Damage identification in high-rise concrete structures using a bio-inspired meta-heuristic optimization algorithm. (February 2023)

• Record Type: Journal Article
• Authors: Minh, Hoang-Le; Sang-To, Thanh; Khatir, Samir; Abdel Wahab, Magd; Cuong-Le, Thanh
• Is Part Of: Advances in engineering software. Volume 176(2023)
• Publication Date: 2023-02
• Subjects: Metaheuristic optimization -- Engineering problems -- Structural damage identification -- SAP2000-OAPI -- Termite Life Cycle Optimizer (TLCO); Computer-aided engineering -- Periodicals; Engineering -- Computer programs -- Periodicals; Engineering -- Software -- Periodicals; Periodicals; 620.0028553
• DOI: 10.1016/j.advengsoft.2022.103399
• Languages: English
• ISSNs: 0965-9978

Abstract

Highlights: Damage detection in high-rise buildings. Finite element model updating using a link between SAP2000 commercial software and MATLAB. Inverse problem using a bio-inspired meta-heuristic optimization algorithm, named Termite life cycle optimizer (TLCO). Abstract: In this paper, for the first time, a damage assessment technique for a high-rise concrete structure is presented. This structure has sixteen stories, a total height of 57 m and its total long and short spans are 33 m. Especially, this structure has the appearance of shear wall and core wall elements, which has not yet investigated in the literature. For this purpose, a new Finite Element (FE) model updating technique is proposed based on the development of a successful program, which makes a link between SAP2000 commercial software and MATLAB program. This program allows the user to create a continuous two-way data exchange between SAP2000 and MATLAB. Thus, the process of parameters updating in the FE model in SAP2000 can be implemented by command in the code instead of by point-click procedures. The process of structural damage assessment is then secured by inverse methods. This method will be handled by a bio-inspired meta-heuristic optimization algorithm, namely Termite Life Cycle Optimizer (TLCO), which is proposed by the authors recently. The parameters in TLCO are fixed. Therefore, it is not necessary for the user to set the initial parameters, which is an effective strategy compared to other algorithms. The results obtained in this study show a significant improvement in the damage identification of large-scale structures.