Enhancing buckling performance of perforated composite laminates by manipulating fiber direction using a genetic algorithm

Cho, Hee Keun; Rowlands, R. E.

doi:10.1007/s12206-015-0818-2

Cited by 7 publications

(3 citation statements)

References 17 publications

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“…The stress concentration, at a certain point, causes a cohesion break of the thin layer of the matrix and the occurrence of a delamination fracture in a relatively large area. Local buckling and stress concentrations are characteristic phenomena occurring in laminated structures [ 63 , 64 ]. This is also the cause of buckling of the upper reinforcement layer and a rapid loss of a part of the load capacity by the beam.…”

Section: Resultsmentioning

confidence: 99%

Failure Progress of 3D Reinforced GFRP Laminate during Static Bending, Evaluated by Means of Acoustic Emission and Vibrations Analysis

Kozioł

Figlus

2015

Materials

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The work aimed to assess the failure progress in a glass fiber-reinforced polymer laminate with a 3D-woven and (as a comparison) plain-woven reinforcement, during static bending, using acoustic emission signals. The innovative method of the separation of the signal coming from the fiber fracture and the one coming from the matrix fracture with the use of the acoustic event’s energy as a criterion was applied. The failure progress during static bending was alternatively analyzed by evaluation of the vibration signal. It gave a possibility to validate the results of the acoustic emission. Acoustic emission, as well as vibration signal analysis proved to be good and effective tools for the registration of failure effects in composite laminates. Vibration analysis is more complicated methodologically, yet it is more precise. The failure progress of the 3D laminate is “safer” and more beneficial than that of the plain-woven laminate. It exhibits less rapid load capacity drops and a higher fiber effort contribution at the moment of the main laminate failure.

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Section: Resultsmentioning

confidence: 99%

Failure Progress of 3D Reinforced GFRP Laminate during Static Bending, Evaluated by Means of Acoustic Emission and Vibrations Analysis

Kozioł

Figlus

2015

Materials

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“…Koide et al (2015aKoide et al ( , 2015b used Latin hypercube sampling to train the metamodels and subsequently used these metamodels for prediction of the buckling load of laminated composite plate. Cho and Rowlands (2015) used genetic algorithm and FEM to optimize the laminated composite plate so that maximum buckling loads can be obtained. Cho and Rowlands (2015) used a perforated laminated composite skew plate for analysis.…”

Section: Introductionmentioning

confidence: 99%

“…Cho and Rowlands (2015) used genetic algorithm and FEM to optimize the laminated composite plate so that maximum buckling loads can be obtained. Cho and Rowlands (2015) used a perforated laminated composite skew plate for analysis. Gu et al (2018) used machine learning and FE analysis to design hierarchical materials.…”

Section: Introductionmentioning

confidence: 99%

Buckling of laminated composite skew plate using FEM and machine learning methods

Mishra

Kumar

Samui

et al. 2020

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Purpose The purpose of this paper is to attempt the buckling analysis of a laminated composite skew plate using the C0 finite element (FE) model based on higher-order shear deformation theory (HSDT) in conjunction with minimax probability machine regression (MPMR) and multivariate adaptive regression spline (MARS). Design/methodology/approach HSDT considers the third-order variation of in-plane displacements which eliminates the use of shear correction factor owing to realistic parabolic transverse shear stresses across the thickness coordinate. At the top and bottom of the plate, zero transverse shear stress condition is imposed. C0 FE model based on HSDT is developed and coded in formula translation (FORTRAN). FE model is validated and found efficient to create new results. MPMR and MARS models are coded in MATLAB. Using skew angle (α), stacking sequence (Ai) and buckling strength (Y) as input parameters, a regression problem is formulated using MPMR and MARS to predict the buckling strength of laminated composite skew plates. Findings The results of the MPMR and MARS models are in good agreement with the FE model result. MPMR is a better tool than MARS to analyze the buckling problem. Research limitations/implications The present work considers the linear behavior of the laminated composite skew plate. Originality/value To the authors’ best of knowledge, there is no work in the literature on the buckling analysis of a laminated composite skew plate using C0 FE formulation based on third-order shear deformation theory in conjunction with MPMR and MARS. These machine-learning techniques increase efficiency, reduce the computational time and reduce the cost of analysis. Further, an equation is generated with the MARS model via which the buckling strength of the laminated composite skew plate can be predicted with ease and simplicity.

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Hierarchical optimization of the composite blade of a stratospheric airship propeller based on genetic algorithm

Meng

Xiao

et al. 2017

Struct Multidisc Optim

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Enhancing buckling performance of perforated composite laminates by manipulating fiber direction using a genetic algorithm

Cited by 7 publications

References 17 publications

Failure Progress of 3D Reinforced GFRP Laminate during Static Bending, Evaluated by Means of Acoustic Emission and Vibrations Analysis

Failure Progress of 3D Reinforced GFRP Laminate during Static Bending, Evaluated by Means of Acoustic Emission and Vibrations Analysis

Buckling of laminated composite skew plate using FEM and machine learning methods

Hierarchical optimization of the composite blade of a stratospheric airship propeller based on genetic algorithm

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