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Title |
Artificial Intelligence?Driven Design, Monitoring, and Maintenance in Structural Engineering: Current Advances and Challenges
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Authors |
최원준(Wonjun Choi) ; 이상현(Sanghyun Lee) ; 김치경(Cheekyeong Kim) ; 허석재(Seokjae Heo) |
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DOI |
https://doi.org/10.4334/JKCI.2025.37.5.645 |
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Keywords |
구조공학; 인공지능; 구조 건전성 모니터링(SHM); 예측 유지관리; 내진 설계 structural engineering; artificial intelligence; structural health monitoring (SHM); predictive maintenance; seismic design |
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Abstract |
Artificial intelligence (AI) has increasingly transformed structural engineering over the past decade. However, the rapid proliferation of diverse AI applications often obscures a holistic understanding of their true impact on the engineering profession. This paper addresses this gap by providing a systematic review of 35 key studies from 2015 to 2025 across five core domains: structural health monitoring (SHM), design optimization, seismic design, predictive maintenance, and large language models (LLMs). Rather than viewing them as isolated facets, we synthesize emerging these trends to propose that the field is converging toward a new, unified paradigm: the ‘Human-AI Collaborative System.’ In this paradigm, AI excels as a tireless computational partner for complex analyses and data processing, while the human engineer is elevated to the role of a strategic decision-maker, focusing on problem definition, critical judgment, and ethical oversight. This review highlights that the primary challenge is no longer just developing more accurate AI, but rather creating a seamless and reliable integration framework for human-AI collaboration. Ultimately, this paper provides a forward-looking perspective on how such synergy will define the future of structural engineering, fostering safer, more efficient, and more innovative built environments.
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