Title: Model updating incorporating measured response uncertainties and confidence levels of tuning parameters

Authors: K.A. Tharindu L. Kodikara; Tommy H.T. Chan; Andy Nguyen; David P. Thambiratnam

Addresses: School of Civil Engineering and Built Environment, Queensland University of Technology, Brisbane, Australia ' School of Civil Engineering and Built Environment, Queensland University of Technology, Brisbane, Australia ' School of Civil Engineering and Built Environment, Queensland University of Technology, Brisbane, Australia ' School of Civil Engineering and Built Environment, Queensland University of Technology, Brisbane, Australia

Abstract: Automated model updating of real civil engineering structures is often very challenging due to the presence of different degrees of uncertainty in measured responses and confidence levels of the tuning parameters used. To address this issue, this paper presents a hybrid model updating procedure for large-scale civil engineering structures which incorporate these variations by means of data scatter for both measured responses and tuning parameters as a logical extension to the conventional automated model updating procedures. Scatters in the measured responses are derived through statistically analysing ambient vibration test data, while confidence levels of tuning parameters are derived based on the engineering judgement. The results of applying this hybrid model automated model updating procedure to a ten story building show a significant improvement in obtaining more realistic updated models, against its conventional counterpart that was done previously on the same structure.

Keywords: automated model updating; measured data undertainty; confidence levels; tuning parameters; ambient vibration; finite element method; FEM; modelling; response uncertainties; civil engineering structures; data scatter; ten story buildings; high rise buildings.

DOI: 10.1504/IJLCPE.2016.082712

International Journal of Lifecycle Performance Engineering, 2016 Vol.2 No.1/2, pp.61 - 78

Received: 11 May 2016
Accepted: 10 Oct 2016

Published online: 08 Mar 2017 *

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