Stochastic modeling of uncertain mass characteristics in rigid body dynamics

Richter, Lanae A.; Mignolet, Marc P.

doi:10.1016/j.ymssp.2016.09.017

Cited by 6 publications

(1 citation statement)

References 9 publications

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“…Since its initial formulation in [1], the maximum entropy-based nonparametric approach has been extended multiple times to cover new classes of problems, e.g., vibro-acoustics [3,4], rotordynamics [5][6][7], nonlinear structural dynamics [8,9], nonlinear thermoelastic problems [10], linear viscoelastic structures [11], etc., but also in rigid body dynamics [12,13] and micromechanics and multiscale modeling, see [2]. The focus of the present effort is on yet another extension of this approach, more specifically to problems in which (i) the response of the mean model (i.e., the one without uncertainty) is localized to one part of the spatial domain and (ii) the uncertainty to be modeled does not alter this localization.…”

Section: Introductionmentioning

confidence: 99%

Reduced Order Model-Based Uncertainty Modeling of Structures With Localized Response

Song

Mignolet

2017

Proceedings of the 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECO

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This paper focuses on the introduction of uncertainty in reduced order models of structures exhibiting a localized static response in the neighborhood of the excitation. A straightforward application of the maximum entropy framework is first considered to carry out the stochastic modeling of the uncertainty. Quite consistently with the maximization of the entropy, it is found that this modeling may lead to a "globalization" of the response and thus an extension of the nonparametric stochastic modeling approach is sought. To this end, the eigenvalues and eigenvectors of the stiffness matrix of structures exhibiting this localization property are first studied. It is found that their lowest eigenvalues are closely spaced when the corresponding eigenvectors are extended to the entire structure. On this basis, a novel version of the nonparametric stochastic modeling approach is introduced to randomize the entire stiffness matrix while distorting only slightly the closely spaced eigenvalue structure. The above concepts are demonstrated on a thin annulus clamped at its inner radius and a localization of the uncertain response is indeed observed using the proposed approach.

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