Compact model of squeeze-film damping based on rarefied flow simulations

Guo, Xiaohui; Alexeenko, Alina

doi:10.1088/0960-1317/19/4/045026

Cited by 54 publications

(61 citation statements)

References 20 publications

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“…Using an expression of the form similar to that of Equation (14), a compact model based on 50 rarefied flow solutions of Equation (3)- (5) has been obtained [20] as,…”

Section: Compact Gas Damping Modelmentioning

confidence: 99%

“…The gas damping, which is obtained by subtracting the structural damping from the total measurements, agrees well with model predictions. Details about this compact damping model can be found in Reference [20].…”

Section: Compact Gas Damping Modelmentioning

confidence: 99%

“…Numerical tests indicated that the set is sufficient for the least-square estimation of the model parameters in the compact model (15) [20].…”

Section: Model Verification and Validationmentioning

confidence: 99%

“…The compact model has been examined in Reference [20] for a good accuracy. Since the numerical simulation is computationally expensive to obtain, we construct the gPC expansion as shown in Equation (12) by using the estimates of compact model.…”

Section: Convergence Study In Gpc Modelmentioning

confidence: 99%

“…Better understanding of gas damping effects on micro-structure dynamics gPC can be highly accurate and efficient. On the other hand, the compact model from [20] is developed specifically for this particular SFD problem. It is a simple closed-form model consisting of a few physical parameters that are fitted based on simulations for varying Knudsen numbers and geometries.…”

Section: Introductionmentioning

confidence: 99%

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Uncertainty quantification models for micro‐scale squeeze‐film damping

Guo

Xiu

et al. 2010

Numerical Meth Engineering

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SUMMARYTwo squeeze-film gas damping models are proposed to quantify uncertainties associated with the gap size and the ambient pressure. Modeling of gas damping has become a subject of increased interest in recent years due to its importance in micro-electro-mechanical systems (MEMS). In addition to the need for gas damping models for design of MEMS with movable micro-structures, knowledge of parameter dependence in gas damping contributes to the understanding of device-level reliability. In this work, two damping models quantifying the uncertainty in parameters are generated based on rarefied flow simulations. One is a generalized polynomial chaos (gPC) model, which is a general strategy for uncertainty quantification, and the other is a compact model developed specifically for this problem in an early work. Convergence and statistical analysis have been conducted to verify both models. By taking the gap size and ambient pressure as random fields with known probability distribution functions (PDF), the output PDF for the damping coefficient can be obtained. The first four central moments are used in comparisons of the resulting non-parametric distributions. A good agreement has been found, within 1%, for the relative difference for damping coefficient mean values. In study of geometric uncertainty, it is found that the average damping coefficient can deviate up to 13% from the damping coefficient corresponding to the average gap size. The difference is significant at the nonlinear region where the flow is in slip or transitional rarefied regimes.

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“…Using an expression of the form similar to that of Equation (14), a compact model based on 50 rarefied flow solutions of Equation (3)- (5) has been obtained [20] as,…”

Section: Compact Gas Damping Modelmentioning

confidence: 99%

Section: Compact Gas Damping Modelmentioning

confidence: 99%

“…Numerical tests indicated that the set is sufficient for the least-square estimation of the model parameters in the compact model (15) [20].…”

Section: Model Verification and Validationmentioning

confidence: 99%

Section: Convergence Study In Gpc Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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