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LLM을 이용한 원전구조물 지진취약도 평가 프로그램 개발 KCI 등재
Development of Seismic Fragility Evaluation Program of NPP Structure using LLM
- 언어KOR
- URLhttps://db.koreascholar.com/Article/Detail/452673
pp.69-76
This study presents the development of an integrated software program that evaluates the seismic fragility of nuclear power plant (NPP) structures using a large language model (LLM). The program combines machine learning (ML)-based prediction of concrete aging deterioration and seismic floor response with a Monte Carlo simulation-based seismic fragility assessment, and integrates them into a single web-based environment. A distinctive feature of the program is an artificial intelligence assistant built upon an LLM and retrieval-augmented generation (RAG); it interprets natural-language queries, automatically invokes the relevant prediction and fragility-assessment tools, and generates answers together with supporting evidence retrieved from technical documents and automatically produced fragility curves. The ML modules predict chloride diffusion, carbonation, thermal effects, and floor response spectra, and recommend the best-performing algorithm automatically, while the fragility module derives lognormal fragility curves and supports aging-degradation scenarios. By connecting deterioration prediction, response prediction, fragility assessment, and literature-based reasoning into one conversational workflow, the developed program significantly lowers the technical barrier for ML-based seismic fragility evaluation and improves both accessibility and reliability. The overall architecture, development environment, and main functions of the program are described in detail.
1. 서론
2. 프로그램의 구성 및 개발환경
3. 경년열화 및 지진응답 예측 기능
4. 지진취약도 평가 기능
5. LLM 기반 인공지능 어시스턴트
6. 결론
감사의 글
References
