The performance prediction and optimization of the fiber-reinforced composite structure with uncertain parameters

Abstract

The fiber-reinforced composites display the random fiber orientations and uncertain material parameters because of the manufacturing error and scattering feature. For this problem, the uncertain prediction and optimization based on the transformed perturbation stochastic method, the edged-based smoothing technique and the optimization theory is presented. In this method, the non-Gaussian probability density functions and the cumulative distribution functions of multi-variables for stochastic static responses of fiber-reinforced composite structure are explicitly exhibited as the prediction result compared with the Monte Carlo solution. Unlike the direct MCs, it only needs an iteration as the FEM and has the potential in the complex construction. In order to improve the efficiency and capability to resist the mesh distortion compared with the traditional stochastic FEM, the edged-based smoothing technique is introduced into the present framework. Furthermore, the stable performance feature of the fiber-reinforced composite in the uncertain working condition is presented. Consequently, objectives of the structural stability and insensitivity criteria based on the second-order perturbation expansion are proposed, and overall uncertain conditions coupled by uncertain fiber orientation, external load, material parameters and geometry sizes are analyzed and optimized within this framework, respectively. To verify the effectiveness and accuracy of the uncertain analysis and optimization in this study, three examples including the composite plates, the composite shell and the composite top cover of automobile are provided.