Wind load estimation on bridges using latent force models enriched with environmental data
Oyvind W. Petersen (Norwegian University of Science and Technology (NTNU))
O. Oiseth (Norwegian University of Science and Technology (NTNU))
E Lourens (TU Delft - Dynamics of Structures, TU Delft - Offshore Engineering)
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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.