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Reduced order voxel‐based model for computational modelling of highly compressible composite materials
Author(s) -
Iskhakov Tagir,
Timothy Jithender J.,
Bessa Miguel,
Meschke Günther
Publication year - 2021
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.202000056
Subject(s) - compaction , cementitious , compressibility , voxel , materials science , composite number , granular material , porous medium , porosity , geotechnical engineering , composite material , cement , mechanics , computer science , geology , physics , artificial intelligence
Compressible cementitious materials are used in tunnel lining systems deployed in ground conditions characterised by expansive soils. The deformation capacity of a cementitious material can be enhanced by the introduction of weak inclusions (EPS) and/or pores. The overall behaviour of such porous cementitious composite materials is strongly influenced by the material properties of the individual components (EPS, pores, sand particles, aggregates), the geometry of the constituents, their spatial distribution and volume. The compaction behaviour of such composites can be described by a voxel model with a discrete distribution of material properties, where the voxels are compacted by applying an eigenforce. The proposed model is integrated into the framework of the reduced order self‐consistent clustering strategy at the scale of a Representative Elementary Volume [1]. The accuracy of the reduced order strategy combined with the voxel model is analysed by comparing it to the full voxel compaction model