Applications of AI for Bridge Engineering
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:
- Decision to commission.
- Design.
- Construction.
- Operation.
- Maintenance.
- Replacement.
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.
- Reich. Y. (1993), A Model of Aesthetic Judgment in Design, Artificial Intelligence in
Engineering, 8(2):141-153.
This paper presents a model of how aesthetic
judgment in design may be performed. It illustrates the ideas by using
examples of bridge shaped synthesized by Bridger.
(Postscript file, 810K)
- Reich, Y. and Fenves, S. J. (July, 1995),
A system that Learns to Design
Cable-Stayed Bridges, Journal of Structural Engineering, ASCE,
121(7):1090-1100.
This paper presents the most complete
description of Bridger. (Note however that due to ASCE's limit on the number of
words per paper [10,000] there are still details that were omitted.)
(Postscript file, 408K; Zipped PDF file, 855K)
Click for more information on Bridger.
- Reich, Y., Fenves, S. J., and Subrahmanian, E. (1994),
Flexible Extraction of Practical Knowledge from Bridge Databases, In
Proceedings of the First Congress on Computing in Civil Engineering
(Washington, DC), pp. 1014-1021.
(Postscript
file, 185K)
- Reich, Y. (1996),
Artificial Intelligence and Bridge Engineering,
Microcomputers in Civil Engineering, Vol 11, No 6, (in press).
This paper reviews the state-of-the-art of applying AI techniques to various
bridge engineering tasks discussed above and addresses the areas in which
AI can be most helpful to bridge engineering.
(Postscript file, 225K)
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Last modified by Yoram Reich on January 8, 1996