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Author:

Zhao, Z. (Zhao, Z..) | Lu, Z.-H. (Lu, Z.-H..) | Zhao, Y.-G. (Zhao, Y.-G..)

Indexed by:

EI Scopus SCIE

Abstract:

The conditional simulation of non-Gaussian excitations utilizing records from the monitoring system is of great significance for hazard mitigation. To this end, this paper proposes a novel conditional non-Gaussian simulation method. In this method, the Unified Hermite Polynomial Model (UHPM) is used to describe the transformation relationship between recorded and unrecorded non-Gaussian processes and their underlying Gaussian counterparts. Meanwhile, an explicit transformation model between their correlation functions is also provided. Then, the covariance matrix of Fourier coefficients of the underlying Gaussian processes is constructed. Based on this covariance matrix, the conditional samples of Fourier coefficients are generated and substituted into the Spectral Representation Method (SRM) to perform the conditional simulation of the underlying Gaussian processes. Finally, the conditionally simulated samples of the underlying Gaussian processes are transformed into the non-Gaussian samples by the UHPM. To showcase the precision and efficacy of the proposed method, two numerical examples involving the conditional simulations of non-Gaussian ground motions and non-Gaussian wind pressure coefficients are provided. © 2024 Elsevier Ltd

Keyword:

Spectral representation method Fourier coefficients Unified hermite polynomial model Non-Gaussian Conditional simulation

Author Community:

  • [ 1 ] [Zhao Z.]Department of Civil and Environmental Engineering, National University of Singapore, 1 Engineering Drive 2, Singapore, 117576, Singapore
  • [ 2 ] [Lu Z.-H.]Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, No.100 Pingleyuan, Beijing, 100124, China
  • [ 3 ] [Zhao Y.-G.]Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, No.100 Pingleyuan, Beijing, 100124, China

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Source :

Probabilistic Engineering Mechanics

ISSN: 0266-8920

Year: 2024

Volume: 76

2 . 6 0 0

JCR@2022

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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