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We principally focus on evaluating the local and entire network performance of railway stations for sustainable logistics management in South Korea. Specifically, we aim to address the issue of dealing with vulnerability in logistics dependent on the degree of connectivity. To resolve this issue, we investigate (i) the current level of local railway station sustainability performance from the perspectives of the value of the station (node) and the geographical location (place), and (ii) how railway station network management can prepare for imminent internal and external risks. Integrating node–place analysis and social network analysis approaches, we demonstrate a means of assessing (i) local railway station performance by comparing how one station’s value differs from that of other stations, and (ii) overall railway network performance by measuring the degree of connectivity based on the centrality characteristics. Consequently, we recommend improvement in planning orders considering the degree of local performance and network vulnerability for railway station network sustainability.

Peak shaving is one of the key mechanisms implemented in technically advanced power grids, including rail networks, to reduce the demand for costly power generation during peak hours. Energy storage systems are commonly used for this purpose. This article presents an analysis of peak load reduction using energy storage considering the specifics of the energy operation of the railway network. Two methods of peak shaving are proposed: a variable threshold value and a constant threshold value. The choice of one of them depends on the relationship between the frequency of occurrence of peak loads on the railway line and the charging time of the energy storage system. An innovative predictive analysis of the temporal characteristics of the railway line load was carried out to determine the likelihood of a peak load occurring during the charging of the energy storage system. The Poisson distribution and Long Short-Term Memory method were used to accomplish this task. The first experiment in Poland on peak shaving using a large-scale energy storage system is presented. It was also one of the first high-power installations of this type in the world to directly cooperate with a 3 kV DC traction network.

Floods pose a substantial risk to human well-being. These risks encompass economic losses, infrastructural damage, disruption of daily life, and potential loss of life. This study presents a state-wide and county-level spatial exposure assessment of the Iowa railway network, emphasizing the resilience and reliability of essential services during such disasters. In the United States, the railway network is vital for the distribution of goods and services. This research specifically targets the railway network in Iowa, a state where the impact of flooding on railways has not been extensively studied. We employ comprehensive GIS analysis to assess the vulnerability of the railway network, bridges, rail crossings, and facilities under 100- and 500-year flood scenarios at the state level. Additionally, we conducted a detailed investigation into the most flood-affected counties, focusing on the susceptibility of railway bridges. Our state-wide analysis reveals that, in a 100-year flood scenario, up to 9% of railroads, 8% of rail crossings, 58% of bridges, and 6% of facilities are impacted. In a 500-year flood scenario, these figures increase to 16%, 14%, 61%, and 13%, respectively. Furthermore, our secondary analysis using flood depth maps indicates that approximately half of the railway bridges in the flood zones of the studied counties could become non-functional in both flood scenarios. These findings are crucial for developing effective disaster risk management plans and strategies, ensuring adequate preparedness for the impacts of flooding on railway infrastructure.

Railway network is an integral part of the economy of many countries. Identifying critical network elements can help network executives to take appropriate preventive actions before the occurrence of catastrophic disruptions or to add necessary redundancy to enhance the resilience of the rail network. The criticality of an element or a link is measured by calculating the increased cost or delay when that element is disrupted. In this paper, we proposed a framework for assessing the vulnerability of the freight rail networks by introducing two bi-level models. The first model determines those critical links which have the greatest impact on the routing cost when interdicted, and the next one takes the cost of rescheduling into account, in addition to that of routing, over all origins and destinations. Rerouting effects are already well-captured by existing alternative measures, but this study allows capturing the ramifications of rescheduling measures. The trains are scheduled by a time–space framework considering customer demand, track and station capacities, and time planning horizon. To overcome the difficulty of solving bi-level models, they are converted to single level models. To verify the models and the proposed approach, we considered a case study focused on three disruption scenarios for the railway network of Iran. The accuracy of the obtained results indicates the effectiveness of the proposed methodology. In addition, our method has a very short computational time in comparison with the network scan method (a full enumeration approach).

Urban sprawl has become a notable feature in China. Previous studies have found that railway development has a significant effect on urban sprawl. However, the detailed mechanisms of how railways affect urban sprawl have not been studied in depth. Furthermore, China’s railway system has already formed a network. The network status of cities within the railway network may affect urban sprawl, but few studies have examined this factor. In this context, to explore the effects of railway networks on urban sprawl and the mechanisms of these effects, this study applied the social network analysis (SNA) method to measure the indicators of railway network characteristics and conducted panel model regression with the above indicators using the data from 26 cities from 2011 to 2019 in the Yangtze River Delta (YRD) in China. The main conclusions are as follows: (1) Railway network construction has a significantly positive impact on urban sprawl through the network agglomeration and diffusion mechanisms. (2) The network agglomeration mechanism improves the location condition of the central cities on the railway network, which encourages urban sprawl as an agglomeration pattern. (3) The network diffusion mechanism enhances the integration of the peripheral cities with the central city on the railway network, which encourages urban sprawl as a diffusion pattern. The network diffusion mechanism is heterogeneous in metropolitan areas (MAs) for the different levels of central city agglomeration. The findings provide a reference for railway construction and urban planning.

Based on the big data-assisted algorithm, the paper uses the dynamic relationship data of railway passenger flow as a research case, adopts the urban network chain model, and uses the mobility and agglomeration of railway passenger flow between cities as the research entry point to analyse the network connection strength of provincial cities and spatial organization structure characteristics. At the same time, it puts forward the idea of using Wuhan’s rich railway resources as the framework of urban railway network passenger flow intensity simulation calculation system, demonstrates the necessity and feasibility of its construction, and puts forward an implementation plan based on the characteristics of the railway network and urban development for the reference of relevant decision makers.

The railway network design problem is one of the critical issues in the transportation sector due to its significance and variety of necessary applications. The major issue of this field relates to the decision of whether to increase the railways’ capacity or construct a new route to meet demand. Although the budget is a great concern of the managers for making such a decision, environmental factors should be necessarily included in the decision-making process. Therefore, this research proposes a novel robust bi-objective mixed-integer linear programming (MILP) model to simultaneously minimize the total cost and environmental impact under uncertain conditions and within a given time horizon. The proposed problem addresses strategic and operational decisions through railway project selection and product flow determination. To deal with the bi-objectiveness of the model and tackle the complexity of the problem, a nondominated sorting genetic algorithm (NSGA-II) is employed. The proposed NSGA-II could reach near-optimal Pareto solutions in a reasonable solution time and showed a reliable performance for being employed in large-sized instances. It also indicates that the proposed NSGA-II can be utilized for solving large-sized samples in a very short time.

Good connectivity and accessibility help to enhance the competitiveness of regions and countries. This research provides a detailed analysis of the connectivity and accessibility of the Chinese railway network. The studied period starts in 1949 and ends in 2017. The research scope covers the railway system of the entire country (except Taiwan, Hong Kong, and Macao). Instead of focusing on main cities as research objects, this paper provides more detailed insights by using counties as the basic research units. The analysis shows that the achieved connectivity has been increasing continuously over the study period. Four accessibility indicators (temporal location indicator, weighted average travel time, daily accessibility, and potential indicator) provide comprehensive and complementary results, indicating that the most accessible cities and units are located in the southeastern part of the Hu line. In addition, higher economic level, or higher population density, is correlated with higher accessibility. Furthermore, the current network exhibits an unbalanced spatial distribution pattern, with an underdeveloped west. All the indicators show that the accessibility of the northwest and southwest regions is the lowest. Based on these conclusions, regional policy-making suggestions can be made to guide a rational railway network expansion and facilitate the equality and sustainable economic development of regions. The future railway system development is suggested to focus more on enhancing inner and inter-region communication in the west of China and attach importance to poverty-stricken counties in support of balanced regional growth and development. The railway development of the eastern regions needs to focus on optimizing the structure of the network as well as reasonably organizing railway routes.

Evaluation of the railway network distribution and its impacts on social and economic development has great significance for building an efficient and comprehensive railway system. To address the lack of evaluation indicators to assess the railway network distribution pattern at the macro scale, this study selects eight indicators—railway network density, railway network proximity, the shortest travel time, train frequency, population, Gross Domestic Product (GDP), the gross industrial value above designated size, and fixed asset investment—as the basis of an integrated railway network distribution index which is used to characterize China’s railway network distribution using geographical information system (GIS) technology. The research shows that, in 2015, the railway network distribution was low in almost half of China’s counties and that there were obvious differences in distribution between counties in the east and west. In addition, multiple dense areas of railway network distribution were identified. The results suggest that it might be advisable to strengthen the connections between large and small cities in the eastern region and that the major urban agglomerations in the midwest could focus on strengthening the construction of railway facilities to increase the urban vitality of the western region. This study can be used to guide the optimization of railway network structures and provide a macro decision-making reference for the planning and evaluation of major railway projects in China.

Delving into the spatiotemporal evolution of the railway network in different periods can provide guidance and reference for the planning and layout of the railway network. However, most of the existing studies tended to model the railway data separately and compare the network indices of adjacent periods based on the railway data of different periods, thus failing to integrate the railway network in different periods into a unified framework for evolution analysis. Therefore, this paper used the railway data from 2008, 2010, 2015, and 2019, and analyzed the spatiotemporal integration of the railway network evolution based on the complex network theory and the self-organizing maps (SOM) method. Firstly, this study constructed the geographical railway network in the four years and probed into how the network feature indices changed. Then, it used the SOM method to capture the spatiotemporal integration of the railway network evolution in multi-time series. Finally, it clustered the change trajectory of each city node and unveiled the relationship between the evolution of city nodes and the hierarchy of urban systems. The results show that from 2008 to 2019, the railway network feature indices showed an upward trend and that the expansion pattern of the railway network could be divided into the core–peripheral pattern, belt expansion pattern, strings of beads pattern, and multi-center network pattern. The evolution of the change trajectory of the city nodes was highly related to the hierarchical structure of the urban system. This study helps to understand the evolution process of the railway network in China, and provides decision-making reference for improving and optimizing China’s railway network.