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Use of Orthogonal Decomposition Tools in Analyzing Wind Effect on Structures

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The main objective of this paper is presentation of the orthogonal decomposition techniques as a tool for simplified response analysis of wind-structure interaction and its possible physical interpretation. The aim is to summarize the procedures that have large impact in the design stages, and not to discuss the cutting edge of this research topic. In case of random processes, orthogonal decomposition consists of projecting a multivariate stochastic field on a base allowing a parametric reconstruction of the stochastic process. The method is presented according to the state-of-the-art, by using either the co-variance or the power spectral density matrix; single modal (structural or load based) and double modal (structural and load based) transformations are also discussed.

The spectrum of wind analyses that benefit from such procedures is quite large: quasi-static structural response to wind, characterization of the resonant amplification, artificial simulation of multivariate wind velocity fields, preliminary design of additional damping systems and experimental dynamic identification of structures.
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Document Type: Research Article

Publication date: 2005-11-01

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    Structural Engineering International (SEI), the quarterly Journal of IABSE, published since 1991, is the leading international journal of structural engineering dealing with all types of structures and materials. SEI offers its readers a unique blend of short profiles on recent structures, and longer, in-depth technical articles on research, development, design, construction and maintenance. Articles are written by practicing engineers and academia from around the world and reflect the high standards of IABSE. IABSE Peer Review stamps are given to papers that have passed through a highly selective review process and demonstrate a significant contribution to the state of structural engineering knowledge.To recognise contributions of the highest quality, an Outstanding Paper Award is presented each year.

    SEI is printed in Switzerland; ISSN 1016-8664; E-ISSN 1683-0350
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