Early Warning System Development for Bridge Collapse
2015-12-15

Cloud Network of the Early Warning System

Sensor Equipped at a Bridge Pier for Real-time Monitoring of Scour

Bridge collapse due to floods and foundation scouring has been a serious problem worldwide. Even in recent years, floods and flash floods caused billions of dollars in damage in the US each year. Current early warning systems of bridge collapsing are extremely ineffective. As a result, the National Applied Research Laboratories (NARLabs) have put their efforts on the floods impact forecasting and real-time monitoring system development to provide an early warning mechanism for bridge collapse. This system provides an effective and practical indicator for decision making for bridge closing during extreme weather events and is also a bridge maintenance index. With this system, fetal events and damages due to natural hazards can be reduced and the costs on the maintenance will be much more effective.

Scour problem plays a key role in many bridge failures that occur around the globe. More than 1000 bridges collapsed over the past 30 years in the US with 60% of the failures caused by scour. This serious problem also happens in many East-Asian countries such as Taiwan and Japan, owing to the fact that these areas are subject to typhoon, hurricane and flood events each year during the Summer and Fall seasons. However, due to the complicated interaction between fluid flow patterns caused by obstructing pier and erosion of sediment leading to the formation of scour hole, it is extremely difficult to develop a reliable analytical/numerical model capable of taking into account various controlling and inter-related factors without over simplification.

Collaborating with the interdisciplinary institutes of NARLabs including Taiwan Typhoon and Flood Research Institute (TTFRI), National Center for Research on Earthquake Engineering (NCREE), Instrument Technology Research Center (ITRC), National Chip Implementation Center (CIC), National Nano Device Laboratories (NDL) and National Center for High-performance Computing (NCHC), we proposed a six-hour early warning forecasting technique by using the upstream rainfall data to estimate the stream possible flow level, the flow velocity and the scour depth of the target bridges. This NARLabs Team developed this bridge early warning monitoring system with a sensory system integrating various types of sensors, such as arrayed scouring sensor for real-time scour depth monitoring, arrayed forcing sensor for turbulent flow velocity measurements which are different from the conventional surface flow velocity data, bridge pier vibration sensor, and combined with the commercial video camera the equipment of measuring the surface flow velocity and the flow level. Data from these sensors are connected to the cloud server with wireless sensor network for real-time signal processing and synchronized to present the immediate public needs. This proposed novel technique for scour monitoring is more resilient to harsh environments with extreme flow conditions and is capable of measuring both scouring and deposition processes at bridge piers. This bridge multi-hazards early warning system has been successfully demonstrated in the river basins in Taiwan.

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