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SUMMARY Larger and more flexible structures are being constructed. As a result, there is an increasing need for more effective, efficient, and innovative displacement control strategies. One such method is the idea of connecting adjacent structures. This control method has the merit of generating sufficient control forces under low frequencies, a property that is necessary for minimizing the displacement response of high‐rise structures. In the present work, closed‐form equations are derived for solving the vibration control problem of connecting two adjacent structures. In this design method, the maximum absolute displacement transmissibility of each structure is reduced. The closed‐form solution is derived for a passive control method, where the structures are coupled via stiffness and damping elements connected in parallel. The presence of the stiffness element allows for the simultaneous tuning of both structures. The method is demonstrated for passive control of adjacent connected buildings subject to the El Centro ground motion. It is shown that the passive connection method is effective in reducing the response of both structures compared with the uncontrolled (unconnected) case. Copyright © 2011 John Wiley & Sons, Ltd.

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Structural health monitoring (SHM) has gained considerable attention as a tool for monitoring the health of civil infrastructure. For bridge infrastructure, previous methods have focused on the detection of localized damage through modal parameters extracted from the longitudinal direction of the structure. This paper investigates a new damage detection method based on the change in the first vertical mode extracted from the transverse direction of the bridge. The mode is determined through application of modal curve fitting to frequency response functions (FRFs) that are formed using vertical response data obtained in the direction perpendicular to the bridge’s longitudinal axis. Using this method, both local damage and global damage in the bridge reveal themselves as having a localized effect on the bridge response. Furthermore, damage is revealed in such a way that it enables differentiation of the damage types. To demonstrate the effectiveness of the method, modal parameters were extracted from acceleration data obtained from a finite element model of a full bridge. Analysis of the modal parameters showed that the proposed approach could not only detect both local and global bridge damage, but could also differentiate between damage types using only one mode shape. The proposed method was compared to a previously developed SHM method.