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IOP Conference Series: Materials Science and Engineering PAPER • OPEN ACCESS Parametric uncertainty quantification in natural frequency of sandwich plates using polynomial neural network To cite this article: P. K. Karsh et al 2020 IOP Conf. Ser.: Mater. Sci. Eng. 798 012036 View the article online for updates and enhancements. You may also like Free vibration and buckling of porous power-law and sigmoid functionally graded sandwich plates using a simple higher- order shear deformation theory Ahmed Amine Daikh and Ashraf M Zenkour - Influence of LiClO 4 Concentration on 1-D Polypyrrole Nanofibers for Enhanced Performance of Glucose Biosensor Pramila Jakhar, Mayoorika Shukla and Vipul Singh - Effect of porosity on the bending analysis of various functionally graded sandwich plates Ahmed Amine Daikh and Ashraf M Zenkour - This content was downloaded from IP address 171.243.67.90 on 01/06/2023 at 02:58
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Parametric uncertainty quantification in natural frequency of sandwich plates using polynomial neural network

Jun 02, 2023

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In this paper, uncertainty quantification in natural frequencies for laminated soft core sandwich plates is presented by employing finite element (FE) coupled polynomial neural network (PNN) approach. The computational efficiency and accuracy is achieved by using PNN as surrogate model. Latin hypercube sampling method is employed for training of data in PNN model. The stochastic first three natural frequencies of sandwich plates are studied for individual variation in input parameters. The stochasticity in individual input parameters are considered in order to assess their influence on global response of the structure

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