Chapter 14 Covariance-Driven Stochastic Subspace Identification of an End-Supported Pontoon Bridge Under Varying Environmental Conditions Knut Andreas Kvåle, Ole Øiseth, and Anders Rönnquist Abstract The Bergsøysund Bridge is currently being extensively monitored with accelerometers, anemometers, wave radars and GNSS sensors. By applying Covariance-driven Stochastic Subspace Identification (Cov-SSI), the modal parameters of the bridge are estimated. The results are interpreted in the context of the environment, represented by significant wave heights. The problem is characterized by the fact that modes are closely spaced in frequency and have high damping. Two weighting algorithms for the Cov-SSI are applied, to assess their performance for application on structures with these characteristics. Keywords Floating bridge • Stochastic subspace identification • Environmental influence • Wave excitation • High damping 14.1 Introduction For decades, floating bridges served mainly as a military asset, for temporary crossings of rivers and straits. Floating bridges were first applied as critical links in modern road networks in the middle of the twentieth century, with exception of the Galata floating bridge in Istanbul finished in 1912 [1]. The continuous box girder design has shown great success in the State of Washington, USA, where most of the existing floating bridges are located. For straits highly affected by current and wave action, floating bridges relying on separate and discretely distributed pontoons may be beneficial. By using such a design, the waves will excite the structure merely in the points where the pontoons are located, and the correlation of the excitation will influence the response in a manner more sensitive to changes in the wave field. This will be of particular importance when the spans of the bridges increase. Currently, limited experience about the behavior of such floating bridges is available, and a thorough study of existing structures will be valuable. There exist only two end-supported floating bridges in the world that rely on discretely distributed pontoons, both located in Norway. The Bergsøysund Bridge is one of them, and it is currently extensively monitored to study its behavior upon wave and wind excitation. Operational modal analysis (OMA) is a highly valuable tool in the study of the behavior of the bridge. The covariance-driven stochastic subspace identification (CovSSI) algorithm is amongst the methods considered most robust and accurate [2–5] and performs very well for traditionally tested civil structures, such as suspension bridges and high-risers. The performance of the Cov-SSI algorithm applied on the Bergsøysund Bridge has previously been studied by [6]. In the current study, it is applied on recordings of acceleration of the bridge, to evaluate how it is affected by variations in the environmental conditions. The performances of various weighting algorithms are also assessed. The results are compared with modal parameters obtained from the eigenvalue solution of an model-updated version of the numerical prediction model presented in [7]. 14.2 Covariance-Driven Stochastic Subspace Identification The applied implementation of the Cov-SSI algorithm is based on the description given by Herman and van Der Auweraer [8], and the reader is referred to the mentioned paper for specifics. Only the most important details are repeated here. The starting point for the analysis is the block-Hankel matrix, ŒHi , which is constructed with sub-matrices representing the K.A. Kvåle ( ) • O. Øiseth • A. Rönnquist Department of Structural Engineering, Faculty of Engineering Science and Technology, NTNU, Norwegian University of Science and Technology, Trondheim, Norway e-mail: knut.a.kvale@ntnu.no © The Society for Experimental Mechanics, Inc. 2017 J. Caicedo, S. Pakzad (eds.), Dynamics of Civil Structures, Volume 2, Conference Proceedings of the Society for Experimental Mechanics Series, DOI 10.1007/978-3-319-54777-0_14 107
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