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Regularization of first order computational homogenization for multiscale analysis of masonry structures

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Abstract

This paper investigates the possibility of using classical first order computational homogenization together with a simple regularization procedure based on the fracture energy of the micro-scale-constituents. A generalized geometrical characteristic length takes into account the size of the macro-scale element as well as the size of the RVE (and its constituents). The proposed regularization ensures objectivity of the dissipated energy at the macro-scale, with respect to the size of the FE in both scales and with respect to the size of the RVE. The proposed method is first validated against benchmark examples, and finally applied to the numerical simulation of experimental tests on in-plane loaded shear walls made of periodic masonry.

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Acknowledgments

This research has received the financial support from the Graduate School of the University “G. D’ Annunzio” of Chieti-Pescara, from the Italian Department of Civil Protection through the Reluis Project, from the MINECO (Ministerio de Economia y Competitividad of the Spanish Government) and the ERDF (European Regional Development Fund) through the MICROPAR project (Identification of mechanical and strength parameters of structural masonry by experimental methods and numerical micro-modelling, ref num. BIA2012-32234) and from the Excellence Programme for Knowledge Generation by MINECO, through the EACY project (Enhanced accuracy computational and experimental framework for strain localization and failure mechanisms, ref. MAT2013-48624-C2-1-P).

S. Oller acknowledges the support of the European Research Council under the Advanced Grant: ERC-2012-AdG 320815 COMP-DES-MAT “Advanced tools for computational design of engineering materials”.

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Petracca, M., Pelà, L., Rossi, R. et al. Regularization of first order computational homogenization for multiscale analysis of masonry structures. Comput Mech 57, 257–276 (2016). https://doi.org/10.1007/s00466-015-1230-6

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