Typical advances of artificial intelligence in civil engineering

Abstract

Artificial intelligence (AI) provides advanced mathematical frameworks and algorithms for further innovation and vitality of classical civil engineering (CE). Plenty of complex, time-consuming, and laborious workloads of design, construction, and inspection can be enhanced and upgraded by emerging AI techniques. In addition, many unsolved issues and unknown laws in the field of CE can be addressed and discovered by physical machine learning via merging the data paradigm with physical laws. Intelligent science and technology in CE profoundly promote the current level of informatization, digitalization, autonomation, and intellectualization. To this end, this paper provides a systematic review and summarizes the state-of-the-art progress of AI in CE for the entire life cycle of civil structures and infrastructure, including intelligent architectural design, intelligent structural health diagnosis, intelligent disaster prevention and reduction. A series of examples for intelligent architectural art shape design, structural topology optimization, computer-vision-based structural damage recognition, correlation-pattern-based structural condition assessment, machine-learning-enhanced reliability analysis, vision-based earthquake disaster evaluation, and dense displacement monitoring of structures under wind and earthquake, are given. Finally, the prospects of intelligent science and technology in future CE are discussed.