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2019 | OriginalPaper | Chapter

Uncertainty Quantification and Model Identification in a Bayesian and Metaheuristic Framework

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Abstract

Uncertainty quantification of identified parameters is an important feature when some quality assessment of the results of model updating procedure is necessary, or when important decisions depend upon these values. In this work, a modification of the conventional sensitivity method is tested along with a Bayesian Monte Carlo framework for identification of system parameters from experimental data, and their probability distributions. First, the updating procedure uses a metaheuristic algorithm (derivative-free) and the Euclidean norm metric. Then, a modification of Markov Chain Monte Carlo method called Transitional MCMC is applied to obtain an approximation of the mean values and probability distributions of the updated parameters based on the scattering of the experimental data. An example is presented with real structure experimental data for updating discrete mass, stiffness and damping parameters, as well as a comparison with previous results yielded by different methods, suggesting equivalent levels of agreement in the updated parameters, but with the advantage of MCMC formulation being practically independent of parameters vectors.

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Literature
go back to reference Ching, J., Chen, Y.-C.: Transitional Markov Chain Monte Carlo method for Bayesian model updating, model class selection, and model averaging. J. Eng. Mech. 33(7), 816–832 (2007)CrossRef Ching, J., Chen, Y.-C.: Transitional Markov Chain Monte Carlo method for Bayesian model updating, model class selection, and model averaging. J. Eng. Mech. 33(7), 816–832 (2007)CrossRef
go back to reference Brooks, S., Gelman, A., Jones, G.L., Meng, X.-L.: Handbook of Markov Chain Monte Carlo. CRC Press, Boca Raton (2011)CrossRef Brooks, S., Gelman, A., Jones, G.L., Meng, X.-L.: Handbook of Markov Chain Monte Carlo. CRC Press, Boca Raton (2011)CrossRef
go back to reference Gamerman, D., Lopes, Hedibert, F.: Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, 2nd edn. Chapman and Hall/CRC, New York (2006). Editors: Carlin, B.P., Chatfield, C., Tanner, M., Zidek, J. Gamerman, D., Lopes, Hedibert, F.: Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, 2nd edn. Chapman and Hall/CRC, New York (2006). Editors: Carlin, B.P., Chatfield, C., Tanner, M., Zidek, J.
go back to reference Yuen, K.-V.: Bayesian Method for Structural Dynamics and Civil Engineering. Wiley, Hoboken (2010)CrossRef Yuen, K.-V.: Bayesian Method for Structural Dynamics and Civil Engineering. Wiley, Hoboken (2010)CrossRef
go back to reference Löw, A.M., Gomes, H.M.: Parameters identification with evaluation of uncertainties using sensitivity method and covariance matrix analysis. In: Proceedings of 24th ABCM International Congress of Mechanical Engineering, Curitiba, PR, Brazil, 3–8 December 2017 Löw, A.M., Gomes, H.M.: Parameters identification with evaluation of uncertainties using sensitivity method and covariance matrix analysis. In: Proceedings of 24th ABCM International Congress of Mechanical Engineering, Curitiba, PR, Brazil, 3–8 December 2017
go back to reference Feldman, M.: Hilbert transform in vibration analysis. Mech. Syst. Signal Process. 25, 735–802 (2011)CrossRef Feldman, M.: Hilbert transform in vibration analysis. Mech. Syst. Signal Process. 25, 735–802 (2011)CrossRef
go back to reference Friswell, M.I., Mottershead, J.E.: Finite Element Model Updating in Structural Dynamics. Solid Mechanics and Its Applications. Kluwer, Boston (1995)CrossRef Friswell, M.I., Mottershead, J.E.: Finite Element Model Updating in Structural Dynamics. Solid Mechanics and Its Applications. Kluwer, Boston (1995)CrossRef
go back to reference Maia, M.M., Silva, J.M.M. (eds.): Theoretical and Experimental Modal Analysis. Research Studies Press, Baldock (1997) Maia, M.M., Silva, J.M.M. (eds.): Theoretical and Experimental Modal Analysis. Research Studies Press, Baldock (1997)
go back to reference Silva, T.A.N., Maia, N.M.M., Link, M., Mottershead, J.E.: Parameter selection and covariance updating. Mech. Syst. Signal Process. 70–71, 269–283 (2016)CrossRef Silva, T.A.N., Maia, N.M.M., Link, M., Mottershead, J.E.: Parameter selection and covariance updating. Mech. Syst. Signal Process. 70–71, 269–283 (2016)CrossRef
Metadata
Title
Uncertainty Quantification and Model Identification in a Bayesian and Metaheuristic Framework
Authors
Alexandre Marks Löw
Herbert Martins Gomes
Copyright Year
2019
DOI
https://doi.org/10.1007/978-3-319-97773-7_37

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