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Piecewise polynomial chaos expansion with an application to brake squeal of a linear brake system
Abstract : This paper proposes numerical developments based on polynomial chaos (PC) expansions to process stochastic eigenvalue problems efficiently. These developments are applied to the problem of linear stability calculations for a simplified brake system: the stability of a finite element model of a brake is investigated when its friction coefficient or the contact stiffness are modeled as random parameters. Getting rid of the statistical point of view of the PC method but keeping the principle of a polynomial decomposition of eigenvalues and eigenvectors, the stochastic space is decomposed into several elements to realize a low degree piecewise polynomial approximation of these quantities. An approach relying on continuation principles is compared to the classical dichotomy method to build the partition. Moreover, a criterion for testing accuracy of the decomposition over each cell of the partition without requiring evaluation of exact eigenmodes is proposed and implemented. Several random distributions are tested, including a uniform-like law for description of friction coefficient variation. Results are compared to Monte Carlo simulations so as to determine the method accuracy and efficiency. Some general rules relative to the influence of the friction coefficient or the contact stiffness are also inferred from these calculations.
Cited literature [44 references]
https://hal.archives-ouvertes.fr/hal-00744841
Contributor : Emmanuelle Sarrouy Connect in order to contact the contributor
Submitted on : Wednesday, October 24, 2012 - 9:41:33 AM
Last modification on : Monday, January 31, 2022 - 2:22:02 PM
Long-term archiving on: : Friday, January 25, 2013 - 3:42:00 AM
Contributor : Emmanuelle Sarrouy Connect in order to contact the contributor
Submitted on : Wednesday, October 24, 2012 - 9:41:33 AM
Last modification on : Monday, January 31, 2022 - 2:22:02 PM
Long-term archiving on: : Friday, January 25, 2013 - 3:42:00 AM
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