Finite element model updating using Bayesian approach

Tshilidzi Marwala, Lungile Mdlazi, Sibusiso Sibisi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)


This paper compares the Maximum-likelihood method and Bayesian method for finite element model updating. The Maximum-likelihood method was implemented using genetic algorithm while the Bayesian method was implemented using the Markov Chain Monte Carlo. These methods were tested on a simple beam and an unsymmetrical H-shaped structure. The results show that the Bayesian method gave updated finite element models that predicted more accurate modal properties than the updated finite element models obtained through the use of the Maximum-likelihood method. Furthermore, both these methods were found to require the same levels of computational loads.

Original languageEnglish
Title of host publicationIMAC-XXIII
Subtitle of host publicationConference and Exposition on Structural Dynamics - Structural Health Monitoring
Publication statusPublished - 2005
Externally publishedYes
Event23rd Conference and Exposition on Structural Dynamics 2005, IMAC-XXIII - Orlando, FL, United States
Duration: 31 Jan 20053 Feb 2005

Publication series

NameConference Proceedings of the Society for Experimental Mechanics Series
ISSN (Print)2191-5644
ISSN (Electronic)2191-5652


Conference23rd Conference and Exposition on Structural Dynamics 2005, IMAC-XXIII
Country/TerritoryUnited States
CityOrlando, FL


  • Bayesian
  • Finite element updating
  • Maximum-likelihood

ASJC Scopus subject areas

  • General Engineering
  • Computational Mechanics
  • Mechanical Engineering


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