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سازه های مهندسی
جزئیات رویداد
همایش ، رویداد ، ژورنال
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  • probabilistic dynamic behavior of a long-span bridge under extreme events

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    • تاریخ ارائه: 1392/07/24
    • تاریخ انتشار در تی پی بین: 1392/07/24
    • تعداد بازدید: 559
    • تعداد پرسش و پاسخ ها: 0
    • شماره تماس دبیرخانه رویداد: -
     in addition to moderate wind and normal traffic scenarios, it is known that some extreme events may also occur on long-span bridges. these extreme events may include complex traffic congestion on the bridge, coupled with moderate or even strong wind. it is known that the excessive dynamic response and stress level of the bridge under these rare but critical scenarios, even for a very short period, may cause critical damage initiation or accumulation on some local bridge members. in addition to accelerating damages, the extreme events (e.g. heavy traffic) may even trigger the hazardous collapse of a whole bridge in some rare cases, especially when some hidden damage or design flaw has not been detected. therefore, even though the extreme cases associated with congested traffic and/or windy weather are relatively rare, it is important for bridge engineers to appropriately look into these unusual extreme events during design and life-time management. by applying the general bridge/traffic/wind coupled analysis methodology, the present study focuses on (1) conducting the cellular automaton (ca)-based traffic flow simulation of a long-span bridge and connecting roadways under incidental situations, (2) defining representative scenarios for the extreme events, and (3) numerically studying the bridge performance under these possible extreme events. by conducting studies on a comprehensive set of possible scenarios, it is anticipated that better understanding of extreme events of long-span bridges from the perspectives of strength and serviceability design will be achieved, which may contribute to the future design specification about long-span bridges. the proposed methodology will also offer a reasonable framework to replicate probabilistic traffic flow, characterize dynamic interaction and assess structural performance under those rare but critical situations integrally.

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