Technical Notes
Oct 25, 2021

Classification Protocol and Comprehensive Database of Vertically Correlated Longitudinal Wind Velocities for Structural Analysis and Risk Assessment

Publication: Journal of Structural Engineering
Volume 148, Issue 1

Abstract

This manuscript presents a streamlined protocol to generate and classify synthetic random wind samples. The manuscript is accompanied with a comprehensive and publicly accessible repository of spatially and temporally correlated wind velocity samples for use in probabilistic structural analysis and design. The samples are classified based on the maximum sustained wind speed (maximum 1-min average), and the 3-s gust wind speed (maximum 3-s average), which are the intensity measures commonly used for structural analysis and fragility development. A comparative analysis showed the difference between the direct application of the intensity measure definition (by moving average) and the popular conversion factors used in practice. A classification based on the moving average analysis was found to result in portfolios of samples in each category that better capture the probabilistic characteristics of wind. To demonstrate the use and the importance of the constructed wind repository, a case study of fragility curves analysis of an elevated water tank steel lattice tower is presented. The developed wind database will allow researchers and engineers to select and use wind time histories for many applications, such as the analysis of tall structures located in open terrain areas.

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Data Availability Statement

Some or all data, models, or code generated or used during the study are available in a repository online in accordance with funder data retention policies. In particular, a detailed description of the wind database repository and how it can be used, along with its file formats, is freely available for download through Figshare (Khazaali et al. 2020).

Acknowledgments

This work is part of the Probabilistic Resilience Assessment of Interdependent Systems (PRAISys) project (www.praisys.org). The support from the National Science Foundation through Grant CMMI-1541177 and from the Pennsylvania Department of Community & Economic Development (DCED) through Grant PIT-19-02 is gratefully acknowledged. The authors also thank Liyang Ma for providing thoughtful feedback and assistance throughout this work.

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Journal of Structural Engineering
Volume 148Issue 1January 2022

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Received: Sep 18, 2020
Accepted: Aug 30, 2021
Published online: Oct 25, 2021
Published in print: Jan 1, 2022
Discussion open until: Mar 25, 2022

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Research Assistant, Dept. of Civil and Environmental Engineering, Advanced Technology for Large Structural Systems Engineering Research Center, Lehigh Univ., 117 ATLSS Dr., Bethlehem, PA 18015-4729. ORCID: https://orcid.org/0000-0002-8803-7603. Email: [email protected]
Vasileios Christou [email protected]
Risk Analyst, Fermat Capital Management, LLC, 615 Riverside Ave., Westport, CT 06880. Email: [email protected]
Associate Professor and Director of Graduate Programs, Dept. of Civil and Environmental Engineering, ATLSS Engineering Research Center, Lehigh Univ., 117 ATLSS Dr., Bethlehem, PA 18015-4729 (corresponding author). ORCID: https://orcid.org/0000-0002-5685-2283. Email: [email protected]

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