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

被引:24
|
作者
Mehrez, Loujaine [1 ]
Fish, Jacob [2 ]
Aitharaju, Venkat [3 ]
Rodgers, Will R. [3 ]
Ghanem, Roger [1 ]
机构
[1] Univ Southern Calif, Viterbi Sch Engn, Los Angeles, CA 90089 USA
[2] Altair Engn Inc, Troy, MI 48083 USA
[3] Gen Motors Co, GM R&D Tech Ctr, 30500 Mound Rd, Warren, MI 48092 USA
关键词
Multiscale polynomial chaos; Multiscale stochastic modeling and simulation; Cross-scale dependencies; Composite material systems; STOCHASTIC-ANALYSIS; MODEL-REDUCTION; HOMOGENIZATION; TENSOR; CHAOS;
D O I
10.1007/s00466-017-1502-4
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
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.
引用
收藏
页码:219 / 236
页数:18
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