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Railway Alignment Optimization in Mountainous Regions Considering Spatial Geological Hazards: A Sustainable Safety Perspective

Author

Listed:
  • Hao Pu

    (School of Civil Engineering, Central South University, Changsha 410075, China
    National Engineering Laboratory for High-Speed Railway Construction, Changsha 410075, China)

  • Jia Xie

    (School of Civil Engineering, Central South University, Changsha 410075, China
    National Engineering Laboratory for High-Speed Railway Construction, Changsha 410075, China)

  • Paul Schonfeld

    (Department of Civil and Environmental Engineering, University of Maryland, College Park, MD 20742, USA)

  • Taoran Song

    (School of Civil Engineering, Central South University, Changsha 410075, China
    National Engineering Laboratory for High-Speed Railway Construction, Changsha 410075, China)

  • Wei Li

    (School of Civil Engineering, Central South University, Changsha 410075, China
    National Engineering Laboratory for High-Speed Railway Construction, Changsha 410075, China)

  • Jie Wang

    (China Railway First Survey and Design Institute Group Co. Ltd., Xi’an 710043, China
    State Key Laboratory of Rail Transit Engineering Informatization, Xi’an 710043, China)

  • Jianping Hu

    (China Railway Eryuan Engineering Group Co. Ltd., Chengdu 610031, China)

Abstract

Sustainable railway construction and operation are threatened by densely occurring geological hazards in complex mountainous regions. Thus, during the alignment optimization process, it is vital to reduce the harmful impacts of geological hazards to a railway. However, current alignment-related studies solely consider such threats in existing geological hazard regions and, outside these regions, slight attention has been devoted to the assessment of potential hazardous impacts along the alignment. To this end, this paper proposes a novel railway alignment optimization model considering both existing and potential geological hazards based on quantitative geological hazard evaluation criteria from a sustainable safety perspective. More specifically, a geohazard zone classification method, within which an energy–slope model is integrated, is first developed. Three geohazard regions, namely the geohazard outbreak region, buffer region and fuzzy region, can then be obtained. Afterward, a spatial geological hazard assessment model is constructed considering the geological danger of three kinds of geohazards (debris flows, landslides and rockfalls) and railway construction vulnerability. This model is incorporated into a previous cost–hazard bi-objective alignment optimization model. Finally, the effectiveness of the proposed model is verified by applying it to a real-life case of the Sichuan–Tibet railway. The results show that this method can effectively optimize mountain railway alignments by concurrently reducing geological hazards and costs, which is beneficial to railway safety and sustainable construction and operation.

Suggested Citation

  • Hao Pu & Jia Xie & Paul Schonfeld & Taoran Song & Wei Li & Jie Wang & Jianping Hu, 2021. "Railway Alignment Optimization in Mountainous Regions Considering Spatial Geological Hazards: A Sustainable Safety Perspective," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:4:p:1661-:d:492991
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    References listed on IDEAS

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    1. Kim, Eungcheol & Jha, Manoj K. & Son, Bongsoo, 2005. "Improving the computational efficiency of highway alignment optimization models through a stepwise genetic algorithms approach," Transportation Research Part B: Methodological, Elsevier, vol. 39(4), pages 339-360, May.
    2. Mohammad Mahanpoor & Saeed Monajjem & Vahid Balali, 2019. "Sustainable Highway Maintenance: Optimization of Existing Highway Vertical Alignment Considering Pavement Condition," Sustainability, MDPI, vol. 11(6), pages 1-20, March.
    3. Jong, Jyh-Cherng & Schonfeld, Paul, 2003. "An evolutionary model for simultaneously optimizing three-dimensional highway alignments," Transportation Research Part B: Methodological, Elsevier, vol. 37(2), pages 107-128, February.
    4. Pushak, Yasha & Hare, Warren & Lucet, Yves, 2016. "Multiple-path selection for new highway alignments using discrete algorithms," European Journal of Operational Research, Elsevier, vol. 248(2), pages 415-427.
    5. Jha, Manoj K. & Schonfeld, Paul, 2004. "A highway alignment optimization model using geographic information systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(6), pages 455-481, July.
    6. L. Sharma & Nilanchal Patel & M. Ghose & P. Debnath, 2015. "Development and application of Shannon’s entropy integrated information value model for landslide susceptibility assessment and zonation in Sikkim Himalayas in India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(2), pages 1555-1576, January.
    7. Casalí, J. & Gastesi, R. & Álvarez-Mozos, J. & De Santisteban, L.M. & Lersundi, J. Del Valle de & Giménez, R. & Larrañaga, A. & Goñi, M. & Agirre, U. & Campo, M.A. & López, J.J. & Donézar, M., 2008. "Runoff, erosion, and water quality of agricultural watersheds in central Navarre (Spain)," Agricultural Water Management, Elsevier, vol. 95(10), pages 1111-1128, October.
    8. Sang-Guk Yum & Sungjin Ahn & Junseo Bae & Ji-Myong Kim, 2020. "Assessing the Risk of Natural Disaster-Induced Losses to Tunnel-Construction Projects Using Empirical Financial-Loss Data from South Korea," Sustainability, MDPI, vol. 12(19), pages 1-15, September.
    9. Nicky J. Welton & Howard H. Z. Thom, 2015. "Value of Information," Medical Decision Making, , vol. 35(5), pages 564-566, July.
    10. B. Palma & M. Parise & P. Reichenbach & F. Guzzetti, 2012. "Rockfall hazard assessment along a road in the Sorrento Peninsula, Campania, southern Italy," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 61(1), pages 187-201, March.
    11. Guido Marseglia & Carlo Maria Medaglia & Francisco A. Ortega & Juan A. Mesa, 2019. "Optimal Alignments for Designing Urban Transport Systems: Application to Seville," Sustainability, MDPI, vol. 11(18), pages 1-14, September.
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    Cited by:

    1. Yiming Cao & Hengxing Lan & Langping Li, 2023. "Disaster Risk Assessment for Railways: Challenges and a Sustainable Promising Solution Based on BIM+GIS," Sustainability, MDPI, vol. 15(24), pages 1-27, December.
    2. Shumin Bai & Xiaofeng Ji & Bingyou Dai & Yongming Pu & Wenwen Qin, 2022. "An Integrated Model for the Geohazard Accident Duration on a Regional Mountain Road Network Using Text Data," Sustainability, MDPI, vol. 14(19), pages 1-19, September.
    3. Meng Zhang & Jiatong Ling & Buyun Tang & Shaohua Dong & Laibin Zhang, 2022. "A Data-Driven Based Method for Pipeline Additional Stress Prediction Subject to Landslide Geohazards," Sustainability, MDPI, vol. 14(19), pages 1-16, September.

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