• Smart Structures and Systems
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• v.25 no.4
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• pp.487-499
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• 2020

This paper proposes a novel approach to model updating for a large-scale cable-stayed bridge based on ambient vibration tests coupled with a hybrid metaheuristic search algorithm. Vibration measurements are carried out under excitation sources of passing vehicles and wind. Based on the measured structural dynamic characteristics, a finite element (FE) model is updated. For long-span bridges, ambient vibration test (AVT) is the most effective vibration testing technique because ambient excitation is freely available, whereas a forced vibration test (FVT) requires considerable efforts to install actuators such as shakers to produce measurable responses. Particle swarm optimization (PSO) is a famous metaheuristic algorithm applied successfully in numerous fields over the last decades. However, PSO has big drawbacks that may decrease its efficiency in tackling the optimization problems. A possible drawback of PSO is premature convergence leading to low convergence level, particularly in complicated multi-peak search issues. On the other hand, PSO not only depends crucially on the quality of initial populations, but also it is impossible to improve the quality of new generations. If the positions of initial particles are far from the global best, it may be difficult to seek the best solution. To overcome the drawbacks of PSO, we propose a hybrid algorithm combining GA with an improved PSO (HGAIPSO). Two striking characteristics of HGAIPSO are briefly described as follows: (1) because of possessing crossover and mutation operators, GA is applied to generate the initial elite populations and (2) those populations are then employed to seek the best solution based on the global search capacity of IPSO that can tackle the problem of premature convergence of PSO. The results show that HGAIPSO not only identifies uncertain parameters of the considered bridge accurately, but also outperforms than PSO, improved PSO (IPSO), and a combination of GA and PSO (HGAPSO) in terms of convergence level and accuracy.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.10
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• pp.1217-1224
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• 2014

This paper provides a practical scaling method to solve an old problem for scaling and developing the speed and resistance of a model to full-scale submarine in fully submerged underwater test. In every experimental test in towing tank, water tunnel and wind tunnel, in the first step, the speed of a model should be scaled to the full-scale vessel (ship or submarine). In the second step, the obtained resistance of the model should be developed. For submarine, there are two modes of movement: surface and submerged mode. There is no matter in surface mode because, according to Froude's law, the ratio of speed of the model to the full-scale vessel is proportional to the square root of lengths (length of the model on the length of the vessel). This leads to a reasonable speed and is not so much for the model that is applicable in the laboratory. The main problem is in submerged mode (fully submerged) that there isn't surface wave effect and therefore, Froude's law couldn't be used. Reynold's similarity is actually impossible to implement because it leads to very high speeds of the model that is impossible in a laboratory and inside the water. According to Reynold's similarity, the ratio of speed of the model to the full-scale vessel is proportional to the ratio of the full-scale length to the model length that leads to a too high speed. This paper proves that there is no need for exact Reynold's similarity because after a special Reynolds, resistance coefficient remains constant. Therefore, there is not compulsion for high speeds of the model. For proving this finding, three groups of results are presented: two cases are based on CFD method, and one case is based on the model test in towing tank. All these three results are presented for three different shapes that can show; this finding is independent of the shapes and geometries. For CFD method, Flow Vision software has been used.