Analysis of the Influence of Nanosilica and Industrial By-Products on the Durability of Concrete Using Intelligent Modeling.

The present study investigates the influence of nanosilica and industrial waste materials on the durability performance of concrete using intelligent modeling techniques. Nanosilica, as a highly reactive pozzolanic material, improves the microstructure and mechanical properties of concrete, while the incorporation of industrial by-products such as fly ash, slag, or silica fume contributes to sustainability and waste reduction. In this research, various concrete mixes containing different proportions of nanosilica and industrial wastes were analyzed to evaluate parameters such as compressive strength, permeability, and resistance to chloride ion penetration. Intelligent modeling methods—including Artificial Neural Networks (ANN) and Gene Expression Programming (GEP)-were employed to predict the durability behavior and employed to predict the durability behavior and optimize mix design. The results demonstrated that the combination of nanosilica and industrial waste significantly enhanced the durability of concrete and that the predictive models exhibited high accuracy, indicating the potential of AI-based approaches for sustainable and durable concrete design.

Keywords:

Nanosilica , Industrial waste , Concrete durability , Intelligent modeling , Artificial Neural Network (ANN) , Gene Expression Programming (GEP) , Sustainability , Sustainable concrete