Review on the Use of Artificial Intelligence to Predict Fire Performance of Construction Materials and Their Flame Retardancy

Molecules. 2021 Feb 15;26(4):1022. doi: 10.3390/molecules26041022.

Abstract

The evaluation and interpretation of the behavior of construction materials under fire conditions have been complicated. Over the last few years, artificial intelligence (AI) has emerged as a reliable method to tackle this engineering problem. This review summarizes existing studies that applied AI to predict the fire performance of different construction materials (e.g., concrete, steel, timber, and composites). The prediction of the flame retardancy of some structural components such as beams, columns, slabs, and connections by utilizing AI-based models is also discussed. The end of this review offers insights on the advantages, existing challenges, and recommendations for the development of AI techniques used to evaluate the fire performance of construction materials and their flame retardancy. This review offers a comprehensive overview to researchers in the fields of fire engineering and material science, and it encourages them to explore and consider the use of AI in future research projects.

Keywords: artificial intelligence; chemical kinetics; combustion; flame retardants; machine learning; pyrolysis.

Publication types

  • Review

MeSH terms

  • Artificial Intelligence*
  • Construction Materials / analysis*
  • Fires / prevention & control*
  • Flame Retardants / analysis*
  • Machine Learning
  • Neural Networks, Computer

Substances

  • Flame Retardants