Optimal intensity measure for seismic performance assessment of shield tunnels in liquefiable and non-liquefiable soils

Abstract

Relating the ground motion intensity measure (IM) and the structural engineering demand parameter is a crucial step in the performance-based earthquake engineering framework. This study investigates the selection of IM for development of probabilistic seismic demand model of urban shield tunnels subjected to earthquake ground motions in liquefiable and non-liquefiable soils. Nonlinear dynamic effective stress analyses are conducted to develop a database of the intensity measures and structural seismic responses exposed to ground shaking and soil liquefaction. Two advanced soil constitutive models (i.e., Pressure DependMultiYield03 and PressureIndependMultiYield for liquefiable and non-liquefiable soils, respectively) are employed to capture the nonlinear behavior. A suite of 23 ground motion intensity measures is selected and assessed based on the evaluation criteria of correlation, efficiency, practicality and proficiency. Eventually, the multi-level fuzzy comprehensive evaluation method is employed to comprehensively consider the four evaluation criteria and establish the optimal ground motion IM suitable for probabilistic seismic demand analysis of shield tunnel structures. The obtained results show that the sustained maximum acceleration is the optimal IM for evaluating the structural seismic response, followed by the peak ground acceleration in both liquefiable and non-liquefiable soils. Peak pseudo velocity spectrum, displacement square integral and Housner spectral intensity are found to be not suitable for the probabilistic seismic demand analysis of shield tunnel structures.

Keywords

Ground motion intensity measures / Shield tunnel / Liquefiable and non-liquefiable soils / Probabilistic seismic demand analysis / Fuzzy optimization

CRediT authorship contribution statement

Yiyao Shen: Writing - original draft, Software, Methodology, Formal analysis, Data curation, Conceptualization. M. Hesham El Naggar: Writing - review & editing, Conceptualization. Dongmei Zhang: Writing - review & editing, Supervision, Funding acquisition, Conceptualization. Zhongkai Huang: Writing - review & editing, Funding acquisition, Formal analysis. Xiuli Du: Supervision, Project administration, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgment

This work presented in this paper was supported by the National Key Research and Development Program of China (Grant No. 2022YFC3800905), the National Natural Science Foundation of China (Grant Nos. 52278384, 52108381, 52238010 and 52090082), the Shanghai Science and Technology Committee Program (Grant No. 22XD1430200), the Fundamental Research Funds for the Central Universities (2022-3-ZD-07), and the Natural Science Foundation of Chongqing, China (No. CSTB2023NSCQ-MSX0808). Any opinions, findings and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the financial supporters.

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