Recent Advances in CFD-based Bridge Fire Evaluations: A Brief Review

Abstract

Bridges, as the main elements of transportation networks, demand significant attention due to their unique structural characteristics and high consequences of fire incidents. So, it is crucial to enhance the fire resilience of these structures. Various studies have focused on the integration of advanced fire modeling techniques, including computational fluid dynamics (CFD), the finite element method (FEM), and artificial intelligence (AI) to improve the fire responses of the bridges. This article provided an overview of recent advancements in bridge fire modeling and addressing methodologies, challenges, and future directions for enhancing the fire resilience of bridge structures. Natural language processing (NLP) was employed for an in-depth exploration of bridge fire engineering topics and integrated CFD, FEM, and AI techniques. It has highlighted the importance of AI in enhancing real-time fire prediction and reducing related computational demands, emphasizing the importance of developing AI integrated approaches for the accelerated and effective post-fire assessment of bridge structures, considering their unique structural challenges and high impact of fires.