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Resilience Assessment of Shanxi, Shandong, Henan, and Hebei Expressway Networks Incorporating Dynamic Indicators
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Ying-fei FAN1, 2, Rui-zhe HU1, Rui-jie LI3, Zhi-xuan JIA1, 2
Science Technology and Engineering | 2025, 25(20) : 8696 - 8706
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Science Technology and Engineering | 2025, 25(20): 8696-8706
Papers·Traffics and Transportations
Resilience Assessment of Shanxi, Shandong, Henan, and Hebei Expressway Networks Incorporating Dynamic Indicators
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Ying-fei FAN1, 2, Rui-zhe HU1, Rui-jie LI3, Zhi-xuan JIA1, 2
Affiliations
  • 1 School of Vehicle and Traffic Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China
  • 2 Smart Transportation Laboratory of Shanxi Province, Taiyuan 030024, China
  • 3 School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 611756, China
Published: 2025-07-18 doi: 10.12404/j.issn.1671-1815.2406547
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The evaluation of expressway network resilience has been emphasized due to significant global emergencies. Utilizing complex network theory and the resilience triangle model, a dynamic system was developed to assess the comprehensive performance of nodes, incorporating local, global, and social attributes. A method for evaluating the resilience of expressway networks was proposed, consisting of four stages: initial, disruption, recovery, and stabilization. Six disruption and recovery strategies (node degree, eigenvector, betweenness, accessibility, social attributes, and random selection) were applied to analyze the network’s performance using three key indicators: the number of independent paths, network efficiency, and network connectivity. A topological map of the expressway network spanning the provinces of Shanxi, Shandong, Henan, and Hebei were constructed, and the resilience changes under various disruption and recovery strategies were analyzed. The findings indicate that in the initial stage, the expressway network exhibits a relatively high number of independent paths, suggesting robust anti-risk capabilities. During the disruption stage, network efficiency, the number of independent paths, and network connectivity decrease by 94.32%, 98.18%, and 99.63%, respectively, demonstrating the network’s ability to absorb disruptions. In the recovery stage, the accessibility restoration strategy, which results in the smallest resilience triangle area, exhibits the strongest resilience, whereas the random restoration strategy shows the slowest recovery rate, indicating that it should be avoided whenever possible. In the stabilization stage, network efficiency resilience is found to be superior to that of network connectivity and independent path resilience in the expressway network of the four provinces. It is recommended that urban nodes with higher degree values, such as Xinxiang and Puyang, be prioritized for protection to enhance the overall resilience of the expressway network.

highway transportation  /  social attributes  /  comprehensive node performance  /  complex network  /  resilience assessment
Ying-fei FAN, Rui-zhe HU, Rui-jie LI, Zhi-xuan JIA. Resilience Assessment of Shanxi, Shandong, Henan, and Hebei Expressway Networks Incorporating Dynamic Indicators[J]. Science Technology and Engineering, 2025 , 25 (20) : 8696 -8706 . DOI: 10.12404/j.issn.1671-1815.2406547
Year 2025 volume 25 Issue 20
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Article Info
doi: 10.12404/j.issn.1671-1815.2406547
  • Receive Date:2024-09-01
  • Online Date:2026-05-13
  • Published:2025-07-18
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  • Received:2024-09-01
  • Revised:2025-04-25
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Affiliations
    1 School of Vehicle and Traffic Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China
    2 Smart Transportation Laboratory of Shanxi Province, Taiyuan 030024, China
    3 School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 611756, China
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表12种不同金属材料的力学参数

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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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