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Keywords: relevance vector machine, principal component analysis, wavelet transform, synthetic ground motion, evolutionary power spectral density..

Summary

Nonlinear dynamic analysis is a required step in seismic performance evaluation of many structures. Performing such an analysis requires input ground motions, which are often obtained through simulations, due to the lack of sufficient records representing a given scenario. As seismic ground motions are characterized by timevarying amplitude and frequency content, and the response of nonlinear structures is sensitive to the temporal variations in the seismic energy input, ground motion nonstationarities should be taken into account in simulations. This paper describes a nonparametric approach for modelling and prediction of nonstationary ground motions. Using relevance vector machines, a regression model which takes as input a set of seismic predictors, and produces as output the expected evolutionary power spectral density, conditioned on the predictors. A demonstrative example is presented, where recorded and predicted ground motions are compared in time, frequency, and time-frequency domains. Analysis results indicate a reasonable match between the recorded and predicted quantities.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 106 PROCEEDINGS OF THE TWELFTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STRUCTURES TECHNOLOGY Edited by: Paper 56 A Novel Approach for Modeling Nonstationary Ground Motions Y. Dak Hazirbaba and J. Tezcan Department of Civil and Environmental Engineering, Southern Illinois University Carbondale, United States of America doi:10.4203/ccp.106.56 purchase the full-text of this paper Full Bibliographic Reference for this paper Y. Dak Hazirbaba, J. Tezcan, "A Novel Approach for Modeling Nonstationary Ground Motions", in , (Editors), "Proceedings of the Twelfth International Conference on Computational Structures Technology", Civil-Comp Press, Stirlingshire, UK, Paper 56, 2014. doi:10.4203/ccp.106.56 Keywords: relevance vector machine, principal component analysis, wavelet transform, synthetic ground motion, evolutionary power spectral density.. Summary Nonlinear dynamic analysis is a required step in seismic performance evaluation of many structures. Performing such an analysis requires input ground motions, which are often obtained through simulations, due to the lack of sufficient records representing a given scenario. As seismic ground motions are characterized by timevarying amplitude and frequency content, and the response of nonlinear structures is sensitive to the temporal variations in the seismic energy input, ground motion nonstationarities should be taken into account in simulations. This paper describes a nonparametric approach for modelling and prediction of nonstationary ground motions. Using relevance vector machines, a regression model which takes as input a set of seismic predictors, and produces as output the expected evolutionary power spectral density, conditioned on the predictors. A demonstrative example is presented, where recorded and predicted ground motions are compared in time, frequency, and time-frequency domains. Analysis results indicate a reasonable match between the recorded and predicted quantities. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £65 +P&P)
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