Chapter
Jul 20, 2023

Framework to Enable Regional 3D Probabilistic Assessment of Excavation Induced Structural Damage Using a Monte-Carlo Method

ABSTRACT

This paper presents a framework to enable probabilistic assessment for braced excavation-induced structural damage on a regional scale. Random filed models are created to describe the uncertainties of spatially variable ground displacements induced by excavation, and random variables are adopted to model the uncertainties of soil stiffnesses, structural stiffnesses, and building weights. The uncertainties are propagated to the probability distributions of building characteristic tensile strains (εc) through a Monte-Carlo method, in which a 3-dimensional (3D) soil-structure interaction (SSI) model is evaluated in each simulation. With limit state functions defined based on εc, damage probabilities were quantified for all buildings in the region impacted by the excavation. Fragility heatmaps that can be used for estimating the probabilities of each possible damage state from impact level were also generated for each building. The framework is demonstrated with an excavation case history executed in Oslo, Norway. The 3D SSI model adopted in the framework can provide more accurate building response prediction than conventional 2D analysis. Meanwhile, the probabilistic assessment method provides a tool to quantify the uncertainty effect in the building assessment of large excavation construction.

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REFERENCES

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Go to Geo-Risk 2023
Geo-Risk 2023
Pages: 33 - 41

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Published online: Jul 20, 2023

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Jinyan Zhao [email protected]
1Ph.D. Student, Structural Engineering, Mechanics, and Materials, Dept. of Civil and Environmental Engineering, Univ. of California, Berkeley, CA. Email: [email protected]
Stefan Ritter, Ph.D. [email protected]
2Onshore Foundation Section, Norwegian Geotechnical Institute, Oslo, Norway. Email: [email protected]
Matthew J. DeJong, Ph.D. [email protected]
3Structural Engineering, Mechanics, and Materials, Dept. of Civil and Environmental Engineering, Univ. of California, Berkeley, CA. Email: [email protected]

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