Use of fly ash by percent replacement of cement by weight is considered as one of the most economical and effective method for mitigating Alkali-silica reaction (ASR) related distress in the concrete. Fly ash reduces the pore solution alkalinity through increasing the alkali binding capacity of the cement hydrates and through pozzolanic reaction. However, Fly ash is proven to be somewhat variable in its effectiveness on inhibiting alkali-silica reactivity, principally because its composition depends on the coal properties from which it is derived. Typically Class C fly ashes are not as efficient as Class F ashes due to their higher calcium oxide content. Also, it is not established if the dosage of fly ash is more influential than type of fly ash and vice versa. Therefore, in the field, for a certain job mixture, the prediction of mitigation effect of a certain type and dosage of fly ash is difficult. This research aims to correctly predict the effectiveness of fly ash mitigation, to find out the most influential factor and interaction effects between factors. A statistical model, of two-level design with 3 factors, was developed based on three main factors: fly ash lime content, dosage and soak solution alkalinity. The statistical model was verified with additional experimental results with random fly ash-lime content and different dosages; which matched very well with the model predictions. Therefore, such model(s) could be applied in practice with the availability of larger database. Also, another finding of this research is that, the lime content of the fly ash is the most significant factor followed by the dosage level.
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