The existing multi-objective wheel profile optimization methods mainly consist of three sub-modules: (1) wheel profile generation, (2) multi-body dynamics simulation, and (3) an optimization algorithm. For the first module, a comparably conservative rotary-scaling fine-tuning (RSFT) method, which introduces two design variables and an empirical formula, is proposed to fine-tune the traditional wheel

In wheel–rail adhesion studies, most of the test rigs used are simplified designs such as a single wheel or wheelset, but the results may not be accurate. Alternatively, representing the complex system by using a full vehicle model provides accurate results but may incur complexity in design. To trade off accuracy over complexity, a bogie model can be the optimum selection. Furthermore, only a real-time

Construction issues of high-speed rail infrastructures have been increasingly concerned worldwide, of which the subgrade settlement in soft soil area becomes a particularly critical problem. Due to the high compressibility and low permeability of soft soil, the post-construction settlement of the subgrade is extremely difficult to control in these regions, which seriously threatens the operation safety

Conventional maintenance mode for the traction power supply system (TPSS) is to perform scheduled regular maintenance activities for power supply equipment, while such maintenance mode may result in undue maintenance tasks and low efficiency due to different degradation processes of different sorts of equipment. To address this problem, this paper introduces a preventive opportunistic maintenance (POM)

The rapid growth in railway infrastructure and the construction of high-speed heavy-haul rail network, especially on ground that is basically unsuitable, poses challenges for geotechnical engineers because a large part of the money invested in the development of railway lines is often spent on track maintenance. In fact around the world, the mud pumping of subgrade fines is one of the common reasons

To explore the influence of spatially varying ground motion on the dynamic behavior of a train passing through a three-tower cable-stayed bridge, a 3D train–track–bridge coupled model is established for accurately simulating the train–bridge interaction under earthquake excitation, which is made up of a vehicle model built by multi-body dynamics, a track–bridge finite element model, and a 3D rolling

Since the concept of active suspensions appeared, its large possible benefits has attracted continuous exploration in the field of railway engineering. With new demands of higher speed, better ride comfort and lower maintenance cost for railway vehicles, active suspensions are very promising technologies. Being the starting point of commercial application of active suspensions in rail vehicles, tilting

The pantograph and its recess on the train roof are major aerodynamic noise sources on high-speed trains. Reducing this noise is particularly important because conventional noise barriers usually do not shield the pantograph. However, less attention has been paid to the pantograph recess compared with the pantograph. In this paper, the flow features and noise contribution of two types of noise reduction

Increasing railway traffic and energy utilization issues prompt electrified railway systems to be more economical, efficient and sustainable. As regenerative braking energy in railway systems has huge potential for optimized utilization, a lot of research has been focusing on how to use the energy efficiently and gain sustainable benefits. The energy storage system is an alternative because it not

This paper aims to clarify the influence of system spatial variability on train–track interaction from perspectives of stochastic analysis and statistics. Considering the spatial randomness of system properties in geometry, physics and mechanics, the primary work is therefore simulating the uncertainties realistically, representatively and efficiently. With regard to the track irregularity simulation

Three-dimensional compressible flow simulations were conducted to develop a Hyperloop pod. The novelty is the usage of Gamma transition model, in which the transition from laminar to turbulent flow can be predicted. First, a mesh dependency study was undertaken, showing second-order convergence with respect to the mesh refinement. Second, an aerodynamic analysis for two designs, short and optimized

Railway train energy simulation is an important and popular research topic. Locomotive traction force simulations are a fundamental part of such research. Conventional energy calculation models are not able to consider locomotive wheel–rail adhesions, traction adhesion control, and locomotive dynamics. This paper has developed two models to fill this research gap. The first model uses a 2D locomotive

This paper presents a novel method to estimate queue length at signalised intersections using connected vehicle (CV) data. The proposed queue length estimation method does not depend on any conventional information such as arrival flow rate and parameters pertaining to traffic signal controllers. The model is applicable for real-time applications when there are sufficient training data available to

In this paper, the use of recycled tire-derived aggregates (TDA) mixed with ballast material is evaluated in order to reduce the train-induced ground-borne vibrations. For this purpose, a series of field vibration measurements has been carried out at an executed pilot track. The prepared ballast layer was mixed with different percentages of TDA in three sections. Moreover, another test section with

Rock avalanche–debris flows triggered by earthquakes commonly take place in mountainous areas. When entering a body of water, due to good fluidity they can move for some time instead of halting in water. In this study, we proposed a method for calculating the surge height of rock avalanche–debris flows based on momentum balance and designed a series of model tests to validate this method. The experimental

This study seeks to investigate the variations associated with lane lateral locations and days of the week in the stochastic and dynamic transition of traffic regimes (DTTR). In the proposed analysis, hierarchical regression models fitted using Bayesian frameworks were used to calibrate the transition probabilities that describe the DTTR. Datasets of two sites on a freeway facility located in Jacksonville

Adverse weather has a considerable impact on the behavior of drivers, which puts vehicles and drivers in hazardous situations that can easily cause traffic accidents. This research examines how drivers’ perceived risk changes during car following under different adverse weather conditions by using driving simulation experiment. An expressway road scenario was built in a driving simulator. Eleven types

Pedestrian level of service (PLOS) is an important measure of performance in the analysis of existing pedestrian crosswalk conditions. Many researchers have developed PLOS models based on pedestrian delay, turning vehicle effect, etc., using the conventional regression method. However, these factors may not effectively reflect the pedestrians’ perception of safety while crossing the crosswalk. The

Travel time reliability (TTR) is an important measure which has been widely used to represent the traffic conditions on freeways. The objective of this study is to develop a systematic approach to analyzing TTR on roadway segments along a corridor. A case study is conducted to illustrate the TTR patterns using vehicle probe data collected on a freeway corridor in Charlotte, North Carolina. A number

Roundabout is a channelized intersection where traffic moves around a central island, clockwise for left-side driving and anti-clockwise for right-side driving. Efficiently designed roundabouts can handle traffic very smoothly without causing any delay. The capacity of roundabouts used to be calculated by the weaving theory in India. However, calculation of the entry capacity in the recent literature

Short-term prediction of traffic flow is one of the most essential elements of all proactive traffic control systems. The aim of this paper is to provide a model based on neural networks (NNs) for multi-step-ahead traffic prediction. NNs’ dependency on parameter setting is the major challenge in using them as a predictor. Given the fact that the best combination of NN parameters results in the minimum