Among the many sustainability challenges in the construction industry, those related to the
application of concrete and its components are the most critical. Particularly, the production …

Abstract Analysis and design, as the most critical components in material science, require a
highly rigorous approach to assure long-term success. Due to a recent increase in the …

Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …

The cementitious composites have different properties in the changing environment. Thus,
knowing their mechanical properties is very important for safety reasons. The most important …

Concrete is a widely used construction material, and cement is its main constituent.
Production and utilization of cement severely affect the environment due to the emission of …

Data-driven machine learning (ML) is widely employed in the analysis of materials structure–
activity relationships, performance optimization and materials design due to its superior …

By replacing cement in concrete production with rice husk ash (RHA), the amount of cement
used and its environmental impact can be reduced. The objective of this study is to …

The use of rice husk ash (RHA) in concrete serves a positive role. The compressive strength
of RHA in concrete is predicted using supervised machine learning approaches such as …

The application of the traditional support vector regression (SVR) model to predict the
compressive strength of concrete faces the challenge of parameter tuning. To this end, a …

Ultra-high-performance concrete (UHPC) is a sustainable construction material; it can be
applied as a substitute for cement concrete. Artificial intelligence methods have been used …