چكيده به لاتين
All structures may be affected by various factors such as corrosion, exhaustion of materials, external factors, like earthquake, wind, and impact damage during their lifetime. Early and timely detection of damage in structures is very important since in this way, not only is the optimal performance of the structure guaranteed, but also sudden failure of the existing structures is prevented. Hence, the identification and quantification of damage in structures has received considerable attention in the recent decades. The purpose of this study was to determine the location and severity of damage using model updating methods and specifically to investigate the role of the type of optimizer and the objective function. First, damage was simulated as some changes in the stiffness matrix of the damaged elements. Then, the model updating problem was defined as an optimization procedure by proposing modal flexibility matrix-based cost function. Finally, the problem was solved using the concept of Chaos Theory and Particle Swarm Optimization. To solve highly ill-posed inverse problems, Chaos theory-based Particle Swarm Optimization algorithm shows better performance in comparison with the original Particle Swarm Optimization algorithm; for this reason, it can be a suitable algorithm for model updating procedure. To investigate the applicability of the proposed method, three examples of the structures in different conditions were studied. The results shows acceptable performance of the introduced method.
Keywords: Particle swarm optimization, Chaos, Chaos theory-based optimization algorithm, Structural softness matrix.
