Abstract

Properties of a random porous material such as pervious concrete are strongly dependent on its pore structure features. This study describes the development of different models to understand the material structure - property relationships in pervious concretes. Several pervious concrete mixtures with different pore structure features are proportioned. The pore structure features such as pore area fractions, pore sizes, mean free spacing of the pores, specific surface area, and the three-dimensional pore distribution density are extracted using image analysis methods. The performance features modeled as a function of the pore structure features are: (1) the unconfined compressive strength, (2) permeability, and (3) permeability reduction due to particle trapping in the pores (clogging). A statistical model is used to relate the compressive strength to the relevant pore structure features, which is then used as a base model in a Monte-Carlo simulation for feature sensitivity evaluation. Permeability prediction is accomplished using the well-known Katz-Thompson equation that employs the pore structure features. An idealized 3-D geometry obtained from 2-D planar images of pervious concrete sections is used along with a probablistic particle capture model to predict the particle retention associated with clogging material addition and simulated runoff. These models are anticipated to be useful in designing pervious concrete systems of desired pore structure for requisite performance.

Original languageEnglish (US)
Title of host publicationAmerican Concrete Institute, ACI Special Publication
Pages55-73
Number of pages19
Edition282 SP
StatePublished - 2009
EventThe Leading Edge of Pervious Concrete 2009 at the ACI Fall 2009 Convention - New Orleans, LA, United States
Duration: Nov 8 2009Nov 12 2009

Other

OtherThe Leading Edge of Pervious Concrete 2009 at the ACI Fall 2009 Convention
CountryUnited States
CityNew Orleans, LA
Period11/8/0911/12/09

Fingerprint

Pore structure
Concretes
Compressive strength
Concrete mixtures
Runoff
Specific surface area
Image analysis
Pore size
Porous materials
Geometry

Keywords

  • Clogging
  • Compressive strength
  • Particle capture model
  • Permeability
  • Pervious concrete
  • Pore structure
  • Porosity
  • Statistical analysis

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Materials Science(all)

Cite this

Deo, O., Sumanasooriya, M. S., & Neithalath, N. (2009). Models for property prediction of pervious concretes. In American Concrete Institute, ACI Special Publication (282 SP ed., pp. 55-73)

Models for property prediction of pervious concretes. / Deo, Omkar; Sumanasooriya, Milani S.; Neithalath, Narayanan.

American Concrete Institute, ACI Special Publication. 282 SP. ed. 2009. p. 55-73.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Deo, O, Sumanasooriya, MS & Neithalath, N 2009, Models for property prediction of pervious concretes. in American Concrete Institute, ACI Special Publication. 282 SP edn, pp. 55-73, The Leading Edge of Pervious Concrete 2009 at the ACI Fall 2009 Convention, New Orleans, LA, United States, 11/8/09.
Deo O, Sumanasooriya MS, Neithalath N. Models for property prediction of pervious concretes. In American Concrete Institute, ACI Special Publication. 282 SP ed. 2009. p. 55-73
Deo, Omkar ; Sumanasooriya, Milani S. ; Neithalath, Narayanan. / Models for property prediction of pervious concretes. American Concrete Institute, ACI Special Publication. 282 SP. ed. 2009. pp. 55-73
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