Modelling the Rheological Properties of Fly Ash Incorporated Superplasticized Cement Paste at Different Temperature Using Multilayer Perceptrons in Tensorflow

The rheology deals with flow of matter. It changes with respect to the material composition and test condition. This work investigate the influence of dosage and family of superplasticizer and dosage of mineral admixture and effect of temperature on the rheological properties of cement paste. For this purpose cement pastes were prepared at a water cement ratio of 0.37 using OPC cement, different percentage of fly ash(15, 25, 35) and different dosages of superplasticizer (one from each family). Rheological tests were carried out using co axial cylinder viscometer at three different temperature (15, 27, 35 °C). Rheological parameters like yield stress and plastic viscosities were calculated using Bingham and Herschel bulkley model. Rheological performance were modeled using Multilayer Perceptrons in Tensorflow. Out of 252 data generated, 204 data is used for training the model. The input parameters consists of variables like dosage of cement, fly ash, water, four families of super plasticizers and three different temperatures. The output consists of the measured value of yield stress and plastic viscosity of cement paste. Accuracy of the model is tested using 48 data set. From the predicted data it is clear that the python can be used effectively to predict the rheological properties (yield stress and plastic viscosity) of cement paste.