Efficient Uncertainty Quantification of Wharf Structures under Seismic Scenarios Using Gaussian Process Surrogate Model

Lei Su, Hua Ping Wan, You Dong, Dan M. Frangopol, Xian Zhang Ling

Research output: Journal article publicationJournal articleAcademic researchpeer-review

6 Citations (Scopus)

Abstract

The scenario-based seismic assessment approach is illustrated within a large-scale pile-supported wharf structure (PSWS). As nonlinear seismic response analysis is computationally expensive, a novel and efficient method is developed to improve and update the traditional simulation methods. Herein, the Gaussian Process (GP) surrogate model is proposed to replace the time-consuming FE model of PSWS, which makes the quantification of uncertainty in seismic response of a large-scale PSWS resulting from structural parameter uncertainty more computationally-efficient. The feasibility of the proposed approach in seismic assessment of a large-scale PSWS under a given seismic scenario is verified by using Monte Carlo simulation.

Original languageEnglish
JournalJournal of Earthquake Engineering
DOIs
Publication statusAccepted/In press - 1 Jan 2018

Keywords

  • Finite Element
  • Pile-Supported Wharf Structure
  • Scenario-Based Seismic Assessment
  • Sobol Sequence
  • Surrogate Model
  • Uncertainty

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Geotechnical Engineering and Engineering Geology

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