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Constituent Parameter Identification of Braided Composite Based on Sensitivity Analysis

Mechanical properties of the constituent material of fiber-reinforced braided composites will inevitably change after the manufacturing process. An approach to constituent parameters’ identification of braided composites was proposed to obtain the basic information of composites for structural analy...

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Detalles Bibliográficos
Autores principales: Jiang, Dong, Xie, Shitao, Qin, Furong, Zhang, Dahai, Zhu, Rui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9781644/
https://www.ncbi.nlm.nih.gov/pubmed/36556600
http://dx.doi.org/10.3390/ma15248794
Descripción
Sumario:Mechanical properties of the constituent material of fiber-reinforced braided composites will inevitably change after the manufacturing process. An approach to constituent parameters’ identification of braided composites was proposed to obtain the basic information of composites for structural analysis. Identification of the constituent parameters was transformed as an optimization problem, which was solved by adopting the sensitivity analysis method, iteratively minimizing the discrepancies between the numerically calculated displacement field and the measured displacement field. The sensitivity matrix of displacements with respect to the constituent parameters was directly derived based on the constitutive material model for the first time. Considering that the large magnitude differences between parameters will lead to an ill-posed problem of the sensitivity matrix, the identification was susceptible to noise from the experimental data, the relative sensitivity was adopted, and a condition number-based response point selection was applied to improve the robustness of the parameter identification. A 2.5-dimensional braided composite was employed to illustrate the constituent parameter identification method by comparing with the finite difference method. In addition, the influence of selected measuring points and measuring errors on the proposed method were discussed. The results showed that the proposed method can be used to identify the constituent parameters efficiently and accurately. When the measured displacements are polluted by noise, the condition number of the sensitivity matrix is an effective indicator of preceding information to enhance the identification accuracy.