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An intelligent computer method for vibration responses of the spinning multi-layer symmetric nanosystem using multi-physics modeling

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Abstract

This article is the first attempt to employ deep learning to estimate the frequency performance of the rotating multi-layer nanodisks. The optimum values of the parameters involved in the mechanism of the fully connected neural network are determined through the momentum-based optimizer. The strength of the method applied in this survey comes from the high accuracy besides lower epochs needed to train the multi-layered network. It should be mentioned that the current nanostructure is modeled as a nanodisk on the viscoelastic substrate. Due to rotation, the centrifugal and Coriolis effects are considered. Hamilton’s principle and generalized differential quadrature method (GDQM) are presented for obtaining and solving the governing equations of the high-speed rotating nanodisk on a viscoelastic substrate. The outcomes show that the number of layers viscoelastic foundation, angular velocity speed, angle of ply, nonlocal, and length-scale parameters have a considerable impact on the amplitude and vibration behavior of a laminated rotating cantilevered nanodisk. As an applicable result in related industries, in the initial value of radius ratio, damping of the foundation does not have any effect on the dynamics of the system, but when the outer radius is bigger enough, the effect of damping parameter on the frequency of the laminated nanostructure will be bold sharply.

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Authors and Affiliations

  1. Huawei School of Technology, Weifang University of Science and Technology, Weifang, 262700, Shandong, China

    Jianli Guo

  2. Shandong Provincial University Laboratory for Protected Horticulture, Weifang University of Science and Technology, Weifang, 262700, Shandong, China

    Jianli Guo

  3. Department of Physics, Lorestan University, Khorramabad, Iran

    Abdolrahim Baharvand

  4. South Ural State University, Chelyabinsk, Russian Federation

    Diana Tazeddinova

  5. Zhangir Khan West Kazakhstan Agrarian Technical University, Uralsk, Kazakhstan

    Diana Tazeddinova

  6. Institute of Research and Development, Duy Tan University, Da Nang, 550000, Vietnam

    Mostafa Habibi

  7. Faculty of Electrical–Electronic Engineering, Duy Tan University, Da Nang, 550000, Vietnam

    Mostafa Habibi

  8. Center of Excellence in Design, Robotics, and Automation, Department of Mechanical Engineering, Sharif University of Technology, Azadi Avenue, P.O. Box 11365-9567, Tehran, Iran

    Mostafa Habibi

  9. Faculty of Engineering, Department of Mechanics, Imam Khomeini International University, Qazvin, Iran

    Hamed Safarpour

  10. Facultad de Ciencias de la Salud, Programa Magister en Ciencias Químico-Biológicas, Universidad Bernardo O’Higgins, Santiago, Chile

    Angel Roco-Videla

  11. Departamento de Ingeniería Civil, Facultad de Ingeniería, Universidad Católica de la Santísima Concepción, Concepción, Chile

    Angel Roco-Videla

  12. Department of Civil Engineering, College of Engineering, Prince Sattam Bin Abdulaziz University, 11942, Al-Kharj, Saudi Arabia

    Abdellatif Selmi

  13. Civil Engineering Laboratory, Ecole Nationale d’Ingénieurs deTunis (ENIT), Le belvedere, B.P. 37, 1002, Tunis, Tunisia

    Abdellatif Selmi

Authors
  1. Jianli Guo
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  2. Abdolrahim Baharvand
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  3. Diana Tazeddinova
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  4. Mostafa Habibi
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  5. Hamed Safarpour
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  6. Angel Roco-Videla
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  7. Abdellatif Selmi
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Correspondence to Abdolrahim Baharvand.

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Guo, J., Baharvand, A., Tazeddinova, D. et al. An intelligent computer method for vibration responses of the spinning multi-layer symmetric nanosystem using multi-physics modeling. Engineering with Computers 38 (Suppl 5), 4217–4238 (2022). https://doi.org/10.1007/s00366-021-01433-4

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