A review of materials science-based models for mixture design and permeability prediction of pervious concretes

Milani S. Sumanasooriya, Omkar Deo, Benjamin Rehder, Narayanan Neithalath

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Pervious concrete is one of the relatively recent additions to the class of sustainable multifunctional cement-based materials. The material design of pervious concretes relies on trial-and-error-based approaches since the larger porosity and pore size requirements make a minimal porosity-based approach adopted for conventional concretes non-viable. This paper reviews a particle packing-based methodology for pervious concrete material design using a compaction index from compressible packing model of granular particles as the defining parameter. The pore structure features of the thus designed pervious concretes are characterised using well-accepted stereological and morphological methods. A three-dimensional reconstruction procedure, from two-dimensional starting images, used to develop material structures in which performance (permeability) prediction algorithms can be implemented is also reviewed. Permeability of these model structures have been predicted using a Stokes' solver and a Lattice Boltzmann scheme, and compared to the experimentally determined permeability. A stochastic Monte-Carlo simulation is used to quantify the influence of pore structure features on the permeability of pervious concretes.

Original languageEnglish (US)
Pages (from-to)108-130
Number of pages23
JournalInternational Journal of Materials and Structural Integrity
Volume9
Issue number1-3
DOIs
StatePublished - Jan 1 2015

Keywords

  • Computational models
  • Material design
  • Permeability
  • Pervious concrete
  • Pore structure

ASJC Scopus subject areas

  • Mechanical Engineering
  • Mechanics of Materials
  • Materials Science(all)

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