In this paper, in the domain of 1D-membrane micro-electro-mechanical systems in which the electrostatic field is expressed in terms of geometric curvature of the membrane, we present a numerical approach based on shooting techniques to reconstruct the membrane profile in the device in steady-state case. In particular, starting from known results in literature about existence achieved by Schauder–Tychonoff’s fixed point approach and uniqueness, and focusing on two physical–mathematical parameters appropriately indicative of the applied voltage and electromechanical properties of the membrane, respectively, we will discuss what operation parameters (applied voltage, amplitude of electrostatic field) and for which electromechanical membrane characteristic of the device is permitted or not a convergence of the method with respect to analytical results. Finally, we will discuss in detail the detected ghost solutions.

Reconstructing the Membrane Detection of a 1D Electrostatic Driven MEMS Device by Using the Shooting Method: Convergence Analysis and Ghost Solutions Identification

A. Jannelli
Secondo
;
2018-01-01

Abstract

In this paper, in the domain of 1D-membrane micro-electro-mechanical systems in which the electrostatic field is expressed in terms of geometric curvature of the membrane, we present a numerical approach based on shooting techniques to reconstruct the membrane profile in the device in steady-state case. In particular, starting from known results in literature about existence achieved by Schauder–Tychonoff’s fixed point approach and uniqueness, and focusing on two physical–mathematical parameters appropriately indicative of the applied voltage and electromechanical properties of the membrane, respectively, we will discuss what operation parameters (applied voltage, amplitude of electrostatic field) and for which electromechanical membrane characteristic of the device is permitted or not a convergence of the method with respect to analytical results. Finally, we will discuss in detail the detected ghost solutions.
2018
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3120223
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