Combined influence of eggshell powder and nylon fiber on self-compacting concrete production: experimental assessment and machine learning quantifications

Abstract

The focus of this paper is on the study of the impact of nylon fibers (NF) as a reinforcing agent and eggshell powder (ESP) as an SCM in the production of self-compacting concrete (SCC) for sustainable buildings design. For this reason, the experiment involves finding the optimum amounts of ESP replacement for cement, which ranges between 5% to 15%, and the quantity of nylon fibers added in percent, which is between 0.05% and 0.10%. This study dealt with using ESP and nylon fibers for fresh, mechanical, durability, and microstructure of concrete. Additionally, random forest (RF) and artificial neural network (ANN) based machine learning methods were planned in order to examine the fresh and mechanical response of concrete. The study discovered that concrete containing 0.1 percent nylon fibers and 5 percent ESP performed relatively better compared to the control sample, especially in hardened characteristics. After 28 days, the compressive and splitting tensile strengths increased by 6% and 4%, respectively, compared to the control mixture. Although the UPV test revealed excellent quality in all mixtures, increased ESP levels decreased concrete strength. The maximum R2 value (0.989) and the minimum RMSE value (1.393) for the RF model indicate a strong overall estimation. The study emphasizes the potential of enhancing the overall performance of SCC by utilizing eggshell powder and nylon fibers. These results present a more sustainable approach to concrete production and contribute to a reduced environmental footprint.