INTERNATIONAL JOURNAL OF RAILWAY RESEARCH
Year:2025 | Volume:12 | Issue:2|Papers Count:7

Climate is one of the most important factors in railway infrastructure, and future changes in climate and extreme weather conditions will increase the risks concerning its stability and performance. Understanding and mitigating these risks is vital for ensuring the longevity and safety of railway networks. The research work presented here examines the association of climatic conditions with the geometric degradation of railway lines in Iran using Deep Learning models. The research is based on the geometric data obtained from track measurement machines over 14 years, encompassing track gauge, profile, and twist. These data were matched with meteorological records such as temperature, humidity, rainfall, and wind speed for different regions of Iran. By combining these datasets, deep learning models are developed to analyze and predict the pattern of track degradation resulting from various climatic conditions. The added value of using meteorological data in training predictive models is assessed by comparing the performance of models trained with and without meteorological data. More precisely, one model predicts track degradation without considering meteorological data, while the other includes climatic information. This comparison allows for an evaluation of the effectiveness of weather data in improving the accuracy of track degradation predictions. This research is, therefore, likely to contribute to critical knowledge of how climatic variables influence railway infrastructure, allowing for more realistic forecasts of track life and better planning for maintenance schedules. Given the challenges associated with climate change, the present study addresses the call to develop more resilient railway infrastructure for operational safety across varied climatic conditions.

This paper presents the design and development of a hybrid power supply system for freight railway wagons, aiming to enhance energy autonomy and reduce maintenance requirements. The system utilizes solar energy and rechargeable batteries as primary power sources. An ESP32 microcontroller serves as the central unit, managing energy resources, battery charging and discharging processes, and protecting the connected loads. Additionally, the design includes voltage regulation circuits, current protection mechanisms, and voltage and current sensing modules to ensure precise monitoring and stable operation of the system. Simulation and experimental results confirm the high reliability of the system under various operating conditions and its ability to provide continuous power to the wagon's onboard loads.

Transportation, as a critical sub-sector of the communication infrastructure, constitutes a fundamental pillar of economic development and policy planning. Among the various modes of transportation, rail transport holds a crucial role. Access to smooth, safe, high-speed, efficient and effective rail systems can substantially influence trade development, price stabilization, optimal allocation of scarce resources, increased competition, efficient labor distribution and overall economic development. Accordingly, this study investigates the relationship between selected rail transport indicators and the growth of the transportation sector’s value added in Iran over the period 1997–2023 by using the Vector Autoregressive (VAR) model. The Johansen-Juselius cointegration approach is utilized to estimate the long-run relationships among the variables. The Vector Error Correction Model (VECM) is employed to examine the convergence of the model’s variables and analyzes the short and long-run relationships among them. The obtained results confirm the presence of a long-run relationship among the variables. The number of locomotives, total railway track length, volume of freight transported, and the exchange rate demonstrates a positive influence on the growth of the transportation sector’s value added. Conversely, the inflation rate negatively affects this indicator. The estimated error correction coefficient is 0.12 and indicates that the model converges towards equilibrium, and approximately 8 periods are required to eliminate deviations and align the short-run equilibrium with the long-run steady state.

The phenomenon of unsupported sleepers is considered one of the most critical factors affecting the dynamic performance of ballasted railway tracks. Disrupting the contact between the sleeper and the ballast leads to increased deflection, stress concentration, and reduced track stability. This study aims to numerically analyze and simulate the dynamic effects of unsupported sleepers, focusing on their numbers and layout patterns in the ballasted railway tracks. For this purpose, a three-layer mechanical model consisting of rail, sleeper, and ballast was developed in MATLAB, and its results were compared with an equivalent finite element model created in ABAQUS. The MATLAB model employs mass, stiffness, and damping matrices along with a time-dependent moving load to evaluate the system's response under various unsupported sleeper conditions. In the ABAQUS model, sleepers and ballast were modeled as concentrated masses, with their interactions represented via equivalent spring-damper systems; loading was applied incrementally along the train path. The results indicate that increasing the number of unsupported sleepers—particularly in sequential arrangements—significantly amplifies rail deflection and mid-span stress, with the most critical response observed in the case of three-consecutive-unsupported-sleepers. These findings indicate the necessity of continuous monitoring and preventive maintenance of unsupported zones to ensure track safety and extend structural service life.

Today, paying attention to environmental issues in urban development planning and actions can be an effective step in improving the state of the environment and improving the quality of life of citizens. The country's economic, social, cultural, and political conditions pose challenges for the future of the environment, and examining and identifying these challenges is essential for managing and improving the quality of the environment. Cities are both victims and culprits of environmental changes caused by human activities. Economic growth and industrial development have led to urbanization and an increase in the population of cities around the world. In recent years, environmental concerns such as the excessive use of natural resources, the destruction of wildlife habitats, the extinction of animal species, and various types of pollution have endangered the Earth as a human habitat. Sustainable transportation means finding efficient and easy ways to move people and vehicles with minimal energy consumption and environmental impact. Transportation has widespread negative impacts such as air pollution, noise pollution, heavy traffic, and increased accidents, and valuable urban land is allocated to streets and parking lots. In this article, the environmental impacts of urban rail compared to other transportation systems on air quality, traffic reduction, and accident rates are examined. This research examines and compares the positive and negative impacts of urban rail and other transportation systems from various environmental aspects. The results show that urban rail has positive impacts on the environment and public health by consuming less energy, producing fewer pollutants, and reducing traffic congestion. Also, the reduction of accidents caused by the use of urban railways compared to other public and private means of transportation is one of the important advantages of this transportation system. In contrast, the excessive use of cars and other unsustainable means of transportation have more negative effects on air quality and urban traffic. This article explains the solutions for improving and developing sustainable and efficient transportation systems in cities and points out the importance of using urban railways to preserve the environment and improve the quality of life of citizens.

The railway industry in Iran is one of the country's oldest transport sectors. Over recent decades, efforts have been made to improve its infrastructure, such as connecting major freight hubs to the national rail network, shifting freight transport from road to rail. However, despite its key role in the national logistics system, limited progress has been achieved in modernizing the rolling stock and implementing precise and mechanized loading/unloading operations. This has resulted in resource inefficiencies, loss of freight, and declining confidence among cargo owners in the railway system. Additionally, from an environmental standpoint, inadequate waste and wastewater treatment systems have raised concerns about long-term ecological impacts. Circular economy principles seek to balance economic growth with environmental sustainability by reintegrating recycled materials into production cycles and minimizing ecological degradation. In this study, a network Data Envelopment Analysis (NDEA) model incorporating a centralized structure and cooperative game theory is developed to assess the circular economy performance of railway maintenance companies. The proposed model comprises two interconnected subsystems: the production subsystem, which includes rolling stock washing and repair, and the treatment subsystem, responsible for processing the wastewater and industrial waste produced by the first subsystem. By applying a cooperative game approach, the model enables efficiency evaluation of both subsystems under a unified framework. The proposed methodology is applied to the performance evaluation of Iranian railway maintenance companies during the period 2020–2024 (1399–1403 in the Iranian calendar). The results help identify efficient and inefficient units, offering strategic insights to enhance overall system performance toward best-practice benchmarks.

This paper investigates the performance of a medium-voltage hybrid circuit breaker designed for the protection of electrical power supply networks in railway transportation systems. Two primary topologies, namely LCS (Load Commutation Switch) and CCDC (Current Commutation Drive Circuit), are analyzed for AC and DC networks, respectively. Leveraging recent advancements in semiconductor technology and power electronics, novel approaches are introduced to enhance efficiency and reduce fault-clearing times. The performance of hybrid circuit breakers in medium-voltage AC and DC networks is evaluated using LTspice and PSpice simulation environments. The results demonstrate that the proposed hybrid circuit breaker achieves efficient fault protection with fault-clearing times of less than 10 milliseconds, outperforming conventional systems. Given the critical importance of protection in railway electrical power supply networks, this study proposes enhancements in protective characteristics, particularly in fault-clearing speed, through the application of hybrid circuit breakers.