The air compressors in a locomotive's air supply system are located in confined spaces within the locomotive. Operating continuously under high loads and high temperatures, they generate significant heat and face challenges in heat dissipation. Therefore, this paper uses numerical simulation methods to analyze the effects of the air inlet louver porosity and exhaust configuration on the heat dissipation performance of an air conditioning (AC) unit under extreme ambient temperatures (55 degrees C), and verifies the reliability of the results through algorithmic validation. The results indicate that the temperature distribution on the surface of the AC unit is highly uneven and closely correlated with the local flow velocity distribution. Although there is a linear relationship between the inlet aperture area and the surface temperature of the AC unit, the heat dissipation benefits achieved by adjusting the aperture area alone are not significant. Further analysis revealed that while closing the top cover enhances convective heat transfer, it also leads to an increase in the air flow temperature. In response, this study proposes an integrated optimization scheme that combines a closed top cover with side-wall exhaust ventilation. This scheme enhances surface convective heat transfer while simultaneously lowering the air flow temperature, resulting in a 12.6% and 10.0% decrease in the average surface temperatures of AC1 and AC2, respectively, and significantly reducing the ambient temperature in the machine room. The research findings reveal the mechanisms by which ventilation parameters affect heat dissipation performance, providing valuable guidance for the thermal design of locomotive auxiliary systems.

Previous studies have demonstrated that the Ensemble Kalman Filter (EnKF) has been successfully applied to optimize turbulence model constants under various flow conditions, particularly in two-dimensional cases. However, in engineering applications, the flow fields are often three-dimensional and highly nonlinear. Under such conditions, due to the non-uniqueness of the optimal solution in the inverse problem, directly applying the conventional EnKF often yields unsatisfactory results. To address this challenge, this study combines proper orthogonal decomposition (POD) with EnKF to develop a POD-reduced EnKF algorithm for data assimilation in complex three-dimensional flow fields of high-speed trains. By extracting flow field characteristics through POD, the number of observation points is reduced, which significantly enhances the data assimilation accuracy. Results show that the assimilated turbulence model constants lead to good agreement between simulation and experimental data for a high-speed train operating in open-air conditions. The method also demonstrates strong robustness, achieving consistent assimilation performance across different numbers and locations of observation points. In addition, the optimized constants exhibit a certain degree of generalizability, improving prediction accuracy across different inflow conditions and geometries. The proposed framework offers a promising strategy for enhancing aerodynamic modeling of high-speed trains.

A train body's cross-sectional shape has a significant impact on aerodynamic drag and operational safety in high-speed trains (HSTs). This study extracts five design variables from a real-world HST body: height, width, side arc radius, arc radius at the connection between the side and the roof, and arc radius at the connection between the side and the train's bottom. The cross-validated Kriging surrogate model and the genetic algorithm are used to perform two types of aerodynamic optimization, with the cross-sectional area as a constraint. Cross-sectional shapes are optimized in both windless and windy conditions. Numerical results indicate that in a windless environment, the aerodynamic drag coefficient of the whole train is reduced by 2.4%; in a windy condition, the aerodynamic drag coefficient of the entire vehicle is reduced by 2.4%, and the aerodynamic lateral force of the leading car is reduced by 37.8%. These suggest that a flat and wide shape helps to reduce not only overall aerodynamic drag in a windless environment but also aerodynamic load in a windy environment, which can be accomplished by reducing the area of the side wall and top region, lowering the train body's height, increasing its width, and lowering the radius of the side and top arcs.

Next-generation high-speed trains operating at 450 km/h face critical pantograph stability challenges. Intense roof-level airflow degrades aerodynamic performance and induces aeroelastic vibrations, compromising contact stability, accelerating fatigue, and threatening structural integrity. To address these issues, a bidirectional FSI computational model is developed using ANSYS Workbench. Fluent and Mechanical are employed to solve the fluid and structural fields, respectively, with System Coupling enabling node-level data exchange. The fluid field is modeled using the RANS equations with the SST k-omega turbulence model, while a flexible pantograph model is adopted for the structural field. The "moving catenary, stationary pantograph" concept and the Augmented Lagrange contact algorithm are applied to simulate aeroelastic behavior at 450 km/h. The results indicate that FSI coupling increases the pantograph lift by more than 8% compared to uncoupled simulations, while significantly attenuating aerodynamic load fluctuations. Furthermore, the aerodynamic excitation is found to facilitate the redistribution of vibration energy within the pantograph system. The mean and standard deviation of the contact force are 320 N and 119 N, respectively. Maximum stress reaches 116 MPa at the arc transition of the pantograph head suspension rib, yielding a safety factor of 1.07 and indicating the need for structural reinforcement.

The construction of the railway network is advancing steadily, with a substantial increase in the number of railway tunnels. Among these tunnels, the proportion of double-track tunnels has risen significantly. Along with this trend, the pressure wave superposition effect caused by train crossings in double-track tunnels has become a critical issue, posing threats to the structural integrity of tunnels and passenger comfort. To address this issue, a double-track train wave signature (TWS) model is proposed, based on the principle of characteristic wave superposition. The first part of the paper introduces the principle of the single-track TWS method, outlines the construction of the double-track TWS method, and briefly describes the three-dimensional (3D) numerical model used. The proposed double-track TWS method is then validated through both field measurements and 3D numerical simulations. This is followed by an analysis of the propagation and evolution of wave systems within the tunnel during train crossings. Finally, the paper presents a systematic investigation of tunnel wall pressure amplitude variations resulting from different train entry timings. Key findings indicate that the TWS method achieves sufficient accuracy in simulating tunnel wall pressure for both single- and double-track configurations, with peak-to-peak errors within 10%, except at points near tunnel portals. For double-track crossings at constant speed, the maximum and minimum pressures, as well as peak-to-peak values on tunnel walls, exhibit periodic-like fluctuations with crossing positions. This phenomenon becomes more prominent in shorter tunnels. Moreover, adjusting the entry time difference between trains may even reduce peak-to-peak pressure values on tunnel walls by 50%, offering a theoretical foundation for optimizing train scheduling and tunnel design.

Urban railways alleviate traffic congestion and enhance transportation efficiency. The operation of trains in tunnels can cause significant pressure waves, resulting in passenger discomfort and auditory damage. Therefore, airtight train configurations were employed to mitigate interior pressure fluctuation. To ensure interior air quality, controlled ventilation through air-conditioning units (ACUs) is required. However, during tunnel operations, pressure waves enter the carriage through ACUs, thereby affecting the interior pressure. Considering that the on-off plates of air intakes may malfunction, the influence of tunnel pressure waves on the auditory comfort of passengers is worth investigating. In this study, a full-scale test was conducted to investigate the spatiotemporal distribution characteristics of the interior/exterior pressure variation induced by trains with different lengths passing through tunnels at multiple speeds. The ACU air intake operates in three states: automatic control (closed), 1/4 open, and fully open. An inverse correlation was observed between train length and interior/exterior pressure variation. Compared with the driver's cab, the interior pressure of the passenger compartments was more affected by the train length (with a difference of approximately 30%). The operational state of ACU air intakes significantly impacts interior pressure variations, with closed intakes effectively reducing fluctuations, whereas opening size demonstrated limited influence. Both the amplitude and variation of the interior/exterior pressure exhibited positive correlations with train speed. These findings inform optimized ACU intake control strategies for enhancing passenger auditory comfort.

Traditional experimental methods usually measure the aerodynamic load characteristics of an object by deploying a large number of pressure sensors on its surface, which are often challenging to economically and efficiently obtain accurate surface pressure distribution due to limitation imposed by experimental space, the complexity of geometry, and the cost of measurement instruments. To address this, a compressed sensing (CS) based framework has been proposed in this paper to investigate the reconstruction of the original surface pressure field from extremely sparse measurement data. The proposed framework integrates the generalized proper orthogonal decomposition method for flow field dimensionality reduction, the CS technique for accurate reconstruction of the original signal, and the improved particle swarm optimization algorithm for optimizing sensor placement strategies. Unlike image and unsteady flow field reconstructions, the method presented in this paper has been successful in reconstructing surface pressure fields of high-speed train under various conditions. Based on the accurate reconstruction of surface pressure fields, further aerodynamic load data can be obtained. Additionally, this paper optimizes the traditional pressure sensor layout using a particle swarm optimization method, which not only improves reconstruction accuracy but also significantly reduces the deployment of redundant sensors. Moreover, traditional point selection strategies based on experience can still be incorporated into the pressure sensor layout scheme and effectively reduce reconstruction errors under crosswind conditions. Comparison of the results showed that the proposed framework can accurately and efficiently reconstruct the surface flow field of three-dimensional complex-shaped objects from sparse measurement.

The bogie area with a complex structure is an extremely important source of noise for trains. Based on the large-eddy simulation(LES) and Ffowcs Williams-Hawkings(FW-H) analogy, aero-acoustic simulation was conducted on a 3-car high-speed train of a certain type with a bogie cavity bottom plate installed on the front and rear cars. The results show that bottom plate changes the flow field around the bogie, weakens the flow separation of airflow at the leading edge of the bogie cavity, mitigates the flow impact of airflow on various components of the bogie, suppresses the formation and detachment of large-scale vortices in the bogie area, and reduces the formation of pressure pulsations on the geometric surface of the bogie area. The bogie cavity bottom plate scheme reduces the far-field aerodynamic noise of the train by 1.63dBA, and the noise reduction effect is significant. The aerodynamic noise of the measurement point equipped with a bogie cavity bottom plate is lower than that of the conventional bogie cavity in all frequency bands, and the energy reduction is more significant at medium and low frequencies.

This paper discusses the contribution of the quadrupole noise source on the aerodynamic noise of the high-speed maglev train. The computational method of the aerodynamic noise considering the quadrupole noise source is presented, and the aerodynamic noise characteristics of the high-speed maglev is studied. The study shows that the dipole noise sources of the high-speed maglev train are mainly distributed on the bottom of the head car, the bottom and body of the tail car, the bottom and inside of the suspension frame. The contribution of the quadrupole noise source is more reflected in the low-frequency range. The aerodynamic noise energy of the high-speed maglev train caused by the quadrupole noise source accounts for 42% at the train speed of 600km/h.

为研究压缩波沿隧道传播演化的影响规律,采用考虑压缩波惯性效应和壁面摩擦效应的一维特征线法,建立了压缩波沿隧道传播演化的数值模型,通过一维平面波方程与实车测试两种方法共同验证了该模型的准确性.针对波前形状、车身波等、压力幅值关键因素,研究了初始压缩波沿隧道传播时,最大压力梯度的变化规律.在此基础上,进一步探讨分析了摩擦与气室阵列共同作用对压缩波波前演化的影响以及壁面摩擦的作用机理.结果表明:初始压缩波波形相同时,压缩波最大压力梯度随波前幅值的增大而增大;不同波形的初始压缩波沿隧道的演化规律不完全相同,但列车车身进入隧道所产生的车身波并不会影响压缩波波前的最大压力梯度;考虑壁面摩擦后,气室阵列对压缩波最大压力梯度的缓解效果有了进一步提高,壁面摩擦越大,缓解效果越显著.

The high-speed train's windshield structure is made of high strength rubber. The stagnation pressure under crosswind condition will lead to a large average deformation along with moderate flow-induced vibration of the windshield structure. This deformation and vibration have a vital influence on the servicing life and failure model windshield structures. In this study, the flow-induced deformation and vibration of windshields under crosswind condition are systematically analyzed through an experimentally verified numerical approach. The flow field and aerodynamic load around windshield structure, as well as the deformation of windshield structure are systematically investigated. The results indicate that, compared to the flat ground windless condition, the windshield's maximum deformation location under crosswind has shifted from the upper half to the lower half. Besides, among all windshield structures throughout the three car formation train, the downstream half of windward windshield between head car and middle car exhibits the largest deformation. When the wind angle shifts from 20° to 30°, the primary frequency of this maximum displacement location is around 30 Hz. In contrast, the primary frequency on the maximum displacement location of windward windshields between middle car and trailing car is 17.5 Hz.

为解决目前车体气密强度试验过程中压力加载系统与应力位移测试系统两者相互独立,测试位移方式为相对位移的问题,基于NI平台,借助NI-CompactRIO微控制器和Labview软件人机交互界面设计,采用迭代学习控制算法,开发了轨道车辆车体气密强度试验系统.该试验系统实现了车体气密强度试验过程中压力加载系统与应力位移测试系统耦合,当车体各测点应力位移测试值超出预警值,会自动反馈控制调节压力加载值,使其泄压,起到有效、及时地保护试验车体的作用,提高试验的安全性及智能化程度;同时能够对不同车型任意断面任意位置处车体结构绝对位移测试,提高测试可靠性及精准度,为车体结构优化设计提供数据支撑.

The length of high-speed railway tunnel is an important factor affecting transient pressure of high-speed train. When the tunnel length is the most unfavourable, the transient pressure changes in the tunnel and on the surface of the train are the most severe, which may affect the safe operation of the train or damage the structure in the tunnel. Based on the three-dimensional, compressible, unsteady N-S equation and finite volume method, this paper uses the CFD numerical simulation method to study the change and amplitude distribution of the transient pressure on the train surface and the tunnel when a high-speed train passes through the most unfavourable length tunnel. A fast calculation method is proposed to save the cost of calculation; it has great applicability of pressure amplitude. The results show that the pressure distribution in the tunnel and on the surface of the train is affected by the train speed, the length of the train and the position of the measuring point. The minimum negative peak value in the tunnel appears at the position where the superposition phenomenon is the most severe, and the position will change with the speed of the train. There are two negative peak waveforms of the train surface pressure, and the first waveform is greatly affected by the train speed. It improves a reference for studying the strength requirement of the most unfavourable length tunnels and trains, and ensures the safe operation of trains in tunnels of different lengths.

高速列车驶入隧道时会产生初始压缩波,其沿隧道纵向传播至出口时会向隧道外辐射形成微气压波.本文搭建了利用高压空气瞬间释放产生初始压缩波的实验装置,对其产生的压缩波开展了实验研究.介绍了实验装置的组成,分析了隧道内压力时程曲线及形成机理,给出了实验装置各参数对初始压缩波的影响规律,对压缩波的后续衰减过程进行了分析.实验结果表明:隧道内的压力波动主要受隧道出入口的反射波影响;通过改变实验装置相关参数能够对初始压缩波的波形进行调节;不同高压腔初始压力下,压缩波的衰减周期相同,但初始幅值越大,相同时间内压力衰减得越快.

The high-speed train’s windshield structure is vital to the boundary layer development and drag reduction design. Up to date, windshield structures are assumed as rigid body in most train aerodynamic numerical simulations. This research investigates the fluid-solid coupling effect of high-speed train’s windshield structure based on an 8-car formation model. The influence of speed level and windshield installation location on the flow field parameter and windshield deformation profile are systematically analysed. The results indicate that, with the development the boundary layer, the time-averaged pressure coefficient, lateral force coefficient and windshield’s displacement all gradually decrease from 1st windshield to 4th windshield along the stream direction. In the connecting region between the windshield and vestibule, a pair of negative pressure zone are formed and gradually intensify along the downstream direction, such that the time-averaged deformation, as well as the vibration amplitude of windshields experience a slight increase. According to the power spectral density analysis, the vibration frequency of all windshields’ displacement varies between 10.25 Hz and 12.5 Hz. Meanwhile, the pantograph structure will lead to the generation of vortex group, these vortices will lead to additional small low frequency peaks for windshields installed on the downstream direction of pantograph.

低真空管道超高速磁浮系统是将低真空管道和高速磁浮技术结合的新型超高速地面交通系统,可有效降低列车超高速运行时的气动阻力及气动噪声,实现800～1 000 km/h甚至1 000 km/h以上的运行速度.本文探讨了低真空管道超高速磁浮列车空气动力学数值模拟方法,研究了管道压力、管道面积、列车速度对低真空管道超高速磁浮列车气动阻力、气动升力、气动噪声源、管道交会压力波、发热设备温度等空气动力学性能的影响规律,并针对低真空管道超高速磁浮系统典型场景进行了初步工程化探讨.研究表明:当列车速度为600 km/h时,管道常压-管道面积100 m2 和管道压力0.3 atm-管道面积40 m2 的配置具备工程可行性;而管道压力0.3 atm-管道面积100 m2 下的设备散热存在问题,工程可行性存在一定挑战;当列车速度为1 000 km/h时,管道压力0.3 atm-管道面积100 m2 下的设备散热问题显著,工程可行性挑战较大;若进一步降低管道压力,设备散热与气密强度设计难度将进一步加大.

在高速磁浮列车通过隧道过程中,受隧道内壁面和车体表面形成的环状空间限制,列车头部前方气流受到压缩,在隧道入口形成初始压缩波.初始压缩波在隧道内以当地声速传播至隧道另一端出口,部分能量以脉冲形式向外辐射,形成微气压波,严重影响隧道出口附近环境.当高速磁浮列车速度达到600 km/h以上时,这一问题更加显著.为此,提出一种具有谐振腔结构的隧道,采用三维、非定常、可压缩N-S方程和SST k-ω湍流模型研究其对高速磁浮列车通过隧道的气动效应减缓特性,并对2种谐振腔方案的减缓效果进行了数值模拟和动模型试验验证.研究结果表明:在隧道内冗余空间安装谐振腔结构,可以耗散压缩波能量,减小压缩波压力梯度,对隧道出口微气压波现象有明显减缓作用;与无谐振腔结构的隧道相比,谐振腔结构对隧道出口 20和 50 m处微气压波的减缓效果分别为 41.87%和 40.15%;微气压波减缓效果与隧道内谐振腔数量成线性关系;动模型试验进一步验证了数值模拟方法优选方案的准确性,不同速度试验结果表明微气压波减缓效果与运行速度正相关.

流致振动是高速列车设计和运维过程中需要重点关注的问题之一.针对高速列车司机室车门区域的 凹腔结构,利用数值计算、风洞试验和实车线路试验相结合的方法,分析车门区域的流场特征和车门出现流致振动现象的主要原因,据此对车门两侧凹腔结构和扶手进行优化,并对封堵凹腔和扶手内移2种优化方案进行实车试验验证.结果表明:司机室车门上游凹腔结构诱导的展向涡导致车门表面出现高频的脉动压力,列车运行速度越高,压力波动幅值越大,但波动频率锁定在83 Hz,当压力幅值超过车门承受的限值后,车门将出现流致振动现象;气动拉力和气动侧向力是诱发司机室车门流致振动的主要气动载荷,车门宜设置在车体横截面不变区域;通过优化凹腔结构和扶手的形状能够消除司机室车门的流致振动现象;合理改变扶手位置能够减弱凹腔结构引起的流致振动现象;如果要消除流致振动现象,应将扶手改为盖板结构,或者将扶手截面形状改为非圆形截面.

The demand for large passenger capacity of intercity EMU leads to a shorter streamlined train head, the demand for small cross section of the intercity/suburban line tunnel leads to a larger blockage ration of the train passing through the tunnel. The pressure wave and interior pressure fluctuation of the train passing through the tunnel are the prominent problems, which affect the comfort of the passengers. This paper mainly focuses on the pressure wave and interior pressure fluctuation of the intercity EMU passing through the tunnel under the condition of large blockage ratio. Based on the three-dimensional transient compressible RANS equation and the SST k-ω turbulence model, the numerical calculation method of pressure wave of the intercity EMU passing through the tunnel was established using the slip grid technology. The pressure wave characteristics of the train passing through the tunnel were studied for different train speeds and different tunnel diameters. The empirical formula was used to calculate the interior pressure fluctuation under different dynamic tightness coefficients. The computational results show that the pressure wave of the intercity EMU passing through the tunnel is mainly determined by the train speed and the blocking ratio, and the influence of the train speed is more significant. With the increase of the train speed, the interior pressure fluctuations of the passenger compartment area and the driver's cab area are significantly increased. The interior pressure fluctuation of the driver's cab area is greater than that of the passenger compartment area. When the train speed is 160 km/h, the interior pressure fluctuations of the passenger compartment area and driver's cab area reach the good standard when the dynamic tightness coefficient reaches 5 s, for the tunnel diameters of 7.2 m and 7.4 m. When the train speed is 200 km/h, the interior pressure fluctuations of the passenger compartment area and driver's cab area reach the good standard when the dynamic tightness coefficient reaches 8 s, for the tunnel diameters of 7.2 m and 7.4 m.

Due to the complicated geometric shape, it's difficult to precisely obtain the aerodynamic force of high-speed trains.Taking numerical and experimental data as the training data, the present work proposed a data-driven rapid prediction model to solve this problem, which utilized the Support Vector Machine (SVM) model to construct a nonlinear implicit mapping between design variables and aerodynamic forces of high-speed train.Within this framework, it is a key issue to achieve the consistency and auto-extraction of design variables for any given streamlined shape.A general parameterization method for the streamlined shape which adopted the idea of step-by-step modeling has been proposed.Taking aerodynamic drag as the prediction objective, the effectiveness of the model was verified.The results show that the proposed model can be successfully used for performance evaluation of high-speed trains.Keeping a comparable prediction accuracy with numerical simulations, the efficiency of the rapid prediction model can be improved by more than 90%.With the enrichment of data for the training set, the prediction accuracy of the rapid prediction model can be continuously improved.Current study provides a new approach for aerodynamic evaluation of high-speed trains and can be beneficial to corresponding engineering design departments.