Milani S. Sumanasooriya

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

In the structural and functional performance of enhanced porosity concrete (EPC) (or pervious concrete) and other macroporous materials, porosity, pore sizes and their distribution, connectivity, and specific surface area and other pore structure features play dominant roles. Analysis of such EPC features is dealt with in this paper using mathematical morphology and stereological techniques. Similar porosity values for the studied mixtures were provided by a morphological method based on two-point correlation and stereological methods based on area and line fractions. Lower porosity was shown by single-sized aggregate EPC mixtures than blended aggregate mixtures. Smaller pore sizes are found to result from higher proportions of smaller sized aggregates in the mixture. There is definition of an effective pore diameter based on a critical size based on opening granulometric density function, a two-point correlation based characteristic size, and pore size distribution of equivalent diameters. The pore sizes of the blended aggregate mixtures lie in between those of mixtures in which single-sized aggregates make up the blend. Good correspondence is seen between the inverse of the specific surface areas of pores and the effective pore diameter and correlation lengths, whereas there is linear relation of the mean free spacing between pores and these quantities. There is comparison of stereology-based three-dimensional pore distribution density indicating preconnectivity and a hydraulic connectivity factor for permeability, and the latter is shown to be a more sensitive parameter through which EPC specimens made with different size aggregates can be distinguished.

Planar Image-Based Reconstruction of Pervious Concrete Pore Structure and Permeability Prediction

The permeability of pervious concrete is discussed in this paper. Transport properties of porous materials such as pervious concretes are inherently dependent on a variety of pore structure features. Empirical equations are typically used to relate the pore structure of a porous material to its permeability. In this study, a computational procedure is employed to predict the permeability of 12 different pervious concrete mixtures from three-dimensional (3D) material structures reconstructed from starting planar images of the original material. Two-point correlation (TPC) functions of the two-dimensional (2D) images from real pervious concrete specimens are employed along with the measured volumetric porosities in the reconstruction process. The pore structure features of the parent material and the reconstructed images are found to be similar. The permeabilities predicted using Darcy’s law applied to the reconstructed structures and the experimentally measured permeabilities of pervious concretes are found to be in reasonably good agreement. The 3D reconstruction process provides a relatively inexpensive method (instead of methods such as X-ray tomography) to explore the nature of the pore space in pervious concretes and predict permeability, thus facilitating its use in understanding the changes in pore structure as a result of changes in mixture proportions.

Particle Packing-Based Material Design Methodology for Pervious Concretes

ACI Materials Journal, V. 109, No. 2, March-April 2012. MS No. M-2010-383.R2 received April 25, 2011, and reviewed under Institute publication policies. Copyright

Predicting the Elastic Moduli of Enhanced Porosity (Pervious) Concretes Using Reconstructed 3D Material Structures

Enhanced Porosity Concrete (EPC), also known as pervious concrete is a macroporous material that is finding applications in parking areas and low volume pavements because of its ability to transport a large amount of storm water through its porous material structure. Majority of the current research focuses on the functional performance of this material, with scant research on its mechanical behavior. In this study, a computational procedure is implemented on two-dimensional planar images of EPC to reconstruct three-dimensional material structures. The 3D reconstructed digital image data is used as an input to a finite element program to calculate the effective linear elastic properties of the material when subjected to applied macroscopic strains. EPC consists of three phases – the aggregates, the paste surrounding the aggregates, and the pores. In order to reduce the complications associated with assigning each of these phases different elastic moduli, each aggregate (assumed to be spherical in shape) surrounded by a paste shell, is mapped into an effective particle having a uniform elastic modulus, which is then input into the program to calculate the effective elastic modulus of the composite. The paste thicknesses for different EPC mixtures are obtained from an image analysis procedure. Ultrasonic pulse velocity method is used to experimentally determine the elastic modulus of several EPC mixtures proportioned using different aggregate sizes and blends. The results of the predictions using the computational method, and the experimental values are in good agreement.