• Smart Structures and Systems
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• v.25 no.1
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• pp.47-56
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• 2020

This paper proposes a model-based approach for structural damage identification and quantification. Using pseudo modal strain energy and mode shape vectors, a damage-sensitive objective function is introduced which is suitable for damage estimation and quantification in shear frames. Whale optimization algorithm (WOA) is used to solve the problem and report the optimal solution as damage detection results. To illustrate the capability of the proposed method, a numerical example of a shear frame under different damage patterns is studied in both ideal and noisy cases. Furthermore, the performance of the WOA is compared with particle swarm optimization algorithm, as one the widely-used optimization techniques. The applicability of the method is also experimentally investigated by studying a six-story shear frame tested on a shake table. Based on the obtained results, the proposed method is able to assess the health of the shear building structures with high level of accuracy.

• Structural Engineering and Mechanics
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• v.11 no.1
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• pp.71-87
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• 2001

A frequency domain response analysis is presented for building frames passively controlled by viscoelastic dampers, under harmonic ground excitation. Three different models are used to represent the linear dynamic force-deformation characteristics of viscoelastic dampers namely, Kelvin model, Linear hysteretic model and Maxwell model. The frequency domain solution is obtained by (i) an iterative pseudo-force method, which uses undamped mode shapes and frequencies of the system, (ii) an approximate modal strain energy method, which uses an equivalent modal damping of the system in each mode of vibration, and (iii) an exact method which uses complex frequency response function of the system. The responses obtained by three different methods are compared for different combinations of viscoelastic dampers giving rise to both classically and non-classically damped cases. In addition, the effect of the modelling of viscoelastic dampers on the response is investigated for a certain frequency range of interest. The results of the study are useful in appropriate modelling of viscoelastic dampers and in understanding the implication of using modal analysis procedure for building frames which are passively controlled by viscoelastic dampers against base excitation.

• Structural Engineering and Mechanics
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• v.87 no.6
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• pp.555-574
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• 2023

An efficient optimization algorithm and damage-sensitive objective function are two main components in optimization-based Finite Element Model Updating (FEMU). A suitable combination of these components can considerably affect damage detection accuracy. In this study, a new hybrid damage-sensitive objective function is proposed based on combining two different objection functions to detect the location and extent of damage in structures. The first one is based on Generalized Pseudo Modal Strain Energy (GPMSE), and the second is based on the element's Generalized Flexibility Matrix (GFM). Four well-known population-based metaheuristic algorithms are used to solve the problem and report the optimal solution as damage detection results. These algorithms consist of Cuckoo Search (CS), Teaching-Learning-Based Optimization (TLBO), Moth Flame Optimization (MFO), and Jaya. Three numerical examples and one experimental study are studied to illustrate the capability of the proposed method. The performance of the considered metaheuristics is also compared with each other to choose the most suitable optimizer in structural damage detection. The numerical examinations on truss and frame structures with considering the effects of measurement noise and availability of only the first few vibrating modes reveal the good performance of the proposed technique in identifying damage locations and their severities. Experimental examinations on a six-story shear building structure tested on a shake table also indicate that this method can be considered as a suitable technique for damage assessment of shear building structures.