Deep Gaussian process regression for damping of a long-span bridge under varying environmental and operational conditions
Author:
Funder
National Research Foundation of Korea
Korea Agency for Infrastructure Technology Advancement
Publisher
Springer Science and Business Media LLC
Subject
Safety, Risk, Reliability and Quality,Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s13349-023-00710-8.pdf
Reference85 articles.
1. Magalhaes F, Cunha A, Caetano E, Brincker R (2010) Damping estimation using free decays and ambient vibration tests. Mech Syst Signal Process 24(5):1274–1290. https://doi.org/10.1016/j.ymssp.2009.02.011
2. Fujino Y, Kimura K, Tanaka H (2012) Wind resistant design of bridges in Japan: developments and practices. Springer, Tokyo
3. Xing C, Wang H, Li A, Xu Y (2014) Study on wind-induced vibration control of a long-span cable-stayed bridge using TMD-type counterweight. J Bridg Eng 19(1):141–148. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000500
4. Martínez-Rodrigo MD, Filiatrault A (2015) A case study on the application of passive control and seismic isolation techniques to cable-stayed bridges: a comparative investigation through non-linear dynamic analyses. Eng Struct 99:232–252. https://doi.org/10.1016/j.engstruct.2015.04.048
5. Kim S, Park J, Kim H-K (2017) Damping identification and serviceability assessment of a cable-stayed bridge based on operational monitoring data. J Bridg Eng 22(3):04016123. https://doi.org/10.1061/(ASCE)BE.1943-5592.0001004
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