Tuning nonlinear stiffness of circular membranes by design optimization

Master Thesis (2023)
Author(s)

M. Nasirshoaibi (TU Delft - Mechanical Engineering)

Contributor(s)

Farbod Alijani – Mentor (TU Delft - Dynamics of Micro and Nano Systems)

A. Sarafraz – Coach (TU Delft - Dynamics of Micro and Nano Systems)

Faculty
Mechanical Engineering
Copyright
© 2023 Mehrdad Nasirshoaibi
More Info
expand_more
Publication Year
2023
Language
English
Copyright
© 2023 Mehrdad Nasirshoaibi
Graduation Date
22-11-2023
Awarding Institution
Delft University of Technology
Programme
Mechanical Engineering | Micro and Nano Engineering
Faculty
Mechanical Engineering
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

While nonlinear phenomena in mechanical systems are well understood, strategies for designing structures that exhibit certain nonlinear responses have received little attention. Design optimization is a systematic and iterative process aimed at improving the performance and efficiency of a system. It involves exploring various design choices and parameters to find the best possible solution that meets specific criteria or objective, such as maximizing or minimizing nonlinearity. The use of design optimization techniques for tuning nonlinear dynamics has important implications for the development of micro- and nano-scale devices. By optimizing the nonlinear response of these devices, it is possible to achieve enhanced performance, and better control over their nonlinear behaviour.

In my thesis, I have devised a novel methodology that empowers us to optimize the nonlinear vibration characteristics of devices. My work extends to the development of a versatile routine capable of defining complex geometries and facilitating design within a Finite Element Method (FEM) framework. This routine operates in tandem with optimization algorithms, enabling us to identify and refine the most optimal designs in terms of strength of nonlinearity, minimizing or maximizing it when desirable.

Files

Thesis_Final_.pdf
(pdf | 0 Mb)
- Embargo expired in 22-11-2024
License info not available