Seismic Retrofitting of Reinforced Concrete Structures Using GFRP Materials and the Role of Artificial Intelligence in Performance Optimization

Reinforced concrete (RC) structures are highly vulnerable to seismic loads, which has led to increased interest in effective retrofitting methods. Among various techniques, Glass Fiber Reinforced Polymer (GFRP) composites have become prominent due to their lightweight nature, high tensile strength, and corrosion resistance. This paper outlines the fundamental concepts of seismic retrofitting and highlights the benefits and limitations of GFRP materials. Several application methods for retrofitting RC structures with GFRP are discussed. Furthermore, the integration of Artificial Intelligence (AI), especially machine learning (ML) techniques and Artificial Neural Networks (ANNs), into the field of seismic retrofitting is explored. These AI tools are capable of evaluating structural performance, predicting seismic behavior, and optimizing retrofit designs. By combining traditional structural engineering principles with modern AI technologies, more accurate and efficient retrofitting strategies can be developed. The paper aims to present a concise yet informative overview of how GFRP and AI can be jointly used to enhance seismic resilience.

کلیدواژه ها:

Seismic Retrofitting ، Reinforced Concrete ، GFRP ، Artificial Intelligence ، Machine Learning ، Artificial Neural Networks