Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4920235 | Engineering Structures | 2017 | 8 Pages |
Abstract
A modular Bayesian method is applied for structural identification of a reduced-scale aluminium bridge model subject to thermal loading. The deformation and temperature variations of the structure were measured using strain gauges and thermocouples. Feasibility of a practical, temperature-based, Bayesian structural identification is highlighted. This methodology used multiple responses to identify existent discrepancies of a model, calibrate the stiffness of the bridge support and establish uncertainty of a predicted response. Results show that the inference of a structural parameter is successful even in the presence of substantial modelling discrepancies, converging to its true physical value. However measurements should have a high dependency on the calibration parameters. Usage of temperature variations to perform structural identification is highlighted.
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Authors
Andre Jesus, Peter Brommer, Yanjie Zhu, Irwanda Laory,