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International Journal for Multiscale Computational Engineering
Impact-faktor: 1.016 5-jähriger Impact-Faktor: 1.194 SJR: 0.554 SNIP: 0.68 CiteScore™: 1.18

ISSN Druckformat: 1543-1649
ISSN Online: 1940-4352

International Journal for Multiscale Computational Engineering

DOI: 10.1615/IntJMultCompEng.v4.i1.110
pages 169-182

Trans-scale Coupling in Multiscale Simulations

Feng Rong
LNM, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100080, P. R. China
Haiying Wang
LNM, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100080, P. R. China
Mengfen Xia
LNM, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100080, P. R. China
Fujiu Ke
LNM, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100080, P. R. China
Yilong Bai
LNM, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100080, P. R. China

ABSTRAKT

Trans-scale coupling plays a significant role in multiscale problems. Since the mechanisms governing the trans-scale coupling vary from case to case, to identify and characterize the governing mechanisms of trans-scale coupling are the most crucial points in multiscale simulations. The failure of solid media is a typical multiscale process. This paper chooses two model problems, i.e., damage localization in spallation of an Al alloy and the catastrophe transition in a rock under quasi-static loading, to illustrate the trans-scale coupling in different phases of material failure. In the spallation process the governing mechanism of trans-scale effects is the coupling and competition between dynamics at different levels, which can be effectively characterized by two imposed Deborah numbers. In the catastrophe failure of heterogeneous media the governing mechanism of trans-scale coupling is the strong and sensitive coupling between the nonlinear dynamics and the disordered heterogeneity. In addition, the inverse cascade of damage evolution magnifies the effects of microstructures on failure and induces trans-scale sensitivity. Although the concept of critical sensitivity seems to be promising in catastrophe prediction, novel concepts and numerical schemes are still badly needed.