Keywords

Abstract

Recycled aggregate; 

Plastic waste; 

High-density polyethylene; 

Polypropylene; 

Response surface Method; 

 Artificial neural network

The paper aims to use most of the recycled material from the waste and develop a sustainable Eco-Friendly Self-Compacting Concrete (EF-SCC). Two different plastic wastes, High-Density Polyethylene (HDPE) and Polypropylene (PP), were collected from the dumping yard, thoroughly cleaned, and shredded into the desired shape and size. The plastic was substituted with fine aggregate (FA) in amounts ranging from 5% to 20%, with a 5% rise in each mix. The recycled coarse aggregate was obtained by breaking the concrete cubes, beams, and cylinders available for testing at the concrete technology lab. Totally 4 mixes were prepared for M40 grade EF-SCC to determine the mechanical property at 4 different ages (7, 14, 28 and 56 days). The compressive strength results were then predicted using statistical tools such as RSM and ANN. It is observed that both HDPE and PP have workability in the range of 650mm to 800mm, which is acceptable according to EFNARC 2002. The RSM method yielded 99.69% for PP material, while HDPE had 98.17%. The optimum compressive strength values were achieved at 7.5% of HDPE and 5% of PP material at 28 days and 60 days of curing. The training, validation, Test, and All values of R for M40 grade concrete for HDPE and PP material were 0.9955, 0.9980, 0.9244, 0.9241, and 1, 0.972, 0.802, 0.972 respectively. The flexural strength of EF-SCC showed the best results at 15% replacement. The prediction of actual compressive strength with RSM was more accurate for HDPE material compared to ANN. Recycled aggregate showed positive signs in using waste material in construction industries.

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