Prediction of mechanical properties of concrete blended with marble stone powder by artificial neural network

¹ Department of Civil Engineering, K. G. Reddy College of Engineering and Technology, Moinabad, Hyderabad, T.S. 501504.
² Department of Civil Engineering, Kallam Haranadha Reddy Institute of Technology, Guntur, A.P – 522006.
³ Department of Civil Engineering, Annamacharya Institute of Technology and Sciences, Tirupati, A.P
⁴ Department of Civil Engineering, Jawahar Lal Nehru Technological University College of Engineering Anantapur, Anantapur, A.P.
⁵ Department of CSE, GRIET, Hyderabad, Telangana, India
⁶ Lovely Professional University, Phagwara, Punjab, India.

^* Corresponding author: drtsrameshbabu@gmail.com

Abstract

The current research work is mainly concentrated on the mechanical properties concrete blended with marble stone power resulted from waste sludge marble processing it has a high specific area. M25 grade concrete mix design was considered for this research work. The mechanical properties of concrete i.e. compressive strength, unit weight, splitting tensile strength, modulus of elasticity and flexural strength were considered for the study. The compressive strength of these mixes was measured on 150mm ×150mm × 150mm cubes and tension test split tensile test 150 mm dia × 300 mm height cylinders. The concrete unit weight was considered for calculating the elastic modulus of concrete. The investigational values were matched with ACI, CEB-FIP, BIS and AASHTO LRFD empirical equation and regression analysis was done. The empirical equation result was compared with regression analysis of Artificial Neural Network, and conclusion was brough down that regression analysis of artificial neural network had better prediction than that of above-mentioned empirical equations. The study concluded that 15% replacement of marble power attained highest strength and optimum replacement, 25% replacement was concluded as economical replacement to attain designed strength.