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Title: Stereology- and Morphology-Based Pore Structure Descriptors of Enhanced Porosity (Pervious) Concretes

Author(s): Milani S. Sumanasooriya and Narayanan Neithalath

Publication: Materials Journal

Volume: 106

Issue: 5

Appears on pages(s): 429-438

Keywords: mathematical morphology; pervious concrete; pore structure; porosity; stereology; two-point correlation.

DOI: 10.14359/51663143

Date: 9/1/2009

Abstract:
The pore structure features, such as the porosity, pore sizes and their distribution, connectivity, and specific surface area, play a dominant role in the structural and functional performance of macroporous materials like enhanced porosity concrete (EPC) (or pervious concrete). This paper deals with the analysis of such features for EPC using stereological techniques and mathematical morphology. Stereological methods based on area and line fractions and a morphological method based on two-point correlation provided similar porosity values for the mixtures studied. Single-sized aggregate EPC mixtures showed lower porosity than blended aggregate mixtures. Higher proportions of smaller sized aggregates in the mixture are found to result in smaller pore sizes. An effective pore diameter based on pore size distribution of equivalent diameters, a two-point correlation based characteristic size, and a critical size based on opening granulometric density function are defined. The blended aggregate mixtures have pore sizes that lie in between those of the mixtures made with single-sized aggregates that make up the blend. The inverse of the specific surface area of pores is seen to correspond well with the effective pore diameter and the correlation length, whereas the mean free spacing between pores is linearly related to these quantities. Stereology-based three-dimensional (3D) pore distribution density that indicates pore connectivity is compared to a hydraulic connectivity factor for permeability, and it is shown that the latter is a more sensitive parameter that can distinguish between EPC specimens made with aggregates of different sizes.