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Damage Detection of a Scaled Steel Frame Offshore Structure Using an Improved Imperialist Competitive Algorithm
In this paper, the imperialist competitive optimization algorithm is improved by damage functions to detect damage in a model steel frame test structure for offshore applications. A finite element model of the test structure is developed, validated and updated using the proposed method. As there are much more design variables, which are related to the stiffness of each finite element than the measured mode shapes, the problem is underdetermined. Therefore, damage functions are used to regularize the problem and decrease the number of design variables. A new objective function is proposed for the algorithm using the mode shapes and their l1 norm. The first ten measured mode shapes are used to solve the problem. It is shown that the proposed method is capable of predicting the damage locations with acceptable accuracy.
Damage Detection of a Scaled Steel Frame Offshore Structure Using an Improved Imperialist Competitive Algorithm
In this paper, the imperialist competitive optimization algorithm is improved by damage functions to detect damage in a model steel frame test structure for offshore applications. A finite element model of the test structure is developed, validated and updated using the proposed method. As there are much more design variables, which are related to the stiffness of each finite element than the measured mode shapes, the problem is underdetermined. Therefore, damage functions are used to regularize the problem and decrease the number of design variables. A new objective function is proposed for the algorithm using the mode shapes and their l1 norm. The first ten measured mode shapes are used to solve the problem. It is shown that the proposed method is capable of predicting the damage locations with acceptable accuracy.
Damage Detection of a Scaled Steel Frame Offshore Structure Using an Improved Imperialist Competitive Algorithm
Iran J Sci Technol Trans Civ Eng
Gerist, Saleheh (Autor:in) / Maheri, Mahmoud R. (Autor:in) / Unger, Jörg F. (Autor:in)
01.04.2022
15 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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