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Temperature influence on rheology of superplasticized pozzolana cement and modeling using RKS algorithm

Publication Type : Journal Article

Publisher : Journal of Materials in Civil Engineering

Source : Journal of Materials in Civil Engineering, American Society of Civil Engineers (ASCE), Volume 30, Number 9 (2018)

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Keywords : algorithm, cement (construction material), Cements, Curve fitting, Elasticity, flow modeling, least squares method, numerical model, Portland pozzolana cements, Random kitchen sinks, Regularized Least Squares, Rheological parameter, rheology, shear stress, Superplasticizers, temperature effect, Viscometers, Viscosity measurement

Campus : Coimbatore

School : School of Engineering

Department : Civil

Year : 2018

Abstract : Rheology deals with flow and deformation of matter under applied force. The study of rheological response of superplasticized portland pozzolana cement pastes subjected to a stepwise loading at three levels of temperature using Herschel-Bulkley and Bingham flow models is presented here. Rheological tests were done in a temperature-controlled coaxial cylinder viscometer (Brookfield DV-II). Cement pastes were prepared at a water-cement ratio of 0.37 using four types of portland pozzolana cement (PPC) and superplasticizers (SP) of four different families. Saturation dosages of the superplasticizers were obtained through Marsh cone and mini slump tests. Rheological tests were done on superplasticized cement paste mixes for three levels of dosages viz., lower than the saturation dosage, saturation dosage, and higher than the saturation dosage. Cement paste samples were subjected to shear rates ranging from 30 to 65 S-1 in the viscometer and the resultant shear stress was measured. Rheological parameters were obtained at three test temperatures (15, 27, and 35°C) by fitting the second cycle downward flow curves using Bingham model and Herschel-Bulkley model. These parameters were analyzed and used for modeling through random kitchen sink algorithm. The variation of predicted and measured values of the rheological parameters were compared and validated. It was observed that the model could effectively predict the rheological parameters within the experimental domain. © 2018 American Society of Civil Engineers.

Cite this Research Publication : Dhanya Sathyan, Dr. Anand K. B., and Sindu Menon M, “Temperature Influence on Rheology of Superplasticized Pozzolana Cement and Modeling using RKS Algorithm”, Journal of Materials in Civil Engineering, vol. 30, 2018.

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