Technical Papers
Jan 23, 2024

Modeling Earthquake-Induced Landslide Risk for Mountain Railway Alignment Optimization

Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10, Issue 2

Abstract

Construction investment and geological risk of a railway project are significantly influenced by the alignment design. Thus, for railways in earthquake-prone regions, the seismic risks should be addressed at the alignment decision-making stage. However, this is a challenging problem that should balance cost and risk appropriately. Especially in mountainous regions, besides direct ground shaking, earthquake-induced landslides greatly threaten railways’ construction and operation. Unfortunately, no existing studies in this field have accounted for that factor. In this paper, a novel potential earthquake-induced landslide risk model is proposed for mountain railway alignment optimization. In this model, a probabilistic seismic hazard analysis, critical acceleration computation, and landslide displacement estimation are first integrated. Together with the consideration of railway structures’ damage states, damage ratios, and restoration functions, the direct and indirect monetary losses caused by landslides to railways with specified alignments are evaluated. Then, the aforementioned analyses are incorporated into a previous cost-risk model and solved with a particle swarm optimization (PSO) algorithm. Finally, the model’s effectiveness is tested in a complex railway example. It is found that the studied region is landslide prone, and railway structures, especially bridges, are vulnerable to landslides. Also, a biobjective analysis reveals the alignments can be more sensitive to risks than to costs. Lastly, according to the detailed engineering outputs, the computer-generated alignment is 11.8% less expensive and 27.2% safer than the best manually designed solution.

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Data Availability Statement

Some data, models, or code generated or used during the study are proprietary or confidential in nature and may only be provided with restrictions. All design data for the case study presented here, such as the railway location, manually-design solution, and topographic and seismic information of the study area, are provided by the China Railway Eryuan Engineering Group. These data were provided to support this research but detailed information cannot be presented in this paper because the proprietary rights belong to that company. However, some alternative topography data can be downloaded from the Geospatial Data Cloud website (http://www.gscloud.cn), and the PGA data can be referred to the Seismic Ground Motion Parameter Zonation Map of China (China Earthquake Administration 2016). These data are available from the corresponding author upon reasonable request.

Acknowledgments

This work is partially funded by the National Key R&D Program of China with Award No. 2021YFB2600403, the National Science Foundation of China (NSFC) with Award No. 52078497, the Ministry of Education of China (MOE) Key Laboratory of High-Speed Railway Engineering, Southwest Jiaotong University (2021 Open Fund), the Open Foundation of National Engineering Laboratory for High Speed Railway Construction with Award No. HSR202103, and the Frontier Cross Research Project of Central South University with Award No. 2023QYJC006. The first author (Taoran Song) deeply appreciates his great friend Hengchao “Henry” Xu’s warm help in assisting his settlement, research, and study at the University of British Columbia, Vancouver.

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Go to ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10Issue 2June 2024

History

Received: Jul 10, 2023
Accepted: Oct 3, 2023
Published online: Jan 23, 2024
Published in print: Jun 1, 2024
Discussion open until: Jun 23, 2024

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Taoran Song
Associate Professor, School of Civil Engineering, Central South Univ., Changsha 410075, China; Associate Professor, National Engineering Research Center of High-Speed Railway Construction Technology, Changsha 410075, China.
Professor, School of Civil Engineering, Central South Univ., Changsha 410075, China; Professor, National Engineering Research Center of High-Speed Railway Construction Technology, Changsha 410075, China (corresponding author). Email: [email protected]
T. Y. Yang
Professor, Dept. of Civil Engineering, Univ. of British Columbia, Vancouver, BC, Canada V6T 1Z4.
Paul Schonfeld, F.ASCE
Professor, Dept. of Civil and Environmental Engineering, Univ. of Maryland, College Park, MD 20742.
Xinjie Wan
Ph.D. Student, School of Civil Engineering, Central South Univ., Changsha 410075, China; Ph.D. Student, National Engineering Research Center of High-Speed Railway Construction Technology, Changsha 410075, China.
Wei Li
Associate Professor, School of Civil Engineering, Central South Univ., Changsha 410075, China; Associate Professor, National Engineering Research Center of High-Speed Railway Construction Technology, Changsha 410075, China; Key Laboratory of High-Speed Railway Engineering, Ministry of Education, Southwest Jiaotong Univ., Chengdu 610032, China.
Zhihui Zhu
Professor, School of Civil Engineering, Central South Univ., Changsha 410075, China; Professor, National Engineering Research Center of High-Speed Railway Construction Technology, Changsha 410075, China.
Hong Zhang
Lecturer, Engineering Research Center of Railway Environment Vibration and Noise Ministry Education, East China Jiaotong Univ., Nanchang 330013, China.
Jianping Hu
Professorate Senior Engineer, China Railway Eryuan Engineering Group Co. Ltd., No. 3, Tongjin Rd., Chengdu 610031, China.

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