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Finite element model updating of a multispan bridge with a hybrid metaheuristic search algorithm using experimental data from wireless triaxial sensors

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Abstract
The Guadalquivir bridge is a large-scale twin steel truss bridge located in Spain that opened to traffic in 1929. Since the bridge has come into operation for a long time, structural health monitoring (SHM) is strictly necessary to guarantee safety and avoid serious incidents. This paper proposes a novel approach to model updating for the Guadalquivir bridge based on the vibration measurements combined with a hybrid metaheuristic search algorithm. Cuckoo Search (CS) is an evolutionary algorithm derived from global search techniques to look for the best solution. Nevertheless, CS contains some fundamental defects that may reduce its effectiveness in dealing with optimization issues. A main drawback of CS arises in the low convergence level because CS applies fixed values for parameters when looking for the optimal solution. In addition, CS relies a lot on the quality of original populations and does not have the capability to enhance the quality of the next generations. If the position of the original particles is far from the optimal places, it may be challenging to look for the best solution. To remedy the shortcomings of CS, we propose a hybrid metaheuristic algorithm (HGAICS) employing the advantages of both Genetic Algorithm (GA) and Improved Cuckoo Search (ICS) to solve optimization problems. HGAICS contains two outstanding characteristics as follows: (1) GA is employed to create original particles with the best quality based on the capacity of crossover and mutation operators and (2) those particles are then applied to look for the global best derived from the flexible and global search ability of ICS. This paper also presents the application of wireless triaxial sensors (WTSs) taking the place of classical wired systems (CWSs) to the measurements. The use of WTSs increases dramatically the freedom in setting up experimental measurements. The results show that the performance of the proposed hybrid algorithm not only determines uncertain parameters of the Guadalquivir bridge properly, but also is more accurate than GA, CS, and improved CS (ICS). A MATLAB package of the proposed method (HGAICS) is available via GitHub: yhttps://github.com/HoatranCH/HGAICS.
Keywords
General Engineering, Modelling and Simulation, Software, Computer Science Applications, Improved cuckoo search, Large-scale railway bridge, Finite element method, Model updating, Genetic algorithm, Ambient vibration test, Hybrid metaheuristic algorithm, Wireless triaxial transducers

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MLA
Tran, Hoa, et al. “Finite Element Model Updating of a Multispan Bridge with a Hybrid Metaheuristic Search Algorithm Using Experimental Data from Wireless Triaxial Sensors.” ENGINEERING WITH COMPUTERS, 2021, doi:10.1007/s00366-021-01307-9.
APA
Tran, H., Khatir, S., Le-Xuan, T., De Roeck, G., Bui-Tien, T., & Abdel Wahab, M. (2021). Finite element model updating of a multispan bridge with a hybrid metaheuristic search algorithm using experimental data from wireless triaxial sensors. ENGINEERING WITH COMPUTERS. https://doi.org/10.1007/s00366-021-01307-9
Chicago author-date
Tran, Hoa, Samir Khatir, T. Le-Xuan, G. De Roeck, T. Bui-Tien, and Magd Abdel Wahab. 2021. “Finite Element Model Updating of a Multispan Bridge with a Hybrid Metaheuristic Search Algorithm Using Experimental Data from Wireless Triaxial Sensors.” ENGINEERING WITH COMPUTERS. https://doi.org/10.1007/s00366-021-01307-9.
Chicago author-date (all authors)
Tran, Hoa, Samir Khatir, T. Le-Xuan, G. De Roeck, T. Bui-Tien, and Magd Abdel Wahab. 2021. “Finite Element Model Updating of a Multispan Bridge with a Hybrid Metaheuristic Search Algorithm Using Experimental Data from Wireless Triaxial Sensors.” ENGINEERING WITH COMPUTERS. doi:10.1007/s00366-021-01307-9.
Vancouver
1.
Tran H, Khatir S, Le-Xuan T, De Roeck G, Bui-Tien T, Abdel Wahab M. Finite element model updating of a multispan bridge with a hybrid metaheuristic search algorithm using experimental data from wireless triaxial sensors. ENGINEERING WITH COMPUTERS. 2021;
IEEE
[1]
H. Tran, S. Khatir, T. Le-Xuan, G. De Roeck, T. Bui-Tien, and M. Abdel Wahab, “Finite element model updating of a multispan bridge with a hybrid metaheuristic search algorithm using experimental data from wireless triaxial sensors,” ENGINEERING WITH COMPUTERS, 2021.
@article{8702877,
  abstract     = {{The Guadalquivir bridge is a large-scale twin steel truss bridge located in Spain that opened to traffic in 1929. Since the bridge has come into operation for a long time, structural health monitoring (SHM) is strictly necessary to guarantee safety and avoid serious incidents. This paper proposes a novel approach to model updating for the Guadalquivir bridge based on the vibration measurements combined with a hybrid metaheuristic search algorithm. Cuckoo Search (CS) is an evolutionary algorithm derived from global search techniques to look for the best solution. Nevertheless, CS contains some fundamental defects that may reduce its effectiveness in dealing with optimization issues. A main drawback of CS arises in the low convergence level because CS applies fixed values for parameters when looking for the optimal solution. In addition, CS relies a lot on the quality of original populations and does not have the capability to enhance the quality of the next generations. If the position of the original particles is far from the optimal places, it may be challenging to look for the best solution. To remedy the shortcomings of CS, we propose a hybrid metaheuristic algorithm (HGAICS) employing the advantages of both Genetic Algorithm (GA) and Improved Cuckoo Search (ICS) to solve optimization problems. HGAICS contains two outstanding characteristics as follows: (1) GA is employed to create original particles with the best quality based on the capacity of crossover and mutation operators and (2) those particles are then applied to look for the global best derived from the flexible and global search ability of ICS. This paper also presents the application of wireless triaxial sensors (WTSs) taking the place of classical wired systems (CWSs) to the measurements. The use of WTSs increases dramatically the freedom in setting up experimental measurements. The results show that the performance of the proposed hybrid algorithm not only determines uncertain parameters of the Guadalquivir bridge properly, but also is more accurate than GA, CS, and improved CS (ICS). A MATLAB package of the proposed method (HGAICS) is available via GitHub: yhttps://github.com/HoatranCH/HGAICS.}},
  author       = {{Tran, Hoa and Khatir, Samir and Le-Xuan, T. and De Roeck, G. and Bui-Tien, T. and Abdel Wahab, Magd}},
  issn         = {{0177-0667}},
  journal      = {{ENGINEERING WITH COMPUTERS}},
  keywords     = {{General Engineering,Modelling and Simulation,Software,Computer Science Applications,Improved cuckoo search,Large-scale railway bridge,Finite element method,Model updating,Genetic algorithm,Ambient vibration test,Hybrid metaheuristic algorithm,Wireless triaxial transducers}},
  language     = {{eng}},
  title        = {{Finite element model updating of a multispan bridge with a hybrid metaheuristic search algorithm using experimental data from wireless triaxial sensors}},
  url          = {{http://dx.doi.org/10.1007/s00366-021-01307-9}},
  year         = {{2021}},
}

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