Comprehensive Bayesian structural identification applied to a scale aluminium bridge
Abstract »A modular Bayesian method is applied for structural identification of a reduced-scale aluminium model inspired from the New Joban Line Arakawa bridge subject to thermal loading. The deformation/temperature of the structure were measured with strain gauges/thermocouples and simulated with a finite element model. Relative to other Bayesian formulations, this methodology allows to uncover the true values of unknown structural parameters, model discrepancy as well as other uncertainties existent on model calibration, provided that multiple measurements are given as an input. Results show that model calibration is possible even with a minimal amount of measurements taken near regions with diversified temperature loading conditions. Meaningful predictions of the bridge thermal response are highlighted.
Biography: Andre Jesus was born in 1986 and completed his MSc in civil engineering (structures) at Nova University of Lisbon, Portugal (2010). He worked four years as a researcher in high-speed trains and is a member of the Portuguese Engineering Association. In October 2014, he started his PhD on the School of Engineering, University of Warwick. He has publications in international journals and conference proceedings.
Affiliation: University of Warwick School of Engineering CV47AL Coventry United KingdomZhu, YanjieZhu, Yanjie Yanjie.Zhu@warwick.ac.uk
Affiliation: University of Warwick School of Engineering Coventry United Kingdom