A stochastic analysis framework for a steel frame structure using wireless sensor system measurements |
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| Affiliation: | 1. Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, China;2. Institute for Infrastructure Engineering, University of Western Sydney, Australia;3. School of Civil Engineering, Dalian University of Technology, Dalian 116024, China;1. Laboratory of Ultrasound, Division of Acoustics and Vibration Metrology, Directory of Scientific and Industrial Metrology, National Institute of Metrology, Quality, and Technology, Duque de Caxias, Rio de Janeiro, Brazil;2. Centro de Informática e Sistemas, Polo II, Departamento de Engenharia Informática, Pinhal de Marrocos, Universidade de Coimbra, 3030-290 Coimbra, Portugal;3. Biomedical Eng. Program/COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil;1. CIRRELT and Polytechnique Montréal, Department of Mathematical and Industrial Engineering, C.P. 6079, Succursale Centre-ville, Montréal, QC, Canada H3C 3A7;2. Laboratory for Information and Decision Systems, Department of Electrical Engineering and Computer Science, and Operations Research Center, MIT, Cambridge, MA 02139, USA |
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| Abstract: | This paper presents a stochastic analysis framework for estimating the system-level first-passage probability of the structural responses of multi-degree-of-freedom structural systems based on experimentally measured uncertainties. The uncertainties are quantified by comparing the measured structural responses using a wireless sensor system and the predicted responses from an analytical model. The wireless sensor network is designed based on a modular design method, and the experimental program details for the measurement of structural responses are provided using the developed wireless sensor network. This framework employs a Monte Carlo simulation (MCS)-based first-passage probability estimation technique in which a structural dynamic analysis is performed in each simulation realization. The framework is applied to a 16-story steel frame structure, and the first-passage probability of 16 locations and the series system passage probability of the entire system have been estimated. The effect of the dependency between the structural responses is considered, and the improvements that need to be made to the presented framework in the future works are discussed. |
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| Keywords: | Stochastic analysis framework Probability Wireless sensor networks Steel frame structure |
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