Combined joint and member damage identification of skeletal structures by an improved biology migration algorithm

Aval, Seyed Bahram Beheshti; Mohebian, Pooya

doi:10.1007/s13349-020-00390-8

Cited by 12 publications

(2 citation statements)

References 32 publications

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“…In this study, the severity of joint damage was simulated by reducing the fixity factors of the joints [ 40 ]. Equation (2) presents the 2D stiffness matrix of a semi-rigid frame member based on the Euler–Bernoulli beam theory [ 41 ].

where parameter

is defined using joint fixity factors γ 1 and γ 2 as follows:

…”

Section: Formulation For Parameter Identificationmentioning

confidence: 99%

Parameter Identification of Multispan Rigid Frames Using a Stiffness Separation Method

Xiao,

Yan,

Meng

et al. 2024

Sensors

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Identifying the parameters of multispan rigid frames is challenging because of their complex structures and large computational workloads. This paper presents a stiffness separation method for the static response parameter identification of multispan rigid frames. The stiffness separation method segments the global stiffness matrix of the overall structure into the stiffness matrices of its substructures, which are to be computed, thereby reducing the computational workload and improving the efficiency of parameter identification. Loads can be applied individually to each separate substructure, thereby guaranteeing obvious local static responses. The veracity and efficacy of the proposed methodology are substantiated by applying it to three- and eight-span continuous rigid frame structures. The findings indicate that the proposed approach significantly enhances the efficiency of parameter identification for multispan rigid frames.

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where parameter

is defined using joint fixity factors γ 1 and γ 2 as follows:

…”

Section: Formulation For Parameter Identificationmentioning

confidence: 99%

Parameter Identification of Multispan Rigid Frames Using a Stiffness Separation Method

Xiao,

Yan,

Meng

et al. 2024

Sensors

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“…An improved biology migration algorithm is employed in this method to minimize the hybrid objective function. [47] Gomes et al compared the efficiency of sunflower optimization algorithm and a traditional optimization algorithm in dealing with the damage detection problem of laminated composite plates. [48] Previously, numerous methods based on machine learning have been addressed in structural health assessment literature.…”

Section: Introductionmentioning

confidence: 99%

Multiverse optimizer for structural damage detection: Numerical study and experimental validation

Ghannadi

Kourehli

2020

Structural Design Tall Build

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New optimization algorithms have been increasingly developed in the course of the recent years. The accuracy of identified results in optimization-based damage detection methods depends on the objective function and optimization algorithm. This paper employs multiverse Optimizer (MVO) to solve the optimization-based damage identification problem. Statistical results obtained by MVO are compared with those of sine cosine algorithm (SCA) and Harris hawks optimization (HHO) in order to perform a comparative study. Two objective functions are used in this optimization problem. The first one is based on the modal assurance criterion (MAC) and the second one on modified total modal assurance criterion (MTMAC). Numerical and experimental examples indicate that the combination of objective function based on MTMAC and MVO algorithm can provide accurate and reliable results in structural damage detection process. MAC is also rejected in competition with MTMAC. While using SCA-MTMAC, the accuracy of the results is acceptable in some cases. However, HHO-MTMAC gives weak results in most cases. MVO and SSA are the lowest, and HHO spends significantly more time in terms of computational cost.

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A Two-Stage Method for Damage Identification in Concrete Gravity Dams by Using a Modal Curvature-Based Index and Pathfinder Algorithm

Mohebian,

Motahari,

Aval

2023

Arab J Sci Eng

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Combined joint and member damage identification of skeletal structures by an improved biology migration algorithm

Cited by 12 publications

References 32 publications

Parameter Identification of Multispan Rigid Frames Using a Stiffness Separation Method

Parameter Identification of Multispan Rigid Frames Using a Stiffness Separation Method

Multiverse optimizer for structural damage detection: Numerical study and experimental validation

A Two-Stage Method for Damage Identification in Concrete Gravity Dams by Using a Modal Curvature-Based Index and Pathfinder Algorithm

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