Research Article
Uncertainty quantification models for micro-scale squeeze-film damping
Article first published online: 11 NOV 2010
DOI: 10.1002/nme.2952
Copyright © 2010 John Wiley & Sons, Ltd.
Issue

International Journal for Numerical Methods in Engineering
Volume 84, Issue 10, pages 1257–1272, 3 December 2010
Additional Information
How to Cite
Guo, X., Li, J., Xiu, D. and Alexeenko, A. (2010), Uncertainty quantification models for micro-scale squeeze-film damping. Int. J. Numer. Meth. Engng., 84: 1257–1272. doi: 10.1002/nme.2952
Publication History
- Issue published online: 11 NOV 2010
- Article first published online: 11 NOV 2010
- Manuscript Accepted: 21 APR 2010
- Manuscript Revised: 17 APR 2010
- Manuscript Received: 17 MAR 2009
Funded by
- NNSA Center for Prediction of Reliability, Integrity and Survivability of Microsystems (PRISM) at Purdue University. Grant Number: DE-FC52-08NA28617
- Abstract
- Article
- References
- Cited By
Keywords:
- uncertainty quantification;
- squeeze-film damping;
- gPC expansion;
- rarefied flow
Abstract
Two 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. Copyright © 2010 John Wiley & Sons, Ltd.

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