Wind load estimation on bridges using latent force models enriched with environmental data

Conference paper (2022)

Authors

Oyvind W. Petersen Norwegian University of Science and Technology (NTNU)
O. Øiseth Norwegian University of Science and Technology (NTNU)
E. Lourens Offshore Engineering - CEG , Dynamics of Structures - CEG
Research Group
Dynamics of Structures (CEG) (TU Delft)
Copyright: © 2022 Oyvind W. Petersen, Ole Øiseth, E. Lourens
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Published Date

2022

Language

English

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Faculty

Civil Engineering & Geosciences

Department

Engineering Structures

Research Group

Dynamics of Structures

Abstract

An application of inverse force identification of wind loads on bridges is presented. This contribution explores the extension of latent force models (LFMs) in Kalman filters. Specifically, it is shown how LFMs can be enriched with environmental information from wind data in order to realistically reflect the underlying physics behind the wind loads. This is demonstrated in a case study of a long-span suspension bridge equipped with a structural monitoring system, where an extensive data set of 103 time series of 30-minute events is used. The results show that the estimation of modal wind loads and modal response states is stable. Moreover, optimization of LFMs with maximum likelihood methods shows that optimized solutions match well with the actual (measured) wind load conditions. The work elevates the prospects of physics-informed LFMs with interpretable hyperparameters.

Files

ISMA_2022_Petersen_ID607.pdf
(pdf | 4.7 Mb)
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