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Showing 2 results for Mahinroosta

A. Allahverdi, M. Mahinroosta,
Volume 12, Issue 4 (Transaction A: Civil Engineering December 2014)
Abstract

It was found out that the logarithmic models fit the cement–slag blend systems well. In the present study, based on the experimental results, a logarithmic model has been developed to predict the compressive strength of chemically activated high phosphorous slag content cement. Mixes of phosphorous slag (80 wt.%), Portland cement (14 wt.%) and compound chemical activator (6 wt.%) were prepared at different Blaine finenesses using a laboratory ball mill. Compressive strengths of mortar specimens cured in lime-saturated water were measured at different curing times. Mathematical model was prepared in terms of curing time and water-to-cement ratio as independent variables and compressive strength as dependent variable. The comparisons between the model reproductions and the experimentally obtained results confirm the applicability of the presented model.
Ali Allahverdi, Mostafa Mahinroosta, Shima Pilehvar,
Volume 15, Issue 5 (Transaction A: Civil Engineering 2017)
Abstract

Compressive strength is as one of the most important properties of concrete and mortar that its measurement may be necessary at both early and later ages. Prediction of compressive strength by a proper model is a fast and cost-effective way for evaluating cement quality under various curing conditions. In this paper, a logarithmic model based on the results of an experimental work conducted to investigate the effects of curing time and temperature on the compressive strength development of chemically activated high phosphorous slag content cement has been presented. This model is in terms of curing time and temperature as independent variables and compressive strength as dependent variable. For this purpose, mortar specimens were prepared from 80 wt.% phosphorous slag, 14 wt.% Portland cement, and 6 wt.% compound chemical activator at Blaine fineness of 303 m2/kg. The specimens were cured in lime-saturated water under temperatures of 25, 45, 65, 85 and 100 ºC in oven. The model has two adjustable parameters for various curing times and temperatures. Modeling has been done by applying dimensionless insight. The proposed model can efficiently predict the compressive strength of this type of high phosphorous slag cement with an average relative error of less than 4%.



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