Methodical Procedure for Creating a New Methodology for Assessing the Resilience of Transport Infrastructure

Hoterová, Katarína; Chovančíková, Nikola

doi:10.1016/j.trpro.2021.07.129

Cited by 3 publications

(1 citation statement)

References 6 publications

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“…In other related fields, such as urban resilience and transportation resilience, Chen et al ( 2020 ) put forward that urban resilience should be considered from dimensions of resistance, adaptability and recovery. Hoterová and Chovančíková ( 2021 ) pointed out that robustness, recoverability and adaptability were the critical elements of resilience in the transportation infrastructure system.…”

Section: Development Of Resilience Assessment Modelmentioning

confidence: 99%

Resilience assessment of metro stations against rainstorm disaster based on cloud model: a case study in Chongqing, China

et al. 2022

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Extremely heavy rainfall has posed a significant hazard to urban growth as the most common and disaster-prone natural calamity. Due to its unique geographical location, the metro system is more vulnerable to waterlogging caused by rainstorm disaster. Research on resilience to natural disasters has attracted extensive attention in recent years. However, few studies have focused on the resilience of the metro system against rainstorms. Therefore, this paper aims to develop an assessment model for evaluating metro stations’ resilience levels. Twenty factors are carried out from dimensions of resistance, recovery and adaptation. The methods of ordered binary comparison, entropy weight and cloud model are proposed to build the assessment model. Then, taking Chongqing metro system in china as a case study, the resilience level of 13 metro stations is calculated. Radar charts from dimensions of resistance, recovery, and adaptation are created to propose recommendations for improving metro stations’ resilience against rainstorms, providing a reference for the sustainable development of the metro system. The case study of the Chongqing metro system in china demonstrates that the assessment model can effectively evaluate the resilience level of metro stations and can be used in other infrastructures under natural disasters for resilience assessment.

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Section: Development Of Resilience Assessment Modelmentioning

confidence: 99%

Resilience assessment of metro stations against rainstorm disaster based on cloud model: a case study in Chongqing, China

et al. 2022

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Is Resilient Transportation Infrastructure Low-Carbon? Evidence from High-Speed Railway Projects in China

Wang

Chen

et al. 2022

Computational Intelligence and Neuroscience

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Establishing resilient transport infrastructure is an effective way for cities to deal with external disturbances and uncertainties during rapid urbanization. However, human society is presently facing a series of sustainable development obstacles, where the energy shortage and environmental pollution are catching significant concerns. Hence, it is imperative to investigate the carbon emission of the growing number of resilient transportation infrastructure (RTI) projects. Through extracting the carbon emission factor (CEF), this study built the carbon emission measurement model (CEMM) to evaluate the carbon emission of 26 resilient high-speed railway construction projects in China. The results indicated that the carbon emissions of the entire high-speed railway infrastructure projects in China show regional and social environmental differences. Meanwhile, there are potential correlations and positive relationships between the resilience of the high-speed railway infrastructure projects and their carbon emission. Suggestions and recommendations for governments and construction enterprises are put forward to further improve the resilient and low-carbon development of transportation infrastructure in China.

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Identification of the Key Influencing Factors of Urban Rail Transit Station Resilience against Disasters Caused by Rainstorms

Jiao

Zhang

et al. 2021

Land

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Improving the ability of the urban rail transit system to cope with rainstorm disasters is of great significance to ensure the safe travel of residents. In this study, a model of the hierarchical relationship of the influencing factors is constructed from the resilience perspective, in order to research the action mechanisms of the influencing factors of urban rail transit stations susceptible to rainstorm disaster. Firstly, the concept of resilience and the three attributes (resistance, recovery, and adaptability) are interpreted. Based on the relevant literature, 20 influencing factors are discerned from the 3 attributes of the resilience of urban rail transit stations. Subsequently, an interpretative structural model (ISM) is utilised to analyse the hierarchical relationship among the influencing factors. The key influencing factors of station resilience are screened out using social network analysis (SNA). Combined with ISM and SNA for analysis, the result shows that the key influencing factors are: “Flood prevention monitoring capability”; “Water blocking capacity”; “Flood prevention capital investment”; “Personnel cooperation ability”; “Emergency plan for flood prevention”; “Flood prevention training and drill”; “Publicity and education of flood prevention knowledge”; and “Regional economic development level”. Therefore, according to the critical influencing factors and the action path of the resilience influencing factors, station managers can carry out corresponding flood control work, providing a reference for enhancing the resilience of urban rail transit stations.

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Methodical Procedure for Creating a New Methodology for Assessing the Resilience of Transport Infrastructure

Cited by 3 publications

References 6 publications

Resilience assessment of metro stations against rainstorm disaster based on cloud model: a case study in Chongqing, China

Resilience assessment of metro stations against rainstorm disaster based on cloud model: a case study in Chongqing, China

Is Resilient Transportation Infrastructure Low-Carbon? Evidence from High-Speed Railway Projects in China

Identification of the Key Influencing Factors of Urban Rail Transit Station Resilience against Disasters Caused by Rainstorms

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