Extracting the performance predictors of Enhanced Porosity Concretes from electrical conductivity spectra

Research output: Contribution to journalArticle

33 Scopus citations

Abstract

This paper discusses the application of an analytical model of the dielectric spectrum of Enhanced Porosity Concretes (EPC, or pervious concretes) to predict its porosity and effective conductivity. While porosity is the dominant material parameter that dictates the performance characteristics (acoustic absorption and hydraulic conductivity) of EPC, effective conductivity has been shown to be an important parameter in the non-destructive estimation of performance. The porosities of the EPC specimens were measured using a volumetric method and an image analysis method. The effective conductivities were calculated from the bulk resistances of the samples obtained from Nyquist plots. The fits of the model to the conductivity spectra were used to extract the values of porosity and effective conductivity. The measured and predicted values of porosities and effective conductivities show good correlation. The frequency dependence of the dielectric spectra as well as the advantages of using a conductivity spectrum as opposed to a dielectric constant spectrum is outlined. The need to use effective conductivity rather than conductivity at any frequency is also brought out. It is shown that a single electrical conductivity spectrum could be used to predict the parameters that best describe the performance characteristics of EPC.

Original languageEnglish (US)
Pages (from-to)796-804
Number of pages9
JournalCement and Concrete Research
Volume37
Issue number5
DOIs
StatePublished - May 1 2007
Externally publishedYes

Keywords

  • Acoustic absorption
  • Conductivity spectra
  • Electrical properties
  • Enhanced Porosity (pervious) Concrete
  • Permeability
  • Porosity

ASJC Scopus subject areas

  • Building and Construction
  • Materials Science(all)

Fingerprint Dive into the research topics of 'Extracting the performance predictors of Enhanced Porosity Concretes from electrical conductivity spectra'. Together they form a unique fingerprint.

  • Cite this