Predicting the strength of seashell concrete using Adaptive Neuro-Fuzzy Inference System: An experimental study

Keywords: Seashell concrete, Seashell powder, Seashell aggregate, Curing time, ANFIS, Sustainable concrete


Seashell is a hard, protective outer layer created by an animal that lives in the sea. Empty seashells are often found washed up on beaches by beachcombers. This marine by-product can be used to partial replacement of coarse aggregate or cement in concrete. This paper describes the use of seashell powder and aggregate in the concrete for the replacement of cement and coarse aggregate. The effect of seashell waste in the concrete was studied in terms of its compressive strength, tensile strength and flexural strength after 28, 56 and 90 days of curing. The replacement of cement by seashell powder were 10%, 20% and 30% and replacement of coarse aggregate by seashell aggregate are 5%, 10% and 15%. The properties of seashell concrete were compared with control mix specimen of M25 grade of concrete. Also, it has been tried to predict the strength of the seashell concrete utilizing adaptive neuro-fuzzy inference system (ANFIS). The prediction of strength with the tool was agreeable with the experimental strength with the minimal error of less than 5%. This study concludes, that partial replacement of cement and coarse aggregate by seashell waste enhances the mechanical properties of the concrete significantly and enable proper utilization of these seashell waste as sustainable material for the concrete.


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Author Biographies

Sangeetha Palanivelu, Sri Sivasubramaniya Nadar College of Engineering

Department of Civil Engineering, Sri Sivasubramaniya Nadar College of Engineering, Chennai, Tamilnadu, India.

Shanmugapriya Marayanagaraj, Sri Sivasubramaniya Nadar College of Engineering

Department of Mathematics, Sri Sivasubramaniya Nadar College of Engineering, Chennai, Tamilnadu, India.


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How to Cite
Palanivelu, S., & Marayanagaraj, S. (2023). Predicting the strength of seashell concrete using Adaptive Neuro-Fuzzy Inference System: An experimental study. ITECKNE, 20(1), 34-44.
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