Analytical models to predict the compressive strength of unidirectional composites along fiber direction are either based on microbuckling, kinking of fibers or fiber splitting. Experiments showed that all those mechanisms are together responsible for the failure. The present work evaluates and compares some of the existing models proposed for predicting the compressive strength of unidirectional composites. As an attempt to evaluate analytical models that can be used for the design purposes with a greater degree of confidence, and are easy to use and computationally simple. Experimentally, the determination of lamina compressive strength and modulus using simple fixture of Combined Loading Compression (CLC) test method was investigated. In this test method a tabbed, [0] 12 test coupons were tested in uniaxial compression to measure the longitudinal modulus and strength of IM7/8552 CFRP. Nomenclature F1c = ultimate compressive strength in fiber direction Vf = fiber volume fraction Em = matrix modulus of elasticity Ef = fiber modulus of elasticity Gm = matrix modulus of rigidity Gf = fiber modulus of rigidity k = bonding parameter rf = fiber radius m = matrix Poisson's ratio f = fiber Poisson's ratio = matrix slippage coefficient = fiber-matrix bond condition E = effective axial stiffness of the lamina l = fiber length = end condition coefficient = misalignment angle Hp = stress dependent tangent modulus of the uniaxial stress/plastic strain curve = matrix elastic-plastic shear modulus by incremental theory of plasticity = matrix elastic-plastic shear modulus by deformation theory of plasticity = ultimate tensile yield strength = ultimate shear yield strength = kink band angle n = hardening coefficient = ultimate shear yield strain t = specimen thickness w = specimen width = critical interfacial surface energy G12 = effective shear modulus of the lamina h = gage length E11 = effective Young's modulus of the lamina = effective bending flexural modulus of the lamina Gxz = effective transverse shear modulus of the lamina I = specimen cross-section second moment of area
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.