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Publication Type : Conference Paper
Publisher : IOP
Source : Journal of Physics: Conference Series, 2021
Keywords : Mini slump, Random Forest, Decision Tree, Multiple Regression Algorithms
Campus : Coimbatore
School : School of Engineering
Department : Electronics and Communication
Year : 2021
Abstract : Workability is one of the key property of concrete which is governed by water cement ratio. In order to improve the workability of concrete without any variations in water cement ratio Superplasticizers(SPs) are added. Cement paste helps us to analyze the property of fresh concrete where the dispersion of cement particle is taken into account. SP’s Cement dispersive properties are governed by dosage and the family. Various dosages and families of SP are considered for estimating workability feature of cement paste which is picked for investigating on rheological properties through Mini slump spread diameter. The prime motive of this analysis includes measuring the workability of different superplasticizers by conducting a minislump test and hence modelling the flow rate of the superplasticized Portland Pozzolona Cement (PPC)paste using the application of random forest(RF),decision tree(DT) and multiple regression algorithms. Testing and training data for a model were 287 unique mixture compositions at a water by cement ratio was 0.37. This mixture was tested experimentally in a laboratory using four types of locally available PPC’s and of SP which can be broadly categorised in to four families. Amount of seven types of SP brands, water content, cement weight were the input parameters for the model and flow rate was the output parameter. The model’s predicted and experimentally measured values of flow speed were compared and the amount of deviation was recorded.
Cite this Research Publication : Sathyan, Dhanya & K B, Anand & Jose, Chinnu & Aravind, N. (2018). Modelling the minislump spread of superplasticized PPC paste using RLS with the application of Random Kitchen sink. IOP Conference Series: Materials Science and Engineering. 310. 012035. 10.1088/1757-899X/310/1/012035.