Analysis of the Effect of Spatial Uncertainties on the Dynamic Behavior of Electrostatic Microactuators. (21st July 2016)

• Record Type: Journal Article
• Authors: Alwan, Aravind; Aluru, Narayana R.
• Is Part Of: Communications in computational physics. Volume 20:Number 2(2016:Aug.)
• Page Start: 279
• Page End: 300
• Publication Date: 2016-07-21
• Subjects: 02.50.Ey, -- 02.70.Dh, -- 02.70.Uu, -- 46.15.-x, -- 47.61.Fg; Uncertainty quantification, -- microelectromechanical systems (MEMS), -- electrostatic actuation, -- squeeze-film damping, -- roughness, -- random process, -- damping ratio; Mathematical physics -- Data processing -- Periodicals; Physics -- Data processing -- Periodicals; 530.150285
• DOI: 10.4208/cicp.220115.071215a
• Languages: English
• ISSNs: 1815-2406

Abstract

Abstract: This paper examines the effect of spatial roughness on the dynamical behaviour of electrostatic microactuators. We develop a comprehensive physical model that comprises a nonlinear electrostatic actuation force aswell as a squeeze-film damping term to accurately simulate the dynamical behavior of a cantilever beam actuator. Spatial roughness is modeled as a nonstationary stochastic process whose parameters can be estimated from profilometric measurements. We propagate the stochastic model through the physical system and examine the resulting uncertainty in the dynamical behavior that manifests as a variation in the quality factor of the device. We identify two distinct, yet coupled, modes of uncertainty propagation in the system, that result from the roughness causing variation in the electrostatic actuation force and the damping pressure, respectively. By artificially turning off each of these modes of propagation in sequence, we demonstrate that the variation in the damping pressure has a greater effect on the damping ratio than that arising from the electrostatic force. Comparison with similar simulations performed using a simplified mass-spring-damper model show that the coupling between these two mechanisms can be captured only when the physical model includes the primary nonlinear interactions along with a proper treatment of spatial variations. We also highlight the difference between nonstationary and stationary covariance formulations by showing that the stationary model is unable to properly capture the full range of variation as compared to its nonstationary counterpart.