Bridge collapses caused by floods and foundation scouring have been a severe problem worldwide. In recent years, floods and flash floods in the United States have caused billions of dollars in damage each year. Nevertheless, current early warning systems for bridge collapses are extremely ineffective.
Scour problems play a key role in many bridge failures that occur worldwide. More than 1000 bridges in the United States have collapsed over the past 30 years, with 60% of the failures caused by scouring. This severe problem has also happened in many East Asian countries such as Taiwan and Japan, due to the fact that these areas are subject to typhoons and floods each year during the summer and fall. However, because of the complex interaction between fluid flow patterns caused by obstructing piers and the erosion of sediment leading to the formation of scour holes, it is extremely difficult to develop a reliable analytical/numerical model that can account for various controlling and interrelated factors without oversimplification.
To overcome the challenges of scouring, National Applied Research Laboratories (NARLabs) developed a sensory system for flood impact forecasting and real-time monitoring to provide an early warning mechanism for bridge collapses. This early warning system for bridge collapses is an effective and practical indicator for decision making regarding bridge closures during extreme weather events, and it also provides a bridge maintenance index.
NARLabs proposed a 6-hour early warning forecasting technique that involves using upstream rainfall data to estimate the possible stream flow level, flow velocity, and scour depth of target bridges. For real-time monitoring, the early warning system for bridge collapses integrates various types of sensors such as an arrayed scouring sensor for real-time scour depth monitoring, an arrayed forcing sensor for turbulent flow velocity measurements (which are distinct from conventional surface flow velocity data), a bridge pier vibration sensor, and a commercial video camera combined with equipment for measuring the surface flow velocity and flow level. Data from these sensors are connected to a cloud server by using a wireless sensor network for real-time signal processing that is synchronized to address immediate public needs.
Figure 1. Cloud Network of the Early Warning System for Bridge Collapses
The early warning system for bridge collapses was developed by the interdisciplinary research centers of NARLabs, comprising 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). It was successfully tested in river basins of Taiwan. This proposed novel technique for scour monitoring is resilient to harsh environments under extreme flow conditions and can measure both scouring and deposition processes at bridge piers. With the early warning system for bridge collapses, fatal events and damage caused by natural hazards can be reduced at affordable maintenance costs.
Figure 2. Sensor Equipment at a Bridge Pier for Real-time Scour Monitoring