Structural Engineering and Mechanics

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Application of artificial intelligence for solving the engineering problems

  • Xiaofei, Liu (School of Computer and Information, Anqing Normal University) ;
  • Xiaoli, Wang (Modern Educational Technology Center, Mudanjiang Medical University)
  • Received : 2021.09.11
  • Accepted : 2022.12.19
  • Published : 2023.01.10
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Abstract

Using artificial intelligence and internet of things methods in engineering and industrial problems has become a widespread method in recent years. The low computational costs and high accuracy without the need to engage human resources in comparison to engineering demands are the main advantages of artificial intelligence. In the present paper, a deep neural network (DNN) with a specific method of optimization is utilize to predict fundamental natural frequency of a cylindrical structure. To provide data for training the DNN, a detailed numerical analysis is presented with the aid of functionally modified couple stress theory (FMCS) and first-order shear deformation theory (FSDT). The governing equations obtained using Hamilton's principle, are further solved engaging generalized differential quadrature method. The results of the numerical solution are utilized to train and test the DNN model. The results are validated at the first step and a comprehensive parametric results are presented thereafter. The results show the high accuracy of the DNN results and effects of different geometrical, modeling and material parameters in the natural frequencies of the structure.

Keywords

Acknowledgement

This work was supported by Anhui Province Department of Education University Scientific Research Fund (KJ2019A0570), And this work was supported by Mudanjiang 2022 Guiding Science and Technology Plan Project: Research on Medical Image Segmentation Based on Deep Learning (2022JG110).

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