Sensitivity Analysis of a CPAM Inverse Algorithm for Composite Laminates Characterization

Using experimental data and numerical simulations, a new combined technique is presented for characterization of thin and thick orthotropic composite laminates. Four or five elastic constants, as well as ply orientation angles, are considered as the unknown parameters. The material characterization...

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Bibliographic Details
Main Authors: Farshid Masoumi, Ahmad Ghasemi Ghalebahman
Format: Article
Language:English
Published: Hindawi Limited 2017-01-01
Series:Shock and Vibration
Online Access:http://dx.doi.org/10.1155/2017/2821873
Description
Summary:Using experimental data and numerical simulations, a new combined technique is presented for characterization of thin and thick orthotropic composite laminates. Four or five elastic constants, as well as ply orientation angles, are considered as the unknown parameters. The material characterization is first examined for isotropic plates under different boundary conditions to evaluate the method’s accuracy. The proposed algorithm, so-called CPAM (Combined Programs of ABAQUS and MATLAB), utilizes an optimization procedure and makes simultaneous use of vibration test data together with their corresponding numerical solutions. The numerical solutions are based on a commercial finite element package for efficiently identifying the material properties. An inverse method based on particle swarm optimization algorithm is further provided using MATLAB software. The error function to be minimized is the sum of squared differences between experimental and simulated data of eigenfrequencies. To evaluate the robustness of the model’s results in the presence of uncertainty and unwanted noises, a sensitivity analysis that employs Gaussian disorder model is directly applied to the measured frequencies. The results with high accuracy confirm the validity and capability of the present method in simultaneous determination of mechanical constants and fiber orientation angles of composite laminates as compared to prior methods.
ISSN:1070-9622
1875-9203