Model calibration of a long-span concrete cable-stayed bridge based on structural health monitoring data: Influence of concrete variability

Article type: Research Article

Authors: Natalicchio, Cortney^a | Al-Khateeb, Hadi^b | Chajes, Michael J.^c | Wu, Zheng Y.^d | Shenton III, Harry W.^{e; *}

Affiliations: [a] Rummel, Kleppar, & Kahl, Baltimore, MD, USA | [b] Jacobs Engineering, New York, NY, USA | [c] Department of Civil and Environmental Engineering, University of Delaware, Newark, DE, USA | [d] Bentley Fellow, Bentley Systems, Incorporated, Watertown, CT, USA | [e] Department of Civil and Environmental Engineering, University of Delaware, Newark, DE, USA

Correspondence: [*] Corresponding author: Harry W. Shenton III, Department of Civil and Env. Engineering, University of Delaware, Newark, DE 19716, USA. Tel.: +1 302 831 2447; Fax: +1 302 831 3640; E-mail: shenton@udel.edu.

Abstract: Structural Health Monitoring (SHM) systems, in combination with controlled load tests, can provide valuable data for calibrating high fidelity bridge models, which can then be used for evaluating the long-term performance of the bridge, improved load ratings, and permit vehicle evaluation. The objective of this research was to calibrate a 3D model of the Indian River Inlet (IRIB) cable-stayed bridge, using strains recorded by the bridge SHM system during a controlled load test. The bridge was modeled in STAAD-Pro and calibrated using a pre-commercialized software platform that uses a Generic Algorithm to minimize the error between the measured and predicted strains. The calibration parameters were the elastic modulus of groups of the main longitudinal edge girder/deck elements, which once calibrated, could be related to the measured concrete strength of the members. Four different models were investigated, using 6, 10, 14, and 18 parameter element groups of the edge girder members. Of the different models, the 14 and 18 parameter models yielded the best results. The “design” model yielded errors as high as 42% when compared to the measured strains; the error was less than 10% for the majority of measurements for the 14-parameter model. Including the effect of the traffic barriers in the model, the weighted average concrete strength of the calibrated model was within 4% of the measured weighted strength. The calibration was shown to be insensitive to measurement noise and was validated using several unique single and multi-vehicle load cases that were heavier and more offset from the centerline of the bridge. The calibration procedure was able to capture the variability in flexural stiffness of the edge girders due to the variability of the concrete, resulting in significantly better agreement between the live load measured strains and the model predicted strains.

Keywords: Calibration, cable-stayed bridge, concrete, concrete strength, strain, load test, structural health monitoring, system identification

DOI: 10.3233/BRS-220195

Journal: Bridge Structures, vol. 18, no. 1-2, pp. 45-62, 2022