shock topology, separation/reattachment pattern and flow regime are only weakly affected. Using pure-CFD radiative-equilibrium calculations as references, the proposed method predicts outer-wall stagnation temperature with errors of about 2% and 6.15% for unchoked and choked flows, respectively. Structural results indicate that, under unchoked flow, the vehicle-head stagnation area and shock-affected locations heat up first, but the long-duration temperature field is reshaped by through-thickness heat input and tangential diffusion; post-shock uniformly heated areas can therefore accumulate heat. After 3600 s (1 h), the stagnation-area temperature reaches about 430 K, exceeding the 423 K long-term service threshold for aluminum alloys. Under choked flow, restricted compression and shock trains continuously heat the head and throat/front-middle body, raising the maximum stagnation temperature to about 490 K and causing a more severe material thermal-safety risk. These findings demonstrate that the CFD-based one-way coupled method with hot-wall correction can efficiently predict the long-duration structural thermal response of Hyperloop vehicles and provide guidance for thermal-protection system design in supersonic low-pressure-tube transportation.

The air-conditioning system (ACS) is an indispensable element of metro carriage. It can automatically regulate the temperature and humidity inside the carriage to cultivate a comfortable environment for passengers. Most research concerning metro carriage fires overlooks the impact of the ACS on the fire smoke spread inside the metro carriage. In this study, a 1:2 scale model of the metro carriage was constructed, and a series of experiments were conducted with fire sizes ranging from 26.5 to 150 kW. The smoke spread process and the temperature distribution within the carriage were investigated to examine the effects of the ACS on metro carriage fires. The findings demonstrate that the ACS not only delayed the activation of the fire alarm system but also disrupted the ceiling jet flow, leading to a smoke-filled carriage. A modified prediction model was also developed to estimate the maximum ceiling temperature inside the carriage. Finally, the longitudinal ceiling temperature attenuation patterns were studied, and a series of exponential functions have been correlated in this study. These findings could offer technical guidance for vehicle manufacturing and serve as a basis for additional investigation into the best practices for evacuation plans and ventilation systems inside metro carriages.

Pitting corrosion of aluminum fins in coastal air-conditioner units degrades heat-exchange performance. This study quantifies pitting corrosion of 6063 aluminum fin assemblies under cyclic neutral salt spray. A salt-spray protocol (720 h, 42 cycles) was applied to fins with different spacings, surface flatness, dehumidification/desalination strategies, and placement angles. Net mass change was measured by a loss-on-drying gravimetric method and analyzed statistically. Fins with smaller spacing and corrugated surfaces showed a mass increase of approximately 2% from adherent corrosion products after 31 cycles. This increase was substantially larger than for smooth, widely spaced fins, indicating that narrow spacing and poor flatness intensify pitting damage. Under summer conditions, periodic water-mist spraying combined with enclosure and desiccant produced the lowest cumulative mass change among all mitigation measures. In contrast, ozone treatment yielded only modest. The installation angle also significantly affected pitting corrosion. After 42 cycles, vertically mounted fins exhibited a corrosion weight-loss ratio of 12.1%, approximately three times that of horizontal fins (4.0%), while tilted orientations showed intermediate behavior. These results demonstrate that liquid-film thickness and renewal significantly influence the pitting corrosion of coastal aluminum fins, providing quantitative guidance for fin geometry, dehumidification scheduling, and placement angle in coastal air-conditioning design.

Seasonal performance evaluation of refrigeration equipment used for air-conditioning is to evaluate the comprehensive refrigeration capacity of the air-conditioning system throughout the refrigeration season. Different load characteristics and air-conditioning equipment make the simplification and abstraction methods of seasonal performance indicators different. There are great differences in the operating environment, service time range, and air-conditioning performance characteristics between train air-conditioning and building air-conditioning. In order to describe the comprehensive cooling capacity of subway train air-conditioning during the whole cooling season, this study proposes a specific method for evaluating the seasonal performance of the subway train air-conditioning systems under the condition of an air-conditioning bench test. This study first analyzes the construction methods of the typical cooling load model, the running time distribution model, and the performance model of the subway train air-conditioning systems. Then, the specific calculation formulas of seasonal energy efficiency ratio (SEER) are proposed for three common operation forms of subway train air-conditioning systems, which are two-compressor fixed-frequency air-conditioning systems, four-compressor fixed-frequency air-conditioning systems, and two-compressor variable-frequency air-conditioning systems, by means of numerical simulation and mathematical derivation. Finally, the real SEER is calculated based on the energy consumption test value for the two-compressor fixed-frequency air-conditioning system. Compared with the real SEER, the relative error of SEERcal obtained by the SEER calculation method proposed in this study is less than 5%, which indicates that the seasonal performance evaluation of refrigeration equipment used for subway train air-conditioning systems is highly accurate.

This study investigates the diffusion mechanism of gaseous pollutants within the water pipeline under longitudinal ventilation by analyzing the effects of ventilation velocity, release rate, and distance to the air inlet vent. According to previous studies, NH3 was chosen as the gaseous pollutant, and a series of numerical simulations were conducted. The results demonstrate that the airflow within the water pipeline is piston flow, the direction of which is determined by ventilation mode. Affected by the Coanda effect, the ununiform velocity leads to an uneven distribution of NH3 on the water pipeline cross-sections. The mean cross-sectional values are chosen for further analysis. The concentration of NH3 in the water pipeline is proportional to the release rate of NH3 and distance to the air inlet vent, respectively. When the release rate is fixed, increasing the ventilation velocity can effectively remove the pollutant, and the concentration of NH3 is proportional to the -1 power of the ventilation velocity. Finally, a prediction model of the mean cross-sectional concentration of NH3 is obtained by combining it with theoretical analysis. Therefore, this study can not only optimize the operation of the ventilation system in this Inter-basin Water Transfer (IBWT) project but also guide the design of the ventilation system in other IBWT projects with deep buried long-distance water pipelines.

Despite its significant application potential,low-vacuum ultra-high-speed rail transit faces several pressing scientific and technical challenges.This paper presents a comprehensive review of low-vacuum tube ultra-high-speed rail transit technology,covering its origins,development,and current international research trends.The necessity and feasibility of developing this technology are then an-alyzed,followed by a detailed discussion on the adaptability of magnetic levitation technology for trains operating in low-pressure envi-ronments,as well as the primary technical challenges,such as heat dissipation and insulation issues.Furthermore,the paper proposes technical solutions and measures for rescue and evacuation specific to low-vacuum tube transportation systems.

The airflow around a vacuum tube maglev train operating at high speeds is complex. In addition, the effect of relevant parameters in such a transportation system on aerodynamic characteristics is crucial in the design and safety of the system. A three-dimensional (3D) vacuum tube train model is established based on a vacuum tube test platform for rail transit. The effects of the initial ambient temperature and scale ratio on the aerodynamic characteristics are analyzed during the whole operational process in this study. The results mainly focus on each process's variations in the shock waves, choked flow, and drag. During acceleration, shock wave generation is advanced or delayed under different system parameters, which vary the aerodynamic drag. While the train runs at a constant speed, the time that a standard shock is generated and the length of the choked flow differ under the effects of the varying system parameters. In braking, the disappearance of shock waves and reflections of the expansion wave suddenly decreases the aerodynamic drag either earlier or later due to the varying system parameters.

To investigate the influence of enlarged cross-section railway tunnels on high-speed trains' aerodynamic noise source characteristics, the improved delayed detached eddy simulation method is employed to calculate the unsteady flow field around the high-speed train. The aerodynamic noise source characteristics on the train's surface are predicted using the Ffowcs Williams–Hawkings acoustic model. The accuracy of the numerical method is validated through wind tunnel experiments. The results show that, across different operation stages, the unsteady flow field distribution around the high-speed train exhibits similar characteristics. Significant differences are observed in the pulsating pressure distribution on the surfaces of the train body, pantograph, and bogie; however, the dominant frequency remains constant as the train moves. While passing through the enlarged cross section, the sound pressure level at the nose of the head car, the streamlined of the tail car, and the pantograph decreases by 3.1, 10.0, and 9.1 dBA, respectively. The enlarged cross section significantly affects the radiated sound power on the train surface, with the pantograph exhibiting the highest noise radiation power density, followed by the bogie and the train body. The distribution of sound power levels on the train body and pantograph shows distinct dominant frequency characteristics. After passing through the enlarged cross section, the sound power level of the head car decreases by a maximum of 6.7%, while the tail car experiences the slightest reduction of 3.1%. The sound power level of the pantograph decreases only marginally by 3.5 dBA over the entire operation.

Previous research has demonstrated that the Train Wave Signature (TWS) method enables rapid calculation of pressure waves in straight tunnels. However, its application to subway tunnels with complex structural features remains insufficiently explored. This study proposes a generalized mathematical method integrating TWS with graph theory for the simulation of pressure wave generation, propagation, and reflection in complex tunnel systems. A computational program is implemented using this method for efficient simulation. The proposed method achieves high-accuracy prediction of pressure waves in tunnels with complex geometries compared with field measurements conducted in a high-speed subway tunnel with two shafts. We discuss the impact of iteration time intervals on the results and clarify the minimum time interval required for the calculation. Moreover, the sin-type definition of TWSs enhances the precision of pressure gradient prediction, and omitting low-amplitude pressure and reflected waves from the train can improve computational efficiency without compromising accuracy. This study advances the application of TWSs in tunnels with complex structures and provides a practical solution for aerodynamic analysis in high-speed subway tunnels, balancing accuracy with computational efficiency.

The aerodynamic pressure disturbances induced by middle air shafts and bypass ducts in subway tunnels pose significant challenges to enhancing train operational speeds. A comprehensive series of full-scale experiments are employed to examine the impact of these structural elements on the aerodynamic pressure characteristics of platform screen doors (PSD) in high-speed subway stations. The experimental results reveal that peak pressures manifest on PSD surfaces during two distinct scenarios in high-speed subway systems equipped with middle air shafts. One is compression pressure waves propagated from trains traversing the air shaft, and the other is train nearby flow when trains pass the PSD directly. The peak positive pressures caused by train passing PSD is much greater than compression pressure waves. Closing middle air the shaft can reduce the passing pressure waves. The installation of bypass ducts at overtaking station entrances effectively mitigates peak negative pressures during train-PSD interactions, achieving a maximum reduction efficiency of 8

To effectively control the micro-pressure wave noise radiating from tunnel exits, numerical simulations were conducted to investigate the generation and propagation of such noise at the exits of high-speed metro tunnels. Large-eddy simulation was employed to obtain the near-field unsteady flow field data at the tunnel exit. The Ffowcs Williams-Hawkings (FW-H) acoustic analogy was used to predict the types of sound sources for micro-pressure wave noise. The unsteady flow field data were also utilized for finite element method acoustic analysis to calculate the far-field radiation of micro-pressure wave noise. The accuracy of the numerical methods was verified through moving model tests. The results indicate that dipole noise dominates within the micro-pressure wave noise. The tunnel's inner wall contributes most to the dipole sound sources. Dipole noise radiates outward in the form of semi-ellipsoidal waves, with energy mainly concentrated below 20 Hz and a peak frequency of 4 Hz. Furthermore, the decay of dipole noise in the direction of the tunnel exit follows a similar exponential decay pattern to that of an explosion shock wave. When the train speed exceeds 400 km/h, the human ear can distinctly perceive the sonic booms at the tunnel exit.