Experimental investigation on bamboo fibre reinforced mortar using artificial neural network – a comparative study
Prem Kumar V, Vasugi V
School of Civil Engineering, Vellore Institute of Technology, Chennai Campus, Tamil Nadu, India
Bamboo Stem Ash;
Sustainable Building Material;
Taguchi’s Design of Experiment;
Artificial Neural Network
The increase in population promotes the construction industry to exploit the conventional building materials. This phenomenon leads to use of alternative building materials in the construction field. One of the effective natural materials is bamboo. In this paper, the Bamboo Fibre (BF) is used as an additive in the mortar at various percentages (1% to 4%) and Bamboo Stem Ash (BSA) is used as an alternative binder material to replace the cement at different proportions (2.5% to 10%). To increase the property of mortars, Styrene butadiene rubber (SBR) is used a super plasticizer from 0.5% to 2%. Due to high raising demand of river sand, Copper slag (CS) is used partially to replace the fine aggregate at constant percentage (50%) for all the mix proportion. W/B ratio is proportioned from 0.35 to 0.5 at different level. The design of experiment is conducted through Taguchi’s design and the experimental values are validated by Artificial Neural Network (ANN) tool for obtaining the predicted results with respect to dry density, water absorption, compressive strength and flexural strength. The experimental investigation proved that BF and BSA have a potential sign to be used as an alternative sustainable building material. From the comparative analysis of experimental results with ANN, it is revealed that the mortars show an acceptable prediction of physical and strength properties with a maximum error of 8.11%.
© 2022 MIM Research Group. All rights reserved.