Identification of delamination severity in a tapered FRP composite plate

Moorthy, Venkatesan; Marappan, Karthikeyan

doi:10.1016/j.compstruct.2022.116054

Cited by 7 publications

(2 citation statements)

References 54 publications

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“…[18,19] also indicate the same results. However, the damaged position/s are di cult to be located using frequencies (undamaged and damaged) alone [20,26]. The results extracted ( rst frequency and its mode shape) from Abaqus have been utilized as input in the MATLAB software to quantify the DI's using GFEQD method as illustrated in step 2.…”

Section: Validationmentioning

confidence: 99%

Quantification of Damages in Laminated Composite Plates through Artificial Neural Network utilizing Generalized Flexibility Method

Hanumanthappa,

Imdadi,

Emani

2024

Preprint

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In this paper, single and many damages are detected at different places of the three-layered laminated cross-ply (0°/90°/0°) composite plate using Generalized Flexibility Energy Quotient Difference Method (GFEQDM) utilizing the first mode. Only first natural frequency and its mode shape are utilized which constitute the major advantage in the proposed method, as they are easy to capture practically. During the first phase, the Generalized Flexibility Energy Quotient Difference Ratio (β) is calculated at different points on the plate using the elements' reduced modulus of elasticity. In the second phase, the β computed at all locations of the plate for various damaged elements are used as input, in ANN and the damage indices at the damaged locations are taken as output. These results clearly demonstrate the acceptability of the suggested approach, which finds use in averting structural failure. Finally, the damage is quantified by developing the relevant equations.

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Section: Validationmentioning

confidence: 99%

Quantification of Damages in Laminated Composite Plates through Artificial Neural Network utilizing Generalized Flexibility Method

Hanumanthappa,

Imdadi,

Emani

2024

Preprint

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“…They used one-dimensional equivalent through-thickness beam elements to model the composite beam and to identify the potential delamination locations. Moorthy and Marappan [31] identi ed the delamination severity in tapered ber-reinforced polymer laminated composite plates by using the Surrogate-Assisted Realcoded Genetic Algorithm (SARGA) and ANNs. The analysis results indicated that although SARGA and ANNs give good prediction results for the numerical data, ANNs fail to predict delamination regarding experimental results.…”

Section: Introductionmentioning

confidence: 99%

Delamination Localization in the Composite Thin Plates Using Ensemble Learning: Bagging and Boosting Techniques

Daş

2023

Scientia Iranica

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Localization of the delamination is an essential task that is conducted via various approaches, which may require time, experts, and cost. Various intelligent nondestructive techniques are utilized to reduce time consumption, the need for expertise, and expenditures. Yet, developing an accurate, robust, and low-cost intelligent delamination identi cation technique becomes a challenging task due to the anisotropy and the variation in the ber orientation of the composites. Based on those issues, it is aimed to develop an e ective intelligent model to localize delaminations in composite plates. This study measures the performance of the Bagging and Boosting techniques on delamination localization in thin composite plates. To validate the e ectiveness of the proposed approaches; cross-ply, angle-ply, and quasi-isotropic composite plates having 2400 di erent delamination cases are considered. The bagging and boosting models are trained with the vibrational characteristics of the healthy and delaminated composite structures. The free vibration analysis is conducted for those structures to obtain the rst ve natural frequencies and the corresponding mode shapes. For this purpose, classical plate theory is employed by using nite element analysis. It is concluded that bagging and boosting techniques are robust, precise, and accurate in localizing delamination.

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Enhancement of tensile strength of tapered laminates by utilizing thin-ply composites

Hua

Higuchi²,

Yokozeki³

2023

Composites Part B: Engineering

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Identification of delamination severity in a tapered FRP composite plate

Cited by 7 publications

References 54 publications

Quantification of Damages in Laminated Composite Plates through Artificial Neural Network utilizing Generalized Flexibility Method

Quantification of Damages in Laminated Composite Plates through Artificial Neural Network utilizing Generalized Flexibility Method

Delamination Localization in the Composite Thin Plates Using Ensemble Learning: Bagging and Boosting Techniques

Enhancement of tensile strength of tapered laminates by utilizing thin-ply composites

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