We propose an adaptive curved virtual element method (ACVEM) which is able to combine an exact representation of the involved computational geometry and a dynamic tuning of the optimal mesh resolution through a robust and efficient residual-based a-posteriori error estimator. A theoretical analysis on the reliability of the estimator and a gallery of numerical tests supports the efficacy of the proposed approach. The ACVEM is combined with Monte Carlo simulations, and a methodology is developed to determine homogenized material moduli and representative unit cell size of random long-fibre reinforced composites in the framework of antiplane shear deformation. Accuracy and computational efficiency of the proposed homogenization procedure is confirmed by numerical examples.
Artioli, E., Beirao da Veiga, L., Verani, M. (2020). An adaptive curved virtual element method for the statistical homogenization of random fibre-reinforced composites. FINITE ELEMENTS IN ANALYSIS AND DESIGN, 177 [10.1016/j.finel.2020.103418].
An adaptive curved virtual element method for the statistical homogenization of random fibre-reinforced composites
Artioli E.;
2020-01-01
Abstract
We propose an adaptive curved virtual element method (ACVEM) which is able to combine an exact representation of the involved computational geometry and a dynamic tuning of the optimal mesh resolution through a robust and efficient residual-based a-posteriori error estimator. A theoretical analysis on the reliability of the estimator and a gallery of numerical tests supports the efficacy of the proposed approach. The ACVEM is combined with Monte Carlo simulations, and a methodology is developed to determine homogenized material moduli and representative unit cell size of random long-fibre reinforced composites in the framework of antiplane shear deformation. Accuracy and computational efficiency of the proposed homogenization procedure is confirmed by numerical examples.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.