Influences of High-Speed Train Speed on Tunnel Aerodynamic Pressures

To comprehensively investigate the characteristics of aerodynamic pressures on a tunnel caused by the whole tunnel passage of a high-speed train at different speeds, we conduct a series of three-dimensional numerical simulations. Based on the field test results obtained by other researchers, the input parameters of our numerical simulation are determined. The process of a high-speed train travelling through a railway tunnel is divided into three stages according to the spatial relationship between the train and tunnel. Stage I: before train nose enters the entrance; Stage II: while the train body runs inside the tunnel; Stage III: after the train tail leaves the exit. The influences of high-speed train speed on the tunnel aerodynamic pressures of these three stages are systematically investigated. The results show that the maximum peak pressure value decreases with increasing distance from the entrance and increases with increasing train speed in Stage I. There is an approximately linear relationship between the three types of maximum peak pressure (positive peak, negative peak, and peak-to-peak pressures) and the power of the train speed in Stage II. These three types of maximum peak pressure values of the points near tunnel portals increase with increasing train speed in Stage III. Moreover, these three types of maximum peak pressure in the tunnel’s middle section at different train speeds are more complex than those near the tunnel portals, and there is one or more turning points due to the superimposed effects of different pressure waves.

A geomechanics classification for the rating of railroad subgrade performance

The type of subgrade of a railroad foundation is vital to the overall performance of the track structure. With the train speed and tonnage increase, as well as environmental changes, the evaluation and influence of subgrade are even more paramount in the railroad track structure performance. A geomechanics classification for subgrade is proposed coupling the stiffness (resilient modulus) and permanent deformation behaviour evaluated by means of repeated triaxial loading tests. This classification covers from fine- to coarse-grained soils, grouped by UIC and ASTM. For this achievement, we first summarize the main models for estimating resilient modulus and permanent deformation, including the evaluation of their robustness and their sensitivity to mechanical and environmental parameters. This is followed by the procedure required to arrive at the geomechanical classification and rating, as well as a discussion of the influence of environmental factors. This work is the first attempt to obtain a new geomechanical classification that can be a useful tool in the evaluation and modelling of the foundation of railway structures.

Emotional artificial neural network (EANN)-based prediction model of maximum A-weighted noise pressure level

Noise is considered one of the most critical environmental issues because it endangers the health of living organisms. For this reason, up-to-date knowledge seeks to find the causes of noise in various industries and thus prevent it as much as possible. Considering the development of railway lines in underdeveloped countries, identifying and modeling the causes of vibrations and noise of rail transportation is of particular importance. The evaluation of railway performance cannot be imagined without measuring and managing noise. This study tried to model the maximum A-weighted noise pressure level with the information obtained from field measurements by Emotional artificial neural network (EANN) models and compare the results with linear and logarithmic regression models. The results showed the high efficiency of EANN models in noise prediction so that the prediction accuracy of 95.6% was reported. The results also showed that in noise prediction based on the neural network-based model, the independent variables of train speed and distance from the center of the route are essential in predicting.

MATLAB Simulation of Current-Carrying Friction between Catenary and Bow Net Of High-Speed Train under Fluctuating Load

The current carrying capacity of pantograph-catenary will also change dynamically with the continuous change of train speed. The influence of internal and external parameters such as running speed, current, pressure and vibration must be fully considered. Based on this, this paper first analyses the action relationship between CRH pantograph-catenary under fluctuating load, then studies the measurement of current carrying friction between CRH pantograph-catenary under fluctuating load, and finally gives the MATLAB simulation of current carrying friction between pantograph-catenary under fluctuating load.

CFD model to assess parameters influencing piston wind in a subway tunnel and station

Quantifying the train-induced wind affecting the climate of subway stations can be applied to improve underground networks air quality. In this paper, numerical simulations of train-induced airflow in a subway station are performed, using a CFD model with dynamic meshing techniques. A preliminary study is done in a double-track tunnel with blockage ratios of 0.30, 0.37 and 0.46 with a train running at constant speed in the order of 10 m/s. The tunnel length necessary to obtain a stable flow around the train body is determined, and this upstream tunnel length is included in a subway station model. Two different architectures and three train speeds are simulated, and the effect of these configurations on the station airflow is evaluated through the air velocity and the mass flow rate at a location on the platform. The results evidence an increase in air circulation with blockage ratio and train speed.

Conceptual exploration of power peak shaving by smart train operation in rail freight transport

Powerful electric locomotives with high traction performance are foreseen to be used to boost the overall performance of freight transport. However, they would exert extra burden on the power supply system, so the power peak demand would be a bottleneck for future freight transport. To avoid large-scale modifications to the existing systems but ensure operational reliability, this study investigates the formation of power peaks and explores power peak shaving concepts to let the existing systems be more reliable and accommodate more freight traffic. Different from many previous studies which focus on energy saving, this study aims at lowering the power peak demand by “smart train operation”, i.e. altering the train speed profile without compromising running time. This study is mainly performed by simulation based on a standardized freight operation with full regenerative braking used. But this study also shows a real case study based on measurement data of power history from an onboard energy meter. The study shows the formation of power peaks in different conditions and suggests some possible measures to shave the power peak demand. The study also shows that there is a compromise between power peak shaving and energy saving, to which more attention is needed in future studies.

Notch-based speed trajectory optimisation for high-speed railway automatic train operation

Automatic train operation (ATO) systems are fast becoming one of the key components of the intelligent high-speed railway (HSR). Designing an effective optimal speed trajectory for ATO is critical to guide the high-speed train (HST) to operate with high service quality in a more energy-efficient way. In many advanced HSR systems, the traction/braking systems would provide multiple notches to satisfy the traction/braking demands. This paper modelled the applied force as a controlled variable based on the selection of notch to realise a notch-based train speed trajectory optimisation model to be solved by mixed integer linear programming (MILP). A notch selection model with flexible vertical relaxation was proposed to allow the traction/braking efforts to change dynamically along with the selected notch by introducing a series of binary variables. Two case studies were proposed in this paper where Case study 1 was conducted to investigate the impact of the dynamic notch selection on train operations, and the optimal result indicates that the applied force can be flexibly adjusted corresponding to different notches following a similar operation sequence determined by optimal train control theory. Moreover, in addition to the maximum traction/braking notches and coasting, medium notches with appropriate vertical relaxation would be applied in accordance with the specific traction/braking demands to make the model feasible. In Case study 2, a comprehensive numerical example with the parameters of CRH380AL HST demonstrates the robustness of the model to deal with the varying speed limit and gradient in a real-world scenario. The notch-based model is able to obtain a more realistic optimal strategy containing dynamic notch selection and speed trajectory with an increase (1.622%) in energy consumption by comparing the results of the proposed model and the non-notch model.