Modeling Earthquake-Induced Landslide Risk for Mountain Railway Alignment Optimization

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.