Contact of Rough Surfaces With Asymmetric Distribution of Asperity Heights

Yu, Ning; Polycarpou, Andreas A.

doi:10.1115/1.1403458

Cited by 126 publications

(74 citation statements)

References 16 publications

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“…To model the asperity distributions with different skewness and kurtosis values, the Pearson system of frequency curves is adopted (Kotwal and Bhushan 1996). The advantage of using the Pearson method over other methods (Yu and Polycarpou 2002;Chilamakuri and Bhushan 1998) to generate distributions that take into account the effect of skewness and kurtosis, is that it uses the moments of the density distribution to determine the distribution parameters. Since the skewness and kurtosis correspond to the third and fourth moments of the probability function, the distribution parameters can be determined as function of the skewness and kurtosis.…”

Section: Contact Asperity Modelmentioning

confidence: 99%

Adhesion and contact modeling and experiments in microelectromechanical systems including roughness effects

Tayebi

Polycarpou

2006

Microsyst Technol

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The intermolecular adhesive forces in microelectromechanical systems (MEMS) applications are very significant and can hinder normal operation of sensors and actuators as well as micro-engines where catastrophic adhesion and high friction could be promoted. It has been experimentally shown that surface texturing (roughening) decreases the effect of these forces. In this paper, a model that predicts the effects of roughness, on the adhesion and contact forces in MEMS interfaces is presented. The three key parameters used to characterize the roughness, the asymmetry and the flatness of a surface topography are the root-mean-square roughness (RMS), skewness and kurtosis, respectively. It is predicted that surfaces with high RMS, high kurtosis and positive skewness exhibit lower adhesion and are thus less prone to collapsing when they come into contact or near contact. Moreover, polysilicon films with different levels of roughness, asymmetry and peakiness (sharpness) were fabricated. Experiments were conducted to evaluate the adhesive pull-off forces associated with these films. The roughness characteristics of these films were also used in the model to predict the adhesive pull-off forces. Good agreement was obtained between the theoretical and experimental results. Such a model could be used to determine the critical characteristics of a microstructure prior to fabrication to prevent adhesion and lower friction in terms of surface roughness, mechanical properties and environment.

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Section: Contact Asperity Modelmentioning

confidence: 99%

Adhesion and contact modeling and experiments in microelectromechanical systems including roughness effects

Tayebi

Polycarpou

2006

Microsyst Technol

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“…However it is not possible to change the skew without also changing the kurtosis as indicated by Eqn. (19).…”

Section: Weibull Distributionmentioning

confidence: 99%

“…The skew, standard deviation, and kurtosis are given by (19) respectively. It follows that these non-dimensional quantities also depend only on the parameter ω.…”

Section: Weibull Distributionmentioning

confidence: 99%

“…McCool [18] extended the GW model by using a Weibull distribution of asperity heights and by including the effect of a surface coating. The multiasperity elastic-plastic CEB contact mo del was generalized to include a Weibull distribution by Yu and Polycarpou [19]. Skew was found to greatly affect the relation between the force, contact area, and the number of contacting asperities…”

Section: Introductionmentioning

confidence: 99%

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Asymmetric Asperity Height Distributions in a Scale-Dependent Model for Contact and Friction

Adams

2003

Contact Mechanics

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The effect of an asymmetric distribution of asperity heights is accounted for in a recently developed scale-dependent multiasperity model of contact and friction. A Weibull distribution of asperity heights is used which allows the skew and kurtosis to be varied, but not independently of each other. The contact and friction model used includes the effects of adhesion and of scale-dependent friction. The results obtained demonstrate that positive/negative skew decreases/increases both the friction coefficient and its dependence on the magnitude of the normal load.

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“…Although the uncertainty characteristics [30], [31], [27], [26] and the non-Gaussianity of the surface height distribution [5], [32], [33] play important roles in the stiction phenomenon, they were either both neglected or accounted for but individually. On the one hand, in [5], the importance of non-Gaussian properties including the skewness and the kurtosis of the contacting surface heights was illustrated by a comparison between numerical predictions and experimental results; however, only deterministic predictions were given.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Multiscale Model of MEMS Stiction Accounting for High-Order Statistical Moments of Non-Gaussian Contacting Surfaces

Hoang

Golinval

et al. 2018

J. Microelectromech. Syst.

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Abstract-Stiction is a failure mode of microelectromechanical systems (MEMS) involving permanent adhesion of moving surfaces. Models of stiction typically describe the adhesion as a multiple asperity adhesive contact between random rough surfaces, and they thus require a sufficiently accurate statistical representation of the surface, which may be non-Gaussian. If the stiction is caused primarily by multiple asperity adhesive contact in only a small portion of the apparent area of the contacting surfaces, the number of adhesive contacts between asperities may not be sufficiently statistically significant for a homogenized model to be representative. In [Hoang et al., A computational stochastic multiscale methodology for MEMS structures involving adhesive contact, Tribology International, 110:401-425, 2017], the authors have proposed a probabilistic multiscale model of multiple asperity adhesive contact that can capture the uncertainty in stiction behavior. Whereas the previous paper considered Gaussian random rough surfaces, the aim of the present paper is to extend this probabilistic multiscale model to non-Gaussian random rough surfaces whose probabilistic representation accounts for the high order statistical moments of the surface height. The probabilistic multiscale model thus obtained is validated by means of a comparison with experimental data of stiction tests of cantilever beams reported in the literature.

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Contact of Rough Surfaces With Asymmetric Distribution of Asperity Heights

Cited by 126 publications

References 16 publications

Adhesion and contact modeling and experiments in microelectromechanical systems including roughness effects

Adhesion and contact modeling and experiments in microelectromechanical systems including roughness effects

Asymmetric Asperity Height Distributions in a Scale-Dependent Model for Contact and Friction

Stochastic Multiscale Model of MEMS Stiction Accounting for High-Order Statistical Moments of Non-Gaussian Contacting Surfaces

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