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An Efficient Analytical Approach for the Periodicity of Nano/Microelectromechanical Systems’ Oscillators

Author

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  • Naveed Anjum
  • Jamshaid Ul Rahman
  • Ji-Huan He
  • Md. Nur Alam
  • Muhammad Suleman
  • Francisco Lopez-Huerta

Abstract

Periodic behavior analysis of nano/microelectromechanical systems (N/MEMS) is an essential field owing to their many promising applications in microinstruments. The interesting and unique properties of these systems, particularly, small size, batch fabrication, low power consumption, and high reliability, have fascinated researchers and industries to implement these structures for the production of different microdevices. The dynamic oscillatory behavior of N/MEMS is very intricate due to the various types of nonlinearities present in these structures. The foremost objective of this study is to explore the periodicity of oscillatory problems from N/MEMS. The variational iteration method (VIM), which has been considered as an effective approach for nonlinear oscillators, is coupled with the Laplace transform to obtain the approximate analytic solution of these nonlinear vibratory systems with fewer computations. This coupling of VIM and Laplace transform not only helps in the identification of the Lagrange multiplier without getting into the details of the cryptic theory of variations, but also finds the frequency-amplitude relationship and the analytic approximate solution of N/MEMS. A generalized vibratory equation for N/MEMS is followed by three examples as special cases of this generalized equation are given to elucidate the effectivity of the coupling. The solution obtained from the Laplace-based VIM not only exhibits good agreement with observations numerically but also higher accuracy yields when compared to other established techniques in the open literature.

Suggested Citation

  • Naveed Anjum & Jamshaid Ul Rahman & Ji-Huan He & Md. Nur Alam & Muhammad Suleman & Francisco Lopez-Huerta, 2022. "An Efficient Analytical Approach for the Periodicity of Nano/Microelectromechanical Systems’ Oscillators," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-12, April.
  • Handle: RePEc:hin:jnlmpe:9712199
    DOI: 10.1155/2022/9712199
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    Cited by:

    1. Jamshaid Ul Rahman & Sana Danish & Dianchen Lu, 2024. "Oscillator Simulation with Deep Neural Networks," Mathematics, MDPI, vol. 12(7), pages 1-15, March.

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