2014
DOI: 10.1016/j.acme.2013.08.004
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Adaptive multiscale analyses on structural failure considering localized damage evolution on vulnerable joints

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Cited by 9 publications
(4 citation statements)
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“…The total time consumed in the MTB multiscale computation is 71.3 per cent less than a single fine-scale computation. Compared to the previous structural multiscale method (Li et al, 2012;Zheng et al, 2014), the MTB simulation can improve the computation efficiency significantly. In this case, the computation error is kept within tolerable range.…”
Section: Numerical Examplesmentioning
confidence: 99%
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“…The total time consumed in the MTB multiscale computation is 71.3 per cent less than a single fine-scale computation. Compared to the previous structural multiscale method (Li et al, 2012;Zheng et al, 2014), the MTB simulation can improve the computation efficiency significantly. In this case, the computation error is kept within tolerable range.…”
Section: Numerical Examplesmentioning
confidence: 99%
“…Because material nonlinear deformation is incompatible with scale bridging at trans-scale boundary, when material inelastic responses evolve and approach the macro-scale domain (Zheng et al, 2014), the trans-scale boundary would be moved toward macro-scale domain to ensure computation accuracy, which is critical in the MTB mechanism. The FE equation would be transformed and modified accordingly.…”
Section: Trans-scale Boundary Movementmentioning
confidence: 99%
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“…The two-scale model composed of beam elements and solid elements or shell elements has been proposed and extensively employed in FEM analysis on RC structures owing to its high computational efficiency [16]. Meanwhile, various kinds of two-scale modeling methods have been successfully applied in the damage and failure analysis of civil structures under earthquakes [16][17][18][19][20]. Moreover, the mesoscale modeling approach has been successfully applied in the numerical simulation of concrete structures subjected to various loading cases [21][22][23].…”
Section: Introductionmentioning
confidence: 99%