Multi-objective optimisation of tunnel parameters in a liquefied sand lens under seismic loads

Author:

Shabani SoltanMoradi Mohammad1ORCID,Azadi Mohammad1ORCID,Jahanian Homayoun1ORCID

Affiliation:

1. Department of Civil Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

Abstract

If underground structures built close to the surface lie within a liquefied sand lens, they will be significantly damaged in the case of a seismic event. To achieve an optimal design in terms of depth, diameter and tunnel lining thickness, it is important to consider factors such as ground subsidence, bending moment and axial forces exerted on the tunnel lining. This study intended to perform multi-objective optimisation of relevant tunnel parameters within a liquefied sand lens location under seismic loads. The Flac3D software was used to model the saturated sand lens and determine changes in pore water pressure and effective tension after lens liquefaction. An artificial neural network was used to find optimal values in the genetic algorithm. All optimal design points were obtained per the target function with a revised non-dominated sorting genetic algorithm II algorithm. The results pertaining to depth, diameter and tunnel lining thickness were in opposition to one another, as reducing ground subsidence resulted in increased bending moment and axial force exerted on the tunnel lining. According to the results, it is possible for the designer of the tunnel to use Pareto charts in order to determine the optimal values regarding tunnel depth, diameter and lining thickness within the liquefied sand lens.

Publisher

Thomas Telford Ltd.

Subject

Geotechnical Engineering and Engineering Geology,Earth and Planetary Sciences (miscellaneous)

Reference25 articles.

1. Analyses of the effect of seismic behavior of shallow tunnels in liquefiable grounds

2. Beheshti K 1998 Study of the Behavior of Saturated Sand Lenses in Soil Layers under Dynamic Loading. MSc thesis Amirkabir University of Technology Tehran, Iran

3. A fast and elitist multiobjective genetic algorithm: NSGA-II

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1. Editorial;Geotechnical Research;2022-12-01

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