Investigating the Effect of Curing Type on Compressive Strength of Normal Concrete Containing Zeolite Using Experimental Analysis and Fuzzy Logic

Abstract

Nowadays, concrete is one of the most widely used building materials around the world. The requirement and wide application of concrete have made it necessary to investigate its behavior and the factors affecting its behavior. In the process of concrete production, more precision is necessary to fulfill the requirements of efficiency and strength. In estimating the behavior of concrete, various mathematical techniques have been presented by researchers, and as a result, the theory of fuzzy sets provides a very effective tool for modeling and analyzing vague and imprecise concepts. The present research aims to predict the 28-day strength of concrete based on the 7-day strength in the presence and absence of zeolite pozzolan models with different curing methods in water, sack, and plastic using fuzzy logic. One of the novel aspects of this study is that it uses fuzzy logic to analyze lab data. This is because fuzzy logic can be used to analyze data even when there is uncertainty. Thus, 12 mixing designs have been prepared to check the grade of cement on the researched parameters based on the values of 300, 400, and 500 kg/m3 containing zeolite in the amounts of 0, 5, 10, and 15 weight percent of cement. All samples have been subjected to tests of concrete performance (slump test) and hardened concrete (compressive strength) at the age of 28 days. After completing the tests, the 28-day compressive strength of concretes has been predicted using fuzzy logic. This study shows that fuzzy logic can be applied as a powerful tool for modeling the compressive strength of concrete.

Received: 5 December 2022 | Revised: 16 January 2023 | Accepted: 31 January 2023

Conflicts of Interest

The authors declare that they have no conflicts of interest in this work.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Author Contribution Statement

Nima Navidi Aghdam: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization. Payam Rajabzadeh Kanafi: Writing – review & editing. Keivan Sohrabpour: Writing – review & editing.