مؤتمر
Bayesian damage characterization based on probabilistic model of scattering coefficients and hybrid wave finite element model scheme
| العنوان: | Bayesian damage characterization based on probabilistic model of scattering coefficients and hybrid wave finite element model scheme |
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| المؤلفون: | Yan W., Chronopoulos D., Papadimitriou C., Cantero-Chinchilla S., Zhu G.-S. |
| المصدر: | COMPDYN Proceedings ; https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079054364&partnerID=40&md5=e81622a57ef37f704630bd321ae0d338Test |
| سنة النشر: | 2019 |
| المجموعة: | University of Thessaly Institutional Repository / Ιδρυματικό Αποθετήριο Πανεπιστημίου Θεσσαλίας |
| مصطلحات موضوعية: | Computation theory, Computational methods, Damage detection, Earthquake engineering, Engineering geology, Frequency domain analysis, Geophysics, Guided electromagnetic wave propagation, Markov processes, Probability density function, Probability distributions, Structural dynamics, Ultrasonic waves, Uncertainty analysis, Bayesian Analysis, Damage Identification, Ultrasonic guided wave, Uncertainty quantifications, Wave finite element, Finite element method, National Technical University of Athens |
| الوصف: | Ultrasonic Guided Wave(GW) has been proven to be sensitive to small damage. Motivated by the fact that the quantitative relationship between wave scattering and damage intensity can be described by scattering properties, this study aims at proposing a new probabilistic damage characterization method based on the scattering coefficients in tandem with hybrid wave finite element model (WFEM) scheme. The probabilistic distribution properties of the scattering coefficients estimated using measured ultrasonic guided waves in the frequency domain are inferred based on absolute complex ratio statistics. The theoretical scattering coefficients can be efficiently calculated using WFEM which combines conventional finite element analysis with periodic structure theory. Based on the probabilistic distribution of reflection/transmission coefficients, the likelihood function connecting the theoretical model responses containing the parameters to be updated and the measured responses are formulated within a unified Bayesian system identification framework to account for various uncertainties. The transitional Monte Carlo Markov Chain (TMCMC) is used to sample the posterior probability density function of the updated parameters. A numerical example is utilized to verify the accuracy of the proposed algorithm. Results indicate that the strategies proposed in this study can quantify the uncertainties of damage characterization © 2019 The authors. |
| نوع الوثيقة: | conference object |
| اللغة: | English |
| ردمك: | 978-618-82844-7-0 618-82844-7-3 |
| تدمد: | 26233347 |
| العلاقة: | http://hdl.handle.net/11615/80871Test |
| الإتاحة: | http://hdl.handle.net/11615/80871Test |
| رقم الانضمام: | edsbas.873DC27F |
| قاعدة البيانات: | BASE |
| ردمك: | 9786188284470 6188284473 |
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| تدمد: | 26233347 |