Elevated Temperature Effects on Geo-Polymer Concrete: An Experimental and Numerical- Review Study

The manufacture of cement plays a substantial role in the emission of carbon dioxide (CO2) into the atmosphere, hence exacerbating the adverse impacts of global warming. Consequently, the emergence of Geo-Polymer concrete has presented itself as a potentially feasible substitute owing to its commendable environmental sustainability. This manuscript provides a comprehensive analysis of prominent studies investigating the effects of increased temperatures and fire exposure on concrete across its entire operating duration. This study examines the significant impacts on the fundamental physical and mechanical characteristics of concrete, as revealed by laboratory experiments. Furthermore, this review comprehensively examines previous research endeavors that have used machine learning methodologies to predict tangible actions, aiming to optimize resource allocation, time efficiency, and cost-effectiveness in laboratory inquiries. Geo-Polymer concretes have exhibited remarkable resistance to elevated temperatures and severe fires, as evidenced by laboratory and field assessments of cracking, spalling, and strength degradation. Prior studies have demonstrated that both the aggregate type and temperature have a substantial impact on the degradation of compressive strength. Moreover, previous research has indicated that Geo-Polymeric concrete, which is comprised of fly ash, exhibits superior heat resistance compared to conventional concrete using Portland cement, withstanding temperatures of up to 400 degrees Celsius. This research also highlights the widespread adoption of the Artificial Neural Network (ANN) technique in forecasting the compressive strength of conventional concrete. Conversely, alternative approaches such as the Genetic Weighted Pyramid Operation Tree (GWPOT) are preferred for high-performance concrete. The primary objective of this extensive investigation is to establish a fundamental basis for future studies on sustainable alternatives to concrete and approaches for predictive modeling.