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Most finite element model updating (FEMU) studies on bridges are acceleration-based due to their lower cost and ease of use compared to strain- or displacement-based methods, which entail costly experiments and traffic disruptions. This leads to a scarcity of comprehensive studies incorporating strain measurements. This study employed the strain- and acceleration-based FEMU analyses performed on a more than 50-year-old multi-span concrete highway viaduct. Mid-span strains under heavy vehicles were considered for the strain-based FEMU, and frequencies and mode shapes for the acceleration-based FEMU. The analyses were performed separately for up to three variables, representing Young's modulus adjustment factors for different groups of structural elements. FEMU studies considered residual minimisation and the error-domain model falsification (EDMF) methodology. The residual minimisation utilised four different single-objective optimisations focusing on strains, frequencies, and mode shapes. Strain- and frequency-based FEMU analyses resulted in an approximately 20% increase in the overall superstructure's design stiffness. This study shows the benefits of the intuitive EDMF over residual minimisation for FEMU, where information gained from the strain data, in addition to the acceleration data, manifests more sensible updated variables. EDMF finally resulted in a 25–50% overestimated design stiffness of internal main girders. [ABSTRACT FROM AUTHOR]

Summary: Accurate finite element (FE) models play an essential role in the health monitoring of operational bridges. Static structural deflections caused by vehicles, which are used in traditional finite element model updating (FEMU) methods, are often procured from field tests, interrupting the traffic and limiting the test loading scenarios. This study proposes a FEMU method that directly applies the massive, multi‐source structural and traffic data in the operation phase to update the FE model, effectively solving the defects above. We use the computer vision‐based vehicle load identification technique to accurately locate and weigh vehicle loads and carry out static simulations in the FE model based on the identified vehicle loads. The proposed FEMU objective function is established using indices including dynamic structural characteristics and vehicle‐induced static structural responses. The static error index in the objective function integrates the curve shape and extrema difference of theoretic and measured static responses. Finally, we deploy a parallel particle swarm optimization (PSO) algorithm to find the global optimal updated FE model. A continuous scale bridge model is employed in the experimental studies with four typical scenarios. Compared to the results from the initial FE model, the updated FE model provides significantly better results both in dynamic and static aspects in all scenarios, and the static error indexes reduce by 75% on average. The proposed method offers a practical approach to deploying the monitoring data for real‐time FEMU, which considers dynamic and static features and provides a basis for damage detection, performance assessment, and management. [ABSTRACT FROM AUTHOR]

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A methodology is proposed to optimize a specimen shape in a biaxial testing machine for the identification of constitutive laws based on full-field measurements. Within the framework of finite element model updating and integrated digital image correlation, the covariance matrix of the identified material parameters due to acquisition noise is computed, and its minimization is the basis of the proposed shape optimization. Two models are investigated: first, a linear elastic law, and second, an elastoplastic law with linear kinematic hardening. Two optimal fillet radii sets are assessed for the two investigated laws based on the minimization of the identification uncertainty. [ABSTRACT FROM AUTHOR]

Historic buildings have a high architectural value and their maintenance, repair and rehabilitation require a special approach. This approach is mainly based on the buildings' performance under non-destructive tests such as operational modal analysis (OMA). Under extreme loads, such as earthquakes, these buildings require representative numerical models to simulate their expected response. In historic buildings, tie rods transfer axial loads and are typically used to balance horizontal trust due to static and dynamic loads associated with seismic actions. It is very important to determine the possibility of exceeding their load-bearing capacity under extreme loads, such as an earthquake. In this context, this paper presents an approach for the analysis of seismic action on the tie rod system in a historic building. The analysis was performed by combining the on-site experimental testing and the finite element model updating (FEMU) of the local models of tie rods and the global model of the structure. It was shown that the combination of analyzing local and global structural models, experimental on-site testing and FEMU is a viable solution for assessment of historic buildings' load bearing capacity. [ABSTRACT FROM AUTHOR]