Predicting fly ash dosages to prevent ASR by introducing the concrete prism test (CPT) chemical index model

Abstract

This study modifies the chemical index model (Malvar and Lenke in ACI Mater J 103(5):319–326, 2006) to predict the fly dosage needed to mitigate ASR (alkali-silica reaction) based on concrete prism test (CPT) expansion data. The utility of such a model (known as the CPT chemical index model) is that it reduces a two-year long test (CPT) to a calculation. Over eighty CPT data points of different aggregate, cement, and fly ash combinations from different literature sources were collated to create a model to predict the fly ash dosage (on a mass basis) necessary to prevent ASR. The CPT chemical index model developed from this study is slightly conservative for Class F fly ashes (0–10% greater replacement than actual) and conservative for Class C fly ashes (0–15% greater replacement than actual). The Standard Error of the Regression is 0.1614. Despite the presence of a relatively large Standard Error of the Regression, the conservative values of this model show promise for predicting ASR expansions with Class F fly ahes.