인공지능 기반 초고속 복합 재난 구조 성능 예측 기술

Artificial Intelligence-Based Fast-Running Models to Predict Multi-Hazard Structural Performance

  • Shin, Jiuk (Korea Institute of Civil Engineering and Building Technology)
  • 발행 : 2020.12.15

초록

키워드

참고문헌

  1. Shin, J., Choi, H. S., & You, Y. C., "BIM/GIS Platform-Based Seismic Damage Assessment System for Building Structures", Journal of Korean Association for Spatial Structures, Vol.20, No.1, pp.18-22, 2020, Retrieved from file:///C:/Users/user/Downloads/00020_001_18.pdf
  2. Shin, J., Scott, D. W., Stewart, L. K., Jeon, J. S., "Multi-hazard assessment and mitigation for seismically-deficient RC building frames using artificial neural network models", Engineering Structures, Vol.207, 2020, doi: 10.1016/j.engstruct.2020.110204
  3. FEMA (2012). Multi-Hazard Loss Estimation Methodology, Hazus-MH 2.1 Technical Manual-Earthquake Model. USA: Federal Emergency Management Agency.
  4. Shin, J., Stewart, L. K., Yang, C. S., Scott, D. W., "Implementation of Bond-Slip Performance Models in the Analyses of Non-Ductile Reinforced Concrete Frames Under Dynamic Loads", Journal of Earthquake Engineering, Vol.24, No.1, pp.129-154, 2020, doi: 10.1080/13632469.2017.1401565
  5. Shin, J., & Jeon, J. S., "Retrofit Scheme of FRP Jacketing System for Blast Damage Mitigation of Non-Ductile RC Building Frames", Composite Structures, Vol.228, 2019, doi: 10.1016/j.compstruct.2019.111328