| 摘要(英) |
Taiwan is a long-shaped island with high north-south mountains and many east-west rivers. Longitudinal traffic lines cross with transversal rivers forming a large amount of bridges which are the most import infrastructures for economic development. These bridges deteriorate due to aging, over-loaded traffic, and especially serious river scouring problems due to an average of 3%-5% slope of rivers which carry huge amounts of water into the sea in a very short time from summer storms or torrential rains. There are many research efforts focus on these scouring problems, such as in situ tests, hydraulic model tests, and mathematical simulations.
Deterioration of car bridges in Taiwan are recorded in the 2nd generation of the Taiwan Bridge Management System (TBMS2), which has a huge inventory of 25,000 bridge data including inspection and maintenance data for several years. However, there was no systematic statistic study for analyzing such big data the relationships between the deterioration of bridge substructures and rivers in various areas. Thus, this research is aimed at finding the characteristics of such deteriorations located in various rivers using big data approaches. Techniques of chart visualization and interactive chart panel are used to rapidly display the various combinations of deterioration of bridge substructures and the 118 river systems in Taiwan. Deteriorations of bridge substructures are classified based on severity to find out vulnerable locations, arears, river systems, and possible hidden information which are useful to bridge management. Results of this research will be provided to the bridge management agencies for reference in making decisions for bridge management. |
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