Novel concepts for reliability analysis of dynamic structural systems

J. Ramon Gaxiola-Camacho, Hamoon Azizsoltani, Achintya Haldar, S. Mohsen Vazirizade, Francisco Javier Villegas-Mercado

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

A novel concept for reliability evaluation of nonlinear systems considering dynamic loading applied in time domain is presented. Several improvements of the concept with various degrees of sophistication are also discussed. Structures are represented by finite elements, and various sources of nonlinearity and uncertainty associated with them are incorporated. A number of advanced mathematical concepts are integrated to produce compounding beneficial effects. The basic concept is verified using the Monte Carlo simulation technique. Capabilities of several improvements of the concept are checked with the help of a case study. Following the Northridge earthquake of 1994, a new design concept, known as the performance-based seismic design, was proposed. The implementation potential of the concept is showcased. Multidisciplinary application potential of the concept is also presented. The authors believe that they proposed an alternative to simulation by conducting few deterministic analyses satisfying the most recent trend in engineering design to incorporate various sources of uncertainty.

Original languageEnglish (US)
Title of host publicationHandbook of Probabilistic Models
PublisherElsevier
Pages305-346
Number of pages42
ISBN (Electronic)9780128165140
ISBN (Print)9780128165461
DOIs
StatePublished - Jan 1 2019

Keywords

  • Finite element method
  • First-order reliability method
  • Kriging method
  • Monte carlo simulation
  • Moving least squares method
  • Performance-based seismic design
  • Response surface method

ASJC Scopus subject areas

  • Computer Science(all)

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    Gaxiola-Camacho, J. R., Azizsoltani, H., Haldar, A., Vazirizade, S. M., & Villegas-Mercado, F. J. (2019). Novel concepts for reliability analysis of dynamic structural systems. In Handbook of Probabilistic Models (pp. 305-346). Elsevier. https://doi.org/10.1016/B978-0-12-816514-0.00013-8