A stochastic simulation algorithm for Bayesian model updating of linear structural dynamic system with non-classical damping
Cheung, Sai Hung
Date of Issue2013
International Conference on Structural Safety and Reliability (ICOSSAR) (11th : 2013 : New York, USA)
School of Civil and Environmental Engineering
Model updating using measured system dynamic response has a wide range of applications in structural health monitoring and control, response prediction, reliability and risk assessment. In this paper, we are interested in model updating of a linear structural dynamic system with non-classical damping based on incomplete modal data including modal frequencies, damping ratios and partial complex mode shapes of some of the dominant modes. To quantify the uncertainties and plausibility of the model parameters, a Bayesian approach is considered in which the probability distribution of the model parameters needs to be updated.A new stochastic simulation algorithm is proposed, which allows for an efficient update of the probability distribution of the model parameters. The effectiveness and efficiency of the proposed method are illustrated by a numerical example involving linear structural dynamic system with complex modes.
© 2013 Taylor & Francis Group. This is the author created version of a work that has been peer reviewed and accepted for publication by Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures, Taylor & Francis Group. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/ 10.1201/b16387-278].