Title
Inverse identification of the gust loading of a high-rise tower with Bayesian statistics
Author
Kemper, F.
Geurts, C.P.W.
Publication year
2022
Abstract
For the modeling of stochastic structural responses due to wind gusts, reasonable assumptions for the aerodynamic admittance are elementary. However, still a large variety of corresponding models exists and it lacks of validation and reliable model estimation studies based on real-data. In this paper, real-data from a high-rise tower in Rotterdam is used to inversely identify the aerodynamic admittance (size-effect and joint-acceptance functions, SE, JAF) based on Maximum Likelihood Estimates (MLE), Marcov-Chain Monte Carlo (MCMC) sampling and a Bayesian posterior (BP) implementation to find parametric models different both aspects of aerodynamic admittance.
Subject
Aerodynamic Admittance
Stochastic Vibrations
Gust Response
Bayesian Parameter Modeling
Buildings and Infrastructures
2015 Urbanisation
To reference this document use:
http://resolver.tudelft.nl/uuid:614adba7-6d26-4dfb-8d9e-0795feb35577
TNO identifier
977788
Source
CWE Workshop 2022 Advanced modeling of stochastic Wind Effects and Vibrations, 1-6
Document type
conference paper