Applications of AI for Bridge Engineering



A Brief Introduction:

Bridge engineering presents significant opportunities for AI, yet little of them is realized. Opportunities exist in each of the tasks involved in the life-cycle of bridges: Each of these tasks generates information that can be fed back to previous tasks and enrich them as shown in Figure 1.

Figure 1: Tasks in bridge engineering and their contextual influences

This information is rarely made explicit or used. Recent efforts to create bridge management systems (BMS) focus of the capture of diverse information about bridges as it is collected in these tasks and use it in future projects. Nevertheless, the mechanisms that are supposed to use this information are too limited to expose the diverse knowledge embedded in this information. Different AI techniques such as machine learning can assist in creating these backward connections between the tasks as shown in Figure 2.

Figure 2: Information flow between bridge engineering tasks

Read more about it in (Reich, Y., Fenves, S. J., and Subrahmanian, E., 1994).

In a recent paper I reviewed the state-of-the-art of applying AI techniques to these tasks and discussed the areas in which AI can be most helpful to bridge engineering.

If you have pointers to work on AI applications to bridge engineering, I'll be most grateful if you can email them to me for incorporation in the above document and here on this page.

A Sample Publications Include:

Pointers to Information on Bridge Engineering:

Pointers to Information on AI Applications to Bridge Engineering:

Pointers to information relating Intelligence and Structures:

What do search engines (i.e., Lycos) say about bridges etc.:

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Last modified by Yoram Reich on January 8, 1996