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Effect of Foundry Sand and Glass Fibres in Concrete using Artificial Neural Network

Chethan C. S.*, B. C. Udaya Shankar**

* Department of Structural Engineering, R. V. College of Engineering, Bangalore, Karnataka, India.

** Department of Civil Engineering, R. V. College of Engineering, Bangalore, Karnataka, India.

Periodicity:December - February'2021
DOI : https://doi.org/10.26634/jce.11.1.17508

Abstract

Alternate material substitution in concrete has been deemed to refine both mechanical and durability properties, and this tradition may contribute to imperishable concrete growth. It has therefore become crucial to look for an auxiliary to the usual river sand. Waste foundry sand (WFS) is one such reassuring material that demands to be extensively appraised as a substitute for fine aggregates to be used in concrete. The incorporation of tiny, closely situated and consistently scattered fibres to concrete would uphold as a crack arrestor and would consequentially enhance its static and dynamic properties. This project aims at examining the effect of foundry sand and glass fibres in concrete. The physical properties of the constituents were tested. Compressive, tensile and flexural strength were evaluated for the concrete manufactured using foundry sand and glass fibres using analytical approach. MLRA and ANN techniques were used to develop mathematical models and prediction values respectively. Further these results were validated with the results available from literature survey. With the introduction of foundry sand as partial replacement to fine aggregate and addition of glass fibres in varying proportions, strength properties were evaluated. Compressive strength increased with gradual increase in foundry sand percentage. Tensile and flexural strength were enhanced with the inclusion of glass fibres.

Keywords

Concrete, Foundry Sand (UFS, WFS, SFS), Glass Fibres, MLRA, ANN

How to Cite this Article?

Chethan, C. S., and Shankar, B. C. U. (2021). Effect of Foundry Sand and Glass Fibres in Concrete using Artificial Neural Network. i-manager's Journal on Civil Engineering, 11(1), 21-32. https://doi.org/10.26634/jce.11.1.17508

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Effect of Foundry Sand and Glass Fibres in Concrete using Artificial Neural Network

Abstract

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