Modelling and analysis of strength and durability properties of internal curing concrete using PEG 400 and artificial neural network

Abstract

Abstract The traditional curing processes necessitate a large amount of water. This is especially difficult in locations where there is a lack of water and for construction of high-rise structures. In this research article, we provide a remedy by inventing concrete that will not require additional water for curing. In the present work, polyethylene glycol was utilized as an internal curing agent in varying percentages. The internally cured concrete with polyethylene glycol was cured at ambient conditions, whereas the conventional concrete without polyethylene glycol was kept in water for curing. Fresh and hardened characteristics of concrete with and without polyethylene glycol are compared. The results revealed that 1.5% polyethylene glycol is an optimum percentage where maximum strength and durable properties are achieved. The microstructure of internal curing concrete indicates that the pore sizes are small compared to conventional concrete. The crystallite size is smaller in internal curing compared to conventional concrete mixtures, resulting in an acceleration of the hydration process in concrete with smaller crystallites.Further experimental results are compared with ANN. Predicted results are very close to experimental values.

Keywords

• Internal curing
• Artificial neural network
• Polyethylene glycol
• Compressive strength
• Durability