Elastic constants identification of symmetric angle-ply laminates via a two-level optimization approach

Abstract

A two-level optimization method for elastic constants identification of symmetric angle-ply laminates is presented. Measured axial and lateral strains of two symmetric angle-ply laminates with different fiber angles are used in the proposed method to identify four elastic constants of the composite laminates. In the first-level optimization process, the theoretically and experimentally predicted axial and lateral strains of a [(45 degrees/-45 degrees)(2)](s) laminate are used to construct the error function which is a measure of the differences between the experimental and theoretical predictions of the axial and lateral strains. The identification of the material constants is then formulated as a constrained minimization problem in which the best estimates of the shear modulus and Poisson's ratio of the laminate are determined by making the error function a global minimum. The problem of this level of optimization is then solved using a multi-start global minimization algorithm. In the second-level optimization process, the shear modulus and Poisson's ratio determined in the previous level of optimization are kept constant while the Young's moduli of the second angle-ply laminate with fiber angles other than 45 degrees are identified using the same minimization technique that has been used in the previous level. The accuracy of the proposed method are studied by means of a number of numerical examples on the material constants identification of symmetric angle-ply laminates made of different composite materials. Finally, static tensile tests of [(45 degrees/-45 degrees)(2)](s) and [(30 degrees/-30 degrees)(2)](s) laminates made of Gr/ep composite material are performed to measure the strains of the laminates. The experimental data are then used to identify the elastic constants of the laminates. The excellent results obtained in the experimental investigation have demonstrated the feasibility and applications of the proposed method. (c) 2006 Elsevier Ltd. All rights reserved.