Chemical approaches to prevent alkali-silica reaction in concrete – A review

Liu, Kaiwei; Mukhopadhyay, Anol; Hsu, Jia-Lin

doi:10.5267/j.esm.2018.6.003

Cited by 4 publications

(1 citation statement)

References 16 publications

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“…The screening tool uses WSA from both fly ashes in addition to soluble alkali from cement to determine the net PSA of concrete mixes for different fly ash replacement levels. The optimum fly ash dosage for ASR mitigation in concrete is estimated based on PSA and aggregate THA relationship (PSA should be ≤THA to mitigate ASR) ( 2 , 3 , 24 ). The following work items were undertaken to achieve the primary objective.…”

Section: Objectives and Research Significancementioning

confidence: 99%

Development of a Screening Tool for Rapid Fly Ash Evaluation for Mitigating Alkali Silica Reaction in Concrete

Saraswatula

Mukhopadhyay

Liu

2022

Transportation Research Record: Journal of the Transportation R

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Performance-based approaches to evaluate fly ash effectiveness in suppressing alkali silica reaction (ASR) require testing for a range of replacement levels to determine optimum fly ash dosage. Current approaches of ASR evaluation, that is, determining optimum fly ash dosage for ASR mitigation, are impractical as a mix design tool for new concrete construction. Therefore, in the present work a screening tool is developed to predict optimum fly ash dosage to suppress ASR in concrete mixes. The screening tool uses water-soluble (readily available) alkali from fly ash and cement to determine pore solution alkalinity (PSA) of concrete mixes for different fly ash replacement levels. The optimum fly ash dosage in concrete to mitigate ASR is estimated based on the PSA and aggregate threshold alkalinity (THA) relationship, that is, PSA should be ≤THA to make the mix ASR mitigated. Results from the screening tool demonstrate an 82% reliability in predicting fly ash dosage necessary to keep expansions below 0.04% based on AASHTO TP 142 tests for ASR expansion. In addition, a multiple non-linear regression model was developed to predict water-soluble alkali from fly ashes in place of testing using 50 experimental data points from laboratory measurements and literature studies. Overall, the screening tool presents a rapid and reliable approach to determine the optimum fly ash content required for ASR mitigation based on pore solution composition of mixes and aggregate reactivity.

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Section: Objectives and Research Significancementioning

confidence: 99%