A new robust flexibility index for structural damage identification and quantification. (November 2021)

• Record Type: Journal Article
• Authors: Khatir, Samir; Tiachacht, Samir; Le Thanh, Cuong; Tran-Ngoc, Hoa; Mirjalili, Seyedali; Abdel Wahab, Magd
• Is Part Of: Engineering failure analysis. Volume 129(2021)
• Publication Date: 2021-11
• Subjects: Complex Structures -- Atom Search Optimization -- Inverse Problem -- Damage quantification -- Modal analysis -- Salp Swarm Optimizer; System failures (Engineering) -- Periodicals; Fracture mechanics -- Periodicals; Reliability (Engineering) -- Periodicals; Pannes -- Périodiques; Rupture, Mécanique de la -- Périodiques; Fiabilité -- Périodiques; Fracture mechanics; Reliability (Engineering); System failures (Engineering); Periodicals; Electronic journals; 620.112
• DOI: 10.1016/j.engfailanal.2021.105714
• Languages: English
• ISSNs: 1350-6307

Abstract

Highlights: Enhanced flexibility indicator for damage detection. Atom Search Optimization for damage quantification. Complex planar truss and space truss dome structures. Damage assessment in Canton Tower. Abstract: In this paper, an enhanced damage indicator using a flexibility index is presented and applied to different complex structures to predict the exact location of damage. Finite Element Method (FEM) is used to model three complex structures, namely a 37-bar planar truss, a 52-bar planar truss, and a 52-bar space truss (Dome structure) to study the effectiveness of the proposed indicator. Single and multiple damage scenarios with different damage levels are considered. The results show that the proposed indicator provides an accurate location of damage. Next, to quantify the damage and assess its severity, two optimization techniques, namely Atom Search Optimization (ASO) and Salp Swarm Optimizer (SSA), which are recently invented, are used to solve an inverse problem. The objective function is based on the measured and calculated enhanced damage indicators. Both optimization techniques provide good results, however the convergence performance and CPU time are better for ASO than SSA. Finally, the proposed approach is tested using a benchmark structure, namely a high-rise tower (Guangzhou TV Tower) to predict the damage location at different floors. The results indicate that the proposed methodology is accurate and fast to predict single and multiple damages.