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Computational Mechanics
Erschienen in: Computational Mechanics 1-2/2018

10.11.2017 | Original Paper

A PCE-based multiscale framework for the characterization of uncertainties in complex systems

verfasst von: Loujaine Mehrez, Jacob Fish, Venkat Aitharaju, Will R. Rodgers, Roger Ghanem

Erschienen in: Computational Mechanics | Ausgabe 1-2/2018

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Abstract

This paper presents a framework for the modeling and analysis of material systems that exhibit uncertainties in their constituents at all scales. The framework integrates multiscale formalism with a polynomial chaos construction enabling an explicit representation of quantities of interests, at any scale, in terms of any form of underlying uncertain parameters, a key feature to model multiscale dependencies. It is demonstrated how the framework can successfully tackle settings where a hierarchy of scales must be explicitly modeled. The application of this framework is illustrated in the construction of stochastic models of mesoscale and macroscale properties of non-crimp fabric composites. Joint statistical properties of upscaled components of the composite, including properties of tow, laminae and laminate, are computed.
Vorheriger Artikel Concurrent multiscale modeling of microstructural effects on localization behavior in finite deformation solid mechanics
Nächster Artikel Uncertainty aggregation and reduction in structure–material performance prediction

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Metadaten
Titel
A PCE-based multiscale framework for the characterization of uncertainties in complex systems
verfasst von
Loujaine Mehrez
Jacob Fish
Venkat Aitharaju
Will R. Rodgers
Roger Ghanem
Publikationsdatum
10.11.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Computational Mechanics / Ausgabe 1-2/2018
Print ISSN: 0178-7675
Elektronische ISSN: 1432-0924
DOI
https://doi.org/10.1007/s00466-017-1502-4

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