Search Results (116)

Hyperloop ultra-high-speed transport presents a transformative opportunity for future mobility systems in smart cities. However, assessing its socio-economic impact remains challenging due to Hyperloop’s unique technological, modal, and operational characteristics. As a novel, fifth mode of transportation—distinct from both aviation and rail—Hyperloop requires tailored evaluation tools for policymakers. This study proposes a custom-designed framework to quantify its macroeconomic effects through changes in gross domestic product (GDP) at the city level. Unlike traditional economic models, the proposed approach is specifically adapted to Hyperloop’s multimodality, infrastructure, speed profile, and digital-green footprint. A Poisson pseudo-maximum likelihood (PPML) model is developed and applied at two technology readiness levels (TRL-6 and TRL-9). Case studies of Glasgow, Berlin, and Busan are used to simulate impacts based on geo-spatial features and city-specific trade and accessibility indicators. Results indicate substantial GDP increases driven by factors such as expanded 60 min commute catchment zones, improved trade flows, and connectivity node density. For instance, under TRL-9 conditions, GDP uplift reaches over 260% in certain scenarios. The framework offers a scalable, reproducible tool for policymakers and urban planners to evaluate the economic potential of Hyperloop within the context of sustainable smart city development. Full article

The safety of lithium-ion batteries during transportation is critically important. However, current standards exhibit limitations, as their environmental testing parameter thresholds fail to fully encompass actual transportation conditions. To enhance both safety and standard applicability, in this study, we focused on four representative environmental conditions: temperature, vibration, shock, and low atmospheric pressure. Field measurements were conducted across road, rail, and air transport modes using a self-developed data acquisition system based on the NearLink communication technology. The measured data were then compared with the threshold values defined in current international and national standards. The results reveal that certain measured values exceeded the upper limits prescribed by existing standards, indicating limitations in their applicability under extreme transport conditions. Based on these findings, we propose revised testing parameters that better reflect actual transport risks, including a temperature cycling range of 72 ± 2 °C (high) and −40 ± 2 °C (low), a shock acceleration limit of 50 gn, adjusted peak frequencies in the vibration PSD profile, and a minimum pressure threshold of 11.6 kPa. These results provide a scientific basis for optimising safety standards and improving the safety of lithium-ion battery transportation. Full article

To investigate how severe wear at No. 12 turnout frogs in an urban rail transit line operating at speeds over 120 km/h on the dynamic performance of the vehicle, a vehicle–frog coupled dynamic model was established by employing the 2021 version of SIMPACK software. Profiles of No. 12 alloy steel frogs and metro wheel rims were measured to simulate wheel–rail interactions as the vehicle traverses the turnout, using both brand-new and worn frog conditions. The experimental results indicate that increased service life deepens frog wear, raises equivalent conicity, and intensifies wheel–rail forces. When a vehicle passes through the frog serviced for over 17 months at the speed of 120 km/h, the maximum derailment coefficient, lateral acceleration of the car body, and lateral and vertical wheel–rail forces increased by 0.14, 0.17 m/s², 9.52 kN, and 105.76 kN, respectively. The maximum contact patch area grew by 35.73%, while peak contact pressure rose by 236 MPa. To prevent dynamic indicators from exceeding safety thresholds and ensure train operational safety, it is recommended that the frog maintenance cycle be limited to 12 to 16 months. Full article

For a given timetable in urban rail transit systems, this paper presents a practical energy efficiency optimization problem that carries out adjustments to the timetable, with the goal of energy saving. We propose two strategies to address this challenge, including adjusting the section running time by selecting a speed profile and improving the utilization of regenerative braking energy by adjusting the trains’ departure time. Constraints on the range of adjustment for energy-efficient time elements are constructed for maintaining the stability of elements of the given timetable. An energy efficiency optimization model is then established to minimize the total net energy consumption of the timetable, and a solution algorithm based on a genetic algorithm is proposed. We make small-scale adjustments to trains’ running trajectories to optimize the overlap time of braking and traction conditions among multiple trains. The case of the Guangzhou Metro Line 8 in China is presented to verify the effectiveness and practicality of our method. The results show that the consumption of traction energy is reduced by 0.95% and the use of regenerative braking energy is increased by 8.18%, with an improvement in energy efficiency of 6.78%. This method can achieve relatively significant energy efficiency results while ensuring the stable service quality of the train timetable and can provide support for an energy-efficient train timetable for urban rail transit operation enterprises. Full article

The muzzle velocity of electromagnetic rail launchers approaches 1550 m/s, exhibiting typical hypervelocity electrical contact characteristics. During the electromagnetic launching process, extreme conditions, such as high current density, high temperature rise, and strong strain can cause wear on the surfaces of the armature and rail. Electromagnetic launch tests are conducted to study the wear conditions of the rail surface and the relationship between the wear state and contact resistance. After the rail is abraded by hundreds of launching armatures, its surface 2D profile and morphological characteristics are measured and analyzed. Based on fractal theory, the static contact resistance model is developed. Concurrently, the contact resistance at various positions is measured to reveal the evolution of the static contact resistance between the armature and the rail under wear. The research results show that along the direction of the armature launch, the rail surface wear transitions from mechanical wear to electrical wear, the fluctuation range of the 2D profile becomes smoother, and the roughness of the rail surface shows a decreasing trend. When the roughness is greater, the contact resistance is more sensitive to changes in external load. Full article

The rapid development of electric transport necessitates efficient energy storage and redistribution in traction systems. A key challenge is the utilization of regenerative braking energy, which is often dissipated in resistors due to network saturation and limited consumption capacity. The paper addresses the problem of inefficient energy utilization in electric rail vehicles due to the absence of effective energy recovery mechanisms. A specific challenge arises when managing energy recuperated during regenerative braking, which is typically lost if not immediately reused. This study proposes the integration of on-board energy storage systems (ESS) based on supercapacitor technology to temporarily store excess braking energy. A mathematical model of a traction drive with a DC motor and supercapacitor-based ESS is developed, accounting for variable load profiles and typical urban driving cycles. Simulation results demonstrate potential energy savings of up to 30%, validating the feasibility of the proposed solution. The model also enables system-level analysis for optimal ESS sizing and placement in electric rail vehicles. Full article

This article presents a mathematically grounded approach to increasing the operational reliability of current collectors in electric transport systems by ensuring a constant contact force between the collector shoe and the power rail. The core objective is achieved through the development and analysis of a mechanical system incorporating spring and cam elements, which is specifically designed to provide a nearly invariant contact pressure under varying operating conditions. A set of equilibrium equations was derived to determine the stiffness ratios of the springs and the geometric conditions under which the contact force remains constant despite wear or displacement. Additionally, the paper introduces a method for synthesizing the cam profile that compensates for nonlinear spring deformation, ensuring force constancy over a wide range of movement. The analytical results were validated through parametric simulations, which assessed the influence of wear depth, rail inclination, and external vibrations on the system’s force output. These simulations, executed within a numerical framework using scientific computing tools, demonstrated that the deviation of the contact force does not exceed a few percent under typical disturbances. Experimental verification further confirmed the theoretical predictions. The study exemplifies the effective use of mathematical modeling, nonlinear mechanics, and numerical methods in the design of energy transmission components for transport applications, contributing to the development of robust and maintainable systems. Full article

The smooth area on the rail surface causes abnormal exposure in the laser section image, resulting in measurement errors of the rail profile. To address this issue, a novel rail profile measurement technique based on polarization fusion imaging is proposed. A polarized camera is utilized to acquire the four-directional polarization component images, Stokes parameter images, linear polarization angle images, and linear polarization degree images of the rail laser section. A polarization image data fusion algorithm based on Segmented Random Sample Consensus (S-RANSAC) is designed using these images as data sources, and the optimal rail profile fitting curve is obtained. Experimental results demonstrate that the proposed method can still obtain accurate and effective rail profile data in regions where traditional methods fail to capture profile data. Compared with the traditional method, the measurement error of the rail profile is reduced from 0.137 mm to 0.081 mm, and the measurement accuracy is improved by 40.9%. Evidently, this method avoids data loss in key areas of the rail profile caused by local underexposure, thus significantly enhancing the measurement accuracy. This method can provide a valuable reference for high-precision measurement of the rail profile under complex working conditions. Full article

This study addresses the critical environmental challenge of increasing carbon emissions from Thailand’s freight transport sector, focusing on container movement in the strategic Lat Krabang ICD–Laem Chabang Port corridor. The research quantifies and compares CO₂ emissions between rail and road container transport modes to identify potential carbon reduction strategies. A comprehensive activity-based methodology was employed, incorporating fuel consumption testing across multiple load conditions, detailed transport activity mapping, and the application of locally relevant emission factors. The results demonstrate that rail transport produces 32.82 kgCO₂eq/TEU compared to 53.13 kgCO₂eq/TEU for road transport, representing a 38.23% emission advantage. Fuel consumption testing revealed a power relationship between train weight and fuel consumption (y = 0.1121x^0.5147, R² = 0.97), indicating improving efficiency with increased loading. Terminal operations contribute significantly to rail transport’s emission profile, accounting for 36% of total emissions. The current modal split presents substantial opportunities for emission reduction through increased rail utilization. This study identifies and evaluates practical carbon reduction strategies across operational, technological, and policy dimensions, with priority interventions including load factor optimization, terminal efficiency improvements, locomotive modernization, and differential road pricing. This research contributes empirical evidence to support sustainable freight transport development in Thailand while establishing a methodological framework applicable to emission assessments in similar corridors throughout developing economies. Full article

The gear-transmission system plays a crucial role in power transmission for urban railway vehicles. However, it can experience abnormal meshing conditions due to wheel polygonization, which presents a potential safety hazard for vehicle operations. To address this issue, the present study develops a dynamic model of an urban railway vehicle that integrates the gear-transmission system, simulating the effects of wheel polygonization on its dynamic behavior. The simulation results reveal that as the amplitude of wheel polygonization and vehicle speed increase, the vertical wheel–rail force, gear-meshing force, and dynamic transmission error (DTE) escalate. Furthermore, an increase in the order of wheel polygonization leads to a rise in the vertical wheel–rail force. In contrast, the gear-meshing force and DTE exhibit distinct trends at different speeds. At a speed of 20 km/h, these parameters increase by 51.34% and 0.29%, respectively. As the speed increases, the peaks of gear-meshing force and DTE occur at the 7th-order and 3rd-order polygon, respectively, suggesting that the dynamic response of the gear-transmission system becomes more sensitive to lower-order polygon effects at higher speeds, which necessitates greater attention during operation. Additionally, the phase difference of wheel polygonization exerts a significant influence on gear-meshing force under various conditions, such as in-phase, out-of-phase, 60° phase difference, and 120° phase difference. Therefore, in engineering applications, it is essential to consider the phase difference of wheel polygonization to alleviate excessive gear-meshing forces and ensure stable transmission performance. The findings of this paper offer insights into the dynamic evaluation and wheelset re-profiling of gear-transmission systems in urban railway vehicles. Full article

A mechanical beam-scanning reflectarray (RA) antenna is presented for Ka band. The 1D steering of the beam is achieved through linear in-plane panel translations, which can be implemented at low cost using a rail-mounted moving RA panel. Compared to related works, a highly uniform beam level is achieved with a remarkably compact antenna profile. A new technique is also proposed to mitigate the high side lobes caused by the compact antenna optics, achieving an estimated 2.3 dB reduction in maximum SLL. The manufactured prototype has a panel size of 256.4 by 187.2 mm with 2898 elements, and an $F/D$ of only 0.47. A measured scan loss of 1.1 dB is achieved over a 45-degree scanning range. The measured gain is 31.6 dBi and the aperture efficiency is 24.7% at the design frequency of 29.5 GHz, with SLL between −9.4 and −17.5 dB. In-band measurements show a 1 dB bandwidth from 28 to over 32 GHz (11.9%). Full article

Hollow wear on wheels is a common form of surface damage often observed in high-velocity vehicles. It is widely recognized that hollow wear of the wheel tread degrades the dynamic performance of rail vehicles, especially in the issue commonly referred to as “operational stability”, and leads to abnormal wheel–rail contact interactions. However, the evaluation criteria for vehicle stability are not uniform, which affects the assessment of wheel conditions and the timing of wheel re-profiling during maintenance. Therefore, numerical simulations were conducted by matching the measured worn wheel profiles with standard rails, and three different methods were employed to evaluate vehicle stability in this article. The numerical results revealed that the wheel equivalent conicity exhibits a nonlinear characteristic caused by hollow wear, which means that the nominal equivalent conicity is unable to accurately represent the geometric contact relationship between the wheel and rail. Under identical wheel wear conditions, a certain difference was observed in the critical speed of the vehicle determined by the velocity-reducing method and the bifurcation configuration method. Both methods were capable of reflecting the impact of wheel hollow wear on vehicle stability at the critical speed. Compared to the velocity-reducing method, the bifurcation configuration method can better reflect the transition process of a vehicle from stable running to hunting instability. Furthermore, the lateral vibration acceleration values measured above the bogie frame indicated that slight wheel wear is insensitive to increased speed. However, when the wear was severe, the lateral vibration acceleration of the bogie was found to increase sharply, exceeding the established stability criteria. This phenomenon was consistent with the safety alarms that occurred during actual vehicle operation, indicating that the vehicle had failed to meet stability requirements. Full article

This paper introduces a comprehensive and publicly accessible data set from an experimental study on an independent cart system powered by linear motors. The primary objective is to advance research in machine health monitoring, predictive maintenance, and stochastic modeling by providing the first data set of its kind. Vibration signals were collected using sensors placed along the track, alongside key system variables such as cart position, following error, speed, and set current. Experiments were conducted under a wide range of operating conditions, including different fault types, fault severities, cart speeds, and fault orientations, for both single-cart and multi-cart configurations. The data set captures the relationship between vibration signatures, system variables, and fault characteristics across diverse speed profiles. The data set includes inner race (IR) and outer race (OR) faults in both the top and bottom bearings, with fault severities of 0.25 mm, 0.5 mm, 1.0 mm, and 1.5 mm in width. Eight different types of experiments were performed, classified based on the number of carts used, the section of the guide rail traversed, and the type of movement exhibited. Each experiment was conducted at two distinct nominal speeds of 1000 mm/s and 2000 mm/s, with acquisition durations ranging from 30 s to 2 min. Many experiments included multiple realizations to ensure statistical reliability. Data were recorded at a sampling frequency of 50 kHz with a resolution of 24 bits. For single-cart experiments, 5 system variables were captured, while for three-cart experiments, 15 system variables were recorded along with nine vibration channels. The total data set is approximately 400 GB, offering an extensive resource for data-driven research. Independent cart systems present unique challenges such as non-synchronous operation, speed reversals, and modularity, with each cart containing multiple bearings. In industrial applications where hundreds of carts may operate simultaneously, monitoring a large number of bearings becomes highly complex, making fault identification and localization particularly difficult. Unlike conventional rotary systems, where bearings are fixed around a rotating shaft, independent cart systems involve bearings that both rotate and translate along the track. This fundamental difference makes existing data sets and methodologies inadequate, emphasizing the need for specialized research. By addressing this gap, this work provides a critical resource for benchmarking and developing novel algorithms for fault diagnosis, signal processing, and machine learning in industrial transport applications. The outcomes of this study lay the foundation for future research in the condition monitoring of linear motor-driven transport systems. Full article

The long-term overextraction of groundwater in the Beijing–Tianjin–Hebei region has led to the formation of the world’s largest groundwater depression cone and the most extensive land subsidence zone, posing a potential threat to the operational safety of high-speed railways in the region. As a critical transportation hub connecting Beijing and the Xiong’an New Area, the Beijing–Xiong’an Intercity Railway traverses geologically complex areas with significant ground subsidence issues. Monitoring and analyzing the causes of land subsidence along the railway are essential for ensuring its safe operation. Using Sentinel-1A radar imagery, this study applies PS-InSAR technology to extract the spatiotemporal evolution characteristics of ground subsidence along the railway from 2016 to 2022. By employing a buffer zone analysis and profile analysis, the subsidence patterns at different stages (pre-construction, construction, and operation) are revealed, identifying the major subsidence cones along the Yongding River, Yongqing, Daying, and Shengfang regions, and their impacts on the railway. Furthermore, the XGBoost model and SHAP method are used to quantify the primary influencing factors of land subsidence. The results show that changes in confined water levels are the most significant factor, contributing 34.5%, with strong interactions observed between the compressible layer thickness and confined water levels. The subsidence gradient analysis indicates that the overall subsidence gradient along the Beijing–Xiong’an Intercity Railway currently meets safety standards. This study provides scientific evidence for risk prevention and the control of land subsidence along the railway and holds significant implications for ensuring the safety of high-speed rail operations. Full article

Severe changes in the profiles of the crossing nose are caused by large dynamic contact forces. To predict these forces as well as the profile evolution, the Whole System Model (WSM) was developed. However, it uses computationally expensive FE simulations. As a replacement, the semi-physical plasticity and wear model (SPPW) has been developed, thus majorly enhancing the overall performance of the WSM. The SPPW considers the influence of wear, plasticity, and wheel-profile-related effects. Its results have shown an overall good correlation with FE results, laboratory data for different materials, and field data from a real crossing. Due to the semi-physical nature of the model, the required computational time for the predictions was significantly reduced compared to FE simulations: minutes instead of weeks. The SPPW will be useful for time-efficient rail damage prediction, like wear and plastic deformation, and, as part of the WSM, contribute to a fast holistic track damage prognosis. Full article