Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Bayesian Calibration of Hysteretic Parameters with Consideration of the Model Discrepancy for Use in Structural Health Monitoring

Version 1 : Received: 7 July 2020 / Approved: 9 July 2020 / Online: 9 July 2020 (11:55:52 CEST)

A peer-reviewed article of this Preprint also exists.

Ceravolo, R.; Faraci, A.; Miraglia, G. Bayesian Calibration of Hysteretic Parameters with Consideration of the Model Discrepancy for Use in Seismic Structural Health Monitoring. Appl. Sci. 2020, 10, 5813. Ceravolo, R.; Faraci, A.; Miraglia, G. Bayesian Calibration of Hysteretic Parameters with Consideration of the Model Discrepancy for Use in Seismic Structural Health Monitoring. Appl. Sci. 2020, 10, 5813.

Journal reference: Appl. Sci. 2020, 10, 5813
DOI: 10.3390/app10175813

Abstract

Bayesian model calibration techniques are commonly employed in the characterization of nonlinear dynamic systems, as they provide a conceptual and effective framework to deal with model uncertainties, experimental errors and procedure assumptions. This understanding has resulted in the need to introduce a model discrepancy term to account for the differences between model-based predictions and real observations. Indeed, the goal of this work is to enhance model-driven Structural Health Monitoring procedures by incorporating the posterior uncertainty linked to updated model discrepancy, and thus make relevant considerations for its use in the Structural Health Monitoring. Specifically, the Bayesian inference has been applied to the calibration of nonlinear hysteretic systems to both provide: (i) most probable values (MPV) of the parameters following the calibration, and; (ii) estimates of the model discrepancy posterior distribution. The effect of the model discrepancy in the calibration is first illustrated recurring to a single degree of freedom Bouc-Wen type oscillator, and then applied for calibrating a reference nonlinear Bouc-Wen model, deriving from real data acquired on a monitored masonry building.

Subject Areas

Bayesian inference; Uncertainty quantification; Nonlinear hysteretic systems; Bouc-Wen model; Model calibration; Hysteretic system identification; Structural Health Monitoring.

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