LAUSR

Abstract The electrical resistivity performance of fly ash in concrete is not easy to predict due to the diverse sources of fly ash and their varying reactivity. Electrical resistivity gives direct evidence of the rate of corrosion within the concrete and provides indirect clues into the fluid transport into the material. This paper aims to develop predictive models for the electrical resistivity of fly ash concrete by applying the Particle Model. The Particle Model rapidly examines individual fly ash particles without human intervention and is used to derive predictive models for 20% and 40% fly ash replacement levels in concrete at seven different periods of hydration. The R-squared values of predictive models in the Particle Model show significant improvement over using the classification method based on Class C and F for both fly ash replacement at all investigated time periods. The derived predictive models are able to accurately estimate the electrical resistivity within +/- 10% for 80% of all measurements at 20% fly ash replacement and within +/− 10% for 75% of all measurements at 40% fly ash replacement. These investigations provide important insights into how the Particle Model can help predict the electrical resistivity of fly ash concrete even at different mixtures and hydration times.