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Identification of composite uncertain material parameters from experimental modal data |
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| Affiliation: | 1. Laboratoire CMI, Université Constantine1, Constantine, Algeria;2. Laboratoire LP3M, Département d’Optique et Mécanique de Précision, Université de Sétif, Sétif 19000, Algeria;3. IM2NP, Aix Marseille, CNRS, Case 142, 13397 Marseille, France;1. Key Laboratory of Display Materials and Photoelectric Devices, Ministry of Education, Tianjin Key Laboratory for Photoelectric Materials and Devices, School of Material Science and Engineering, Tianjin University of Technology, Tianjin 300384, China;2. Beijing Synchrotron Radiation Facility (BSRF), Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China;1. Faculty of Science and Technology, University of Macau, Macao, China;2. Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong, China;1. Università di Pescara-Chieti, Dipartimento PRICOS, Viale Pindaro 42, Pescara, Italy;2. University Campus Bio-Medico of Rome, Engineering Faculty, Via A. del Portillo 21, Rome, Italy;3. Politecnico di Milano, Dipartimento di Ingegneria Civile ed Ambientale, Piazza Leonardo da Vinci 32, Milano, Italy |
| Abstract: | Stochastic analysis of structures using probability methods requires the statistical knowledge of uncertain material parameters. This is often quite easier to identify these statistics indirectly from structure response by solving an inverse stochastic problem. In this paper, a robust and efficient inverse stochastic method based on the non-sampling generalized polynomial chaos method is presented for identifying uncertain elastic parameters from experimental modal data. A data set on natural frequencies is collected from experimental modal analysis for sample orthotropic plates. The Pearson model is used to identify the distribution functions of the measured natural frequencies. This realization is then employed to construct the random orthogonal basis for each vibration mode. The uncertain parameters are represented by polynomial chaos expansions with unknown coefficients and the same random orthogonal basis as the vibration modes. The coefficients are identified via a stochastic inverse problem. The results show good agreement with experimental data. |
| Keywords: | Composite structures Uncertain parameter identification Polynomial chaos Pearson model Experimental modal analysis |
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