余震
大洪水
码头
桥梁冲刷
地质学
岩土工程
桥(图论)
自然灾害
流离失所(心理学)
地震学
结构工程
工程类
地理
心理治疗师
心理学
考古
内科学
海洋学
医学
作者
K. K. Jithiya,Muhamed Safeer Pandikkadavath,Sujith Mangalathu,Praveen Nagarajan
出处
期刊:Lecture notes in civil engineering
日期:2021-09-21
卷期号:: 211-221
被引量:2
标识
DOI:10.1007/978-981-16-4617-1_17
摘要
Natural hazards such as earthquakes and floods can affect the safety of bridges negatively. The lateral support loss at the foundation level due to scour (flood-induced) makes the bridges more vulnerable to damages compared to the normal scenario (no scour condition), especially in the event of seismic disturbances. For bridges located at seismically active and flood-prone regions, multi-hazard scenarios of successive occurrence of flood-induced scour and earthquake can yield a better response prediction. Many times the seismic Mainshocks follow several Aftershocks that in turn make the situation even worse, as the secondary shocks may act on the already damaged structure during the Mainshock. The present investigation aims to assess the seismic performance (Mainshock alone and Mainshock—Aftershock sequence) of reinforced concrete bridges that have been inflicted by flood-induced scouring. To quantify the scour depth activity, the regional annual peak flood discharge data with different return period is used. Additionally, the soil-structure interaction is accommodated using suitable spring models as per the accepted recommendations. The selected study bridge is incorporated in a suitable modelling platform considering the scour effect; successively nonlinear dynamic (time history) analyses are performed to estimate the dynamic bridge responses in the absence and presence of flood-induced scour. The structural responses of the bridges are mainly evaluated in terms of displacement ductility (ratio of actual displacement to related yield displacement). Successively seismic fragility curves are developed corresponding to different damage states under both Mainshock and Mainshock—Aftershock events and the results are compared.
科研通智能强力驱动
Strongly Powered by AbleSci AI