NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Computational & Applied Mathematics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Computational & Applied Mathematics, 289, 2015, DOI: 10.1016/j.cam.2015.02.022
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[en] Stiction is a major failure in microelectromechanical system (MEMS) devices in which two contacting surfaces can remain stuck together because of the adhesive forces. Due to the difference between the surfaces roughness and the adhesive force range, the real contact areas are usually smaller than the apparent one, resulting in a scatter in the adhesive forces. Consequently, the stiction is an uncertain phenomenon. In this work, we develop a probabilistic model to predict the uncertainties of stiction due to the capillary forces acting on stiff materials. This model contains two levels: at the deterministic level, the model can predict the pull-out adhesive contact forces for a given surface topology; at the probabilistic level, the model generates independent identically distributed surfaces on which the deterministic solution can be applied to evaluate the uncertainties related to the stiction phenomenon.
The research has been funded by the Walloon Region under the agreement no 1117477 (CT-INT 2011- 11-14) in the context of the ERA-NET MNT framework and by the Romanian UEFISCDI Agency contract ERA-NET MNT no 7-063 (2012-2015).
Funders :
Service public de Wallonie : Direction générale opérationnelle de l'économie, de l'emploi et de la recherche - DG06 Romanian UEFISCDI Agency FRIA - Fonds pour la Formation à la Recherche dans l'Industrie et dans l'Agriculture
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