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Nanosilica Particles in Concrete: Optimization for Compressive Strength, Permeability, and Cost-Benefit Relationship
In this study concrete mixtures with nanosilica particles (NS), silica fume (SF), and fly ash (FA) were tested for compressive strength, permeability via the rapid chloride ion permeability test (RCPT) and the costs were estimated for each mixture design. Model equations were generated from the empirical data and used to predict compressive strength and permeability for mixes containing NS, SF, and FA, with dosages within the tested range. After establishing the accuracy of the predictive model equations, three goals were established. The first objective was finding the optimal dosage of NS when it is the only admixture considered; the results indicate that the highest level tested of NS%=3 is the optimal dosage. The second objective was to find the maximum compressive strength and lowest permeability when all three admixtures are considered, for both tests, the best performing mixture contained NS%=3, SF%=20 and FA%=0. Finally, the predictive models were used simultaneously in order to find mixtures with the best cost. The predictive models found mixture designs that were able to improve performance, while simultaneously reducing costs when compared with the control mixture.
Nanosilica Particles in Concrete: Optimization for Compressive Strength, Permeability, and Cost-Benefit Relationship
In this study concrete mixtures with nanosilica particles (NS), silica fume (SF), and fly ash (FA) were tested for compressive strength, permeability via the rapid chloride ion permeability test (RCPT) and the costs were estimated for each mixture design. Model equations were generated from the empirical data and used to predict compressive strength and permeability for mixes containing NS, SF, and FA, with dosages within the tested range. After establishing the accuracy of the predictive model equations, three goals were established. The first objective was finding the optimal dosage of NS when it is the only admixture considered; the results indicate that the highest level tested of NS%=3 is the optimal dosage. The second objective was to find the maximum compressive strength and lowest permeability when all three admixtures are considered, for both tests, the best performing mixture contained NS%=3, SF%=20 and FA%=0. Finally, the predictive models were used simultaneously in order to find mixtures with the best cost. The predictive models found mixture designs that were able to improve performance, while simultaneously reducing costs when compared with the control mixture.
Nanosilica Particles in Concrete: Optimization for Compressive Strength, Permeability, and Cost-Benefit Relationship
González-Solá, Luis (author) / Molina-Bas, Omar I. (author) / Portela-Gauthier, Genock (author)
Construction Research Congress 2016 ; 2016 ; San Juan, Puerto Rico
Construction Research Congress 2016 ; 290-299
2016-05-24
Conference paper
Electronic Resource
English
The Use of Nanosilica for Improving of Concrete Compressive Strength and Durability
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