Buckling, postbuckling, and crippling of materially nonlinear laminated composite plates

Arnold, Rocky R.; Mayers, J.

doi:10.1016/0020-7683(84)90055-6

Cited by 25 publications

(9 citation statements)

References 7 publications

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“…Predictions were made using Equations (13) and (19) to calculate values for individual one-edge and no-edge free segments, and then Equation (1) was used to combine these results into a predicted failing load for the overall cross section. The values of E 1 (longitudinal elastic modulus), v 12 (Poisson's ratio in the 12 direction, E2 (transverse elastic modulus), and G (shear modulus) used in these calculations are provided in Table 2.…”

Section: Test Program Test Specimens and Prediction Of Resultsmentioning

confidence: 99%

“…The resulting curves are presented in a form clear enough for practical use by designers who wish to have a logical basis for crippling analysis of composite stiffeners, but who do not wish to use time-consuming large deflection finite element analysis. There is no question that large deflection finite element models such as employed by Spier and Wang [12] or the very thorough theoretical approach proposed by Arnold and Mayers [13] will provide more detail on the behavior of a composite stiffener as one progresses from initial loading up through ultimate failure. But for the initial sizing and optimization of a complete vehicle or large vehicle component, the design curves proposed here are adequate and are easier to use.…”

Section: Summary and Recommendationsmentioning

confidence: 99%

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Crippling of Titanium Matrix Composite Stiffeners

Fogarty

1992

Journal of Composite Materials

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Using established principles of laminate buckling theory and postbuckling load redistribution, a theory is derived for crippling analysis of specially orthotropic or very nearly specially orthotropic laminated composite stiffeners. Results from testing of SCS-6/Ti-15-3 titanium matrix composite (TMC) stiffener segments are also presented and show good correlation with theoretical predictions. The testing program includes three different layups, three different geometries, and a repetition of two tests for each possible geometry/layup combination for a total of 18 tests. The results of the theory are presented in the form of easy-to-use design curves.

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Section: Test Program Test Specimens and Prediction Of Resultsmentioning

confidence: 99%

Section: Summary and Recommendationsmentioning

confidence: 99%

Crippling of Titanium Matrix Composite Stiffeners

Fogarty

1992

Journal of Composite Materials

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“…Theoretical development in analytical analysis procedure to predict buckling, postbuckling and crippling phenomena of the laminated composite plate is given by Arnold and Mayers (1984). Arnold and Mayers (1984) studied graphite-epoxy simply supported plates for buckling, and their theoretical results evaluated are found in good agreement with the experimental results. Buckling analysis of functionally graded plates (FGP) for in-plane compressive loading conditions is investigated by Feldman and Aboudi (1997).…”

Section: Introductionmentioning

confidence: 84%

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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“…The subject is treated with classical bifurcation buckling analysis, plate equations and their solutions. Analytical analysis and development prediction of buckling and postbuckling is stated by Arnold and Mayers (1984). Sundaresan et al (1996) studied the buckling of thick laminated rectangular plates adopting the Mindlin's first-order shear deformation theory and von Karman's theory.…”

Section: Buckling Of Laminated Compositesmentioning

confidence: 99%

Laminated Composites Buckling Analysis Using Lamination Parameters, Neural Networks and Support Vector Regression

Koide

Ferreira

Luersen

2015

Lat. Am. j. solids struct.

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This work presents a metamodel strategy to approximate the buckling load response of laminated composite plates. In order to obtain representative data for training the metamodel, some laminates with different stacking sequences are generated using the Latin hypercube sampling plan. These stacking sequences are converted into lamination parameters so that the number of inputs of the metamodel becomes constant. The buckling load for each laminate of the training set are computed using finite elements. In this way the inputs-outputs metamodel training pairs are the lamination parameters and the corresponding bucking load. Neural network and support vector regression metamodels are employed to approximate the buckling load. The performances of the metamodels are compared in a test case and the results are shown and discussed.

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Buckling, postbuckling, and crippling of materially nonlinear laminated composite plates

Cited by 25 publications

References 7 publications

Crippling of Titanium Matrix Composite Stiffeners

Crippling of Titanium Matrix Composite Stiffeners

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

Laminated Composites Buckling Analysis Using Lamination Parameters, Neural Networks and Support Vector Regression

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