A Novel Artificial Bee Colony Algorithm for Structural Damage Detection

Zhao, Yinghao; Yan, Quansheng; Yang, Zheng; Yu, XiaoLin; Jia, Buyu

doi:10.1155/2020/3743089

Cited by 37 publications

(24 citation statements)

References 31 publications

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“…Artificial neural networks (ANNs) have lately received a lot of attention as a novel way of processing data [ 116 , 117 , 118 , 119 , 120 ]. ANN attempts to mathematically simulate biological brain neural networks [ 121 , 122 , 123 , 124 , 125 ].…”

Section: Methodsmentioning

confidence: 99%

Application of Polyacrylic Hydrogel in Durability and Reduction of Environmental Impacts of Concrete through ANN

Peng

Zandi

et al. 2022

Gels

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While adding superabsorbent polymer hydrogel particles to fresh concrete admixtures, they act as internal curing agents that absorb and then release large amounts of water and reduce self-desiccation and volumetric shrinkage of cement that finally result in hardened concrete with increased durability and strength. The entrainment of microscopic air bubbles in the concrete paste can substantially improve the resistance of concrete. When the volume and distribution of entrained air are adequately managed, the microstructure is protected from the pressure produced by freezing water. This study addresses the design and application of hydrogel nanoparticles as internal curing agents in concrete, as well as new findings on crucial hydrogel–ion interactions. When mixed into concrete, hydrogel particles produce their stored water to power the curing reaction, resulting in less volumetric shrinkage and cracking and thereby prolonging the service life of concrete. The mechanical and swelling performance qualities of the hydrogel are very sensitive to multivalent cations found naturally in concrete mixes, such as aluminum and calcium. The interactions between hydrogel nanoparticles and alkaline cementitious mixes are described in this study, while emphasizing how the chemical structure and shape of the hydrogel particles regulate swelling behavior and internal curing efficiency to eliminate voids in the admixture. Moreover, in this study, an artificial neural network (ANN) was utilized to precisely and quickly analyze the test results of the compressive strength and durability of concrete. The addition of multivalent cations reduced swelling capacity and changed swelling kinetics, resulting in fast deswelling behavior and the creation of a mechanically stiff shell in certain hydrogel compositions. Notably, when hydrogel particles were added to a mixture, they reduced shrinkage while encouraged the creation of particular inorganic phases within the void area formerly held by the swelled particle.

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Section: Methodsmentioning

confidence: 99%

Application of Polyacrylic Hydrogel in Durability and Reduction of Environmental Impacts of Concrete through ANN

Peng

Zandi

et al. 2022

Gels

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“…In recent years, different types of AI methods have been deployed and remarkable results have been obtained compared to other techniques 80–84 . Artificial neural network (ANN), Adaptive neuro‐fuzzy inference system (ANFIS), Machine learning, Extreme Learning Machine (ELM), Particle Swarm Optimization (PSO), etc as subsets of the AI are utilized for data analysis 85–89 …”

Section: Methodsmentioning

confidence: 99%

Artificial intelligent modeling and optimization of the application of aluminum oxide nanoparticles modified cement asphalt toward non‐polluted sustainable environment

Jia

Zandi

Agdas³

et al. 2022

Intl J of Energy Research

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Due to their excellent physicochemical and structural characteristics, aluminum oxide (AL 2 O 3 ) nanoparticles (AlNPs), a family of metal oxide nanoparticles, offer a variety of biological uses. Bitumen binds a high percentage (>95%) of inorganic macrometer-sized particles to provide a cohesive material suitable for use in road pavement. In this study, AL 2 O 3 was added to bitumen as a new bitumen modification to improve the fatigue and rutting performance of bitumen or the base cement asphalt cement (AC) at ratios of 5, 7, and 10% wt by weight of the cement AC. Rheological tests were performed on modified bitumen containing nanoparticles. An extreme learning machine (ELM) analyzes each test outcome. In this case, the properties of AC are greatly affected by the rise in AL 2 O 3 concentration. In comparison to the basic AC, the modified AC's viscosity rose by 90 and 104%, respectively. The outcomes also demonstrated the excellent compatibility and storage stability of both modifiers at high temperatures. A hot mix of AL 2 O 3 modified bitumen was utilized to produce hot cement asphalt samples, and moisture susceptibility was assessed. As a result,

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“…rough the numerical simulation and the experiment of a 3-story building rigid frame, the results show that regardless of weak damage or multiple damages, the identification accuracy is very high and the noise immunity is better. Zhao et al [28] combined the tabu search method and chaos search method to optimize the artificial bee colony algorithm and improved the exploration and development ability of the algorithm. e numerical simulation and experiment proved that the proposed method can effectively identify structural damage and has good robustness under the condition of sufficient measurement data.…”

Section: Introductionmentioning

confidence: 99%

Research on Damage Identification of Nonuniform Microcrack in Beam Structures

Guo

Guan

Pan

2021

Advances in Civil Engineering

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Nonuniform microcrack identification is of great significance in mechanical, aerospace, and civil engineering. In this study, the nonuniform crack is simplified as a semielliptical crack, and simplified calculation methods are proposed for damage severity and damage identification of semielliptical cracks. The proposed methods are based on the calculation method for uniform cracks. The wavelet transform and the intelligent algorithm (IA) are used to identify the damage location and the damage severity of the structure, respectively. The singularity of the wavelet coefficient can be used to identify the signal singularity quickly and accurately, and IA efficiently and accurately calculates the structural damage severity. The particle swarm optimization (PSO) algorithm and the genetic algorithm (GA), widely used, are applied to identify the damage severity of the beam. Numerical simulations and experimental analyses of beams with transfixion and semielliptical cracks are carried out to evaluate the accuracy of the semielliptical crack calculation method and the method of wavelet analysis combined with PSO and GA for nonuniform crack identification. The results show that the wavelet-particle swarm optimization (WPSO) and the wavelet-genetic algorithm (WGA) can accurately and efficiently identify the structural semielliptical damage location and severity and that these methods are not easily influenced by noise. The damage severity calculation method for semielliptical cracks can accurately calculate the semielliptical size and can be used to identify damage in beams with semielliptical cracks.

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A Novel Artificial Bee Colony Algorithm for Structural Damage Detection

Cited by 37 publications

References 31 publications

Application of Polyacrylic Hydrogel in Durability and Reduction of Environmental Impacts of Concrete through ANN

Application of Polyacrylic Hydrogel in Durability and Reduction of Environmental Impacts of Concrete through ANN

Artificial intelligent modeling and optimization of the application of aluminum oxide nanoparticles modified cement asphalt toward non‐polluted sustainable environment

Research on Damage Identification of Nonuniform Microcrack in Beam Structures

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