https://scholars.lib.ntu.edu.tw/handle/123456789/548312
標題: | A multi-hazard safety evaluation framework for a submerged bridge using machine learning model | 作者: | KUO-WEI LIAO Hoang, N.-D. Chien, F.-S. |
公開日期: | 2019 | 來源出版物: | 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019 | 摘要: | This study proposes a submerged bridge safety evaluation process against seismic and flood hazards. Due to the uncertainties in the scours, seismic hazard, and structural performance for a given seismic excitation are inevitable, reliability analysis is adopted. A machine-learning based scour risk curve, which is established by the multivariate adaptive regression splines (MARS) incorporated with firefly algorithm (FA), is built to reflect the flood hazard. The seismic hazard is measured using a code-based probabilistic seismic hazard curve. A series of nonlinear time-history analyses are performed to determine the structural performance under different peak-ground-acceleration values. Displacement ductility is used to measure the bridge performance under attacks of both hazards. The influence of the immersed water depth on a bridge's performance is investigated. A case study, in which the nonlinear behaviors in concrete (including core and cover areas), steel bar and soil are included in a bridge model, is conducted to illustrate the proposed methodology and the structural performances with added mass are investigated to show the submerged water effect. According to the results obtained, highly variability of seismic performances is observed and it is important to include the immersed water depth to capture the seismic capacity of a bridge if the submerged bridge depth is great. ? 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019. All rights reserved. |
URI: | https://www.scopus.com/inward/record.url?eid=2-s2.0-85083951044&partnerID=40&md5=39dd022e457a4ddeb2272b58b79ec153 https://scholars.lib.ntu.edu.tw/handle/123456789/548312 |
SDG/關鍵字: | Bridges; Floods; Hazards; Optimization; Reliability analysis; Scour; Seismic response; Structural analysis; Time series analysis; Uncertainty analysis; Underwater soils; Displacement ductility; Machine learning models; Multivariate adaptive regression splines; Nonlinear time history analysis; Peak ground acceleration; Seismic excitations; Seismic Performance; Structural performance; Machine learning |
顯示於: | 生物環境系統工程學系 |
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