A Frequency Response Functions (FRFs)‐based two‐step algorithm to identify stiffness, mass, and viscous damping matrices is developed in this work. The proposed technique uses the difference between the experimentally recorded FRF and their analytical counterparts by minimizing the resultant error function at selected frequency points. In the first step, only mass and stiffness matrices are updated while keeping the uncalibrated viscous damping matrix constant. In the second step, the damping matrix is updated via changes on the selected unknown modal damping ratios. By using a stacking procedure of the presented error function that combines multiple data sets, adverse effects of noise on the estimated modal damping ratios are decreased by averaging the FRF amplitudes at resonant peaks. The application of this methodology is presented utilizing experimentally obtained data. The presented algorithm can perform an accurate structural identification via model updating, with a viscous damping matrix that captures the variation of the modal damping ratios with natural frequencies as opposed to other conventional proportional damping matrix formulations.

In many finite element platforms, a classical global damping matrix based on the elastic stiffness of the system (including isolators) is usually developed as part of the solution to the equations of motion of base-isolated buildings. The conducted analytical and numerical investigations illustrate that this approach can lead to the introduction of unintended damping to the first and higher vibration modes and the spurious suppression of the respective structural responses. A similar shortcoming might be observed even when a nonclassical damping model (ie, an assembly of the superstructure and isolation system damping sub-matrices) is used. For example, the use of Rayleigh damping approach to develop the superstructure damping sub-matrix can lead to the undesired addition of damping to the isolated mode arising from the massproportional component of the superstructure damping. On the other hand, the improper use of nonclassical stiffness-proportional damping (eg, determining the proportional damping coefficient, β k , based on the first mode) can result in assigning significant damping to the higher-modes and the unintended mitigation of the higher-mode responses. Results show that a nonclassical stiffness-proportional model in which β k is determined based on the second modal period of a base-isolated building can reasonably specify the intended damping to the higher modes without imparting undesirable damping to the first mode. The nonclassical stiffness-proportional damping can be introduced to the numerical model through explicit viscous damper elements attached between adjacent floors. In structural analysis software such as SAP2000®, the desired nonclassical damping can be also modeled through specifying damping solely to the superstructure material.

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Summary Recent developments in instrumentation, modeling, and data collection have advanced the state of the art in structural health monitoring in many engineering areas. However, the application of these developments in civil engineering infrastructure still presents some challenges. With approximately 11% of the bridges in the USA classified as structural deficient and billions of dollars required for either replacement or rehabilitation, transportation authorities require more efficient methods for condition assessment of existing bridges and funding allocation. In this article, a frequency response function‐based, two‐step model updating technique is applied to the Powder Mill Bridge. The Powder Mill Bridge is a typical overpass bridge constructed in 2009 and located in the town of Barre, Massachusetts. The goal of this research is to obtain a baseline finite element model that captures the bridge's behavior in its healthy condition using experimentally collected data from testing performed in 2010. The proposed two‐step protocol successfully identified stiffness, mass, and damping parameters in simulated scenarios with contamination from measurement errors. Likewise, experimental validation using field collected dynamic data produced parameters that were reflective of the field‐observed structural condition of the tested bridge. If the model updating protocol is repeated using collected data at standard intervals, the baseline could be eventually used to identify changes in structural parameters that are indicative of damage. Copyright © 2015 John Wiley & Sons, Ltd.

Accurate representation of the structural performance of civil engineering structures, specifically complex bridge structures, may be achieved through an efficient multiscale finite element (FE) model. Multiscale FE modeling couples multiple dimensions of elements in a single model. In this study, the selected existing multipoint constraint equations applied in planar coupling conditions are modified and refined for out-of-plane coupling conditions in a single three-dimensional FE model. Also, the optimum location for the interface points of different elements is determined to improve the model's accuracy and efficiency. The present case study, the Memorial Bridge in Portsmouth, NH, is a vertical lift bridge, which includes novel gusset-less connections. These connections have complex geometries and therefore require finer dimension elements to represent the structural behavior, while the remainder of the structure is modeled with coarser dimension elements. To achieve an accurate and efficient multiscale model of the Memorial Bridge, multiple global FE models are developed and the predicted structural responses are verified with respect to the fieldcollected structural responses of the bridge.