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Abstract

Recently, the necessity of developing a practical bridge management system (BMS) has been pointed out in Japan, because the maintenance of existing bridges has become a major social concern. The aim of this study was to develop a practical BMS for deteriorated concrete bridges. The proposed system (J-BMS) uses multilayered neural networks to predict deterioration processes in existing bridges, to construct an optimal maintenance plan for repair or strengthening measures based on minimizing life-cycle cost, and to estimate the maintenance cost. A comparison of the results of applying this system to some actual in-service bridges with the results of questionnaire surveys of experts indicates that optimal maintenance planning as well as bridge rating can be predicted accurately by this system.

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References

Thompson

P. D.

, Small

E. P.

, Johnson

, and Marshall

A. R.

. The PONTIS Bridge Management System. Structural Engineering International, Journal of the IABSE, Vol. 8, No. 4, 1998, pp. 303–308.

Miyamoto

, Kusida

, and Kinoshita

. Concrete Bridge Rating Expert System with Machine Learning. Proc., IABSE Colloquium on Knowledge Support Systems in Civil Engineering, Bergamo, Italy, 1995, pp. 301–306.

Miyamoto

, and Kusida

. Development of Neuro-Fuzzy Expert System for Serviceability Assessment of Concrete Bridges. Technology Reports of Yamaguchi University, Vol. 5, No. 5, 1996, pp. 335–353.

Miyamoto

, Morikawa

, Kusida

, and Tokuyama

. A Knowledge-Based Expert System Application in Structural Safety Assessment of Concrete Bridges. Bridge Management, Vol. 2, 1993, pp. 96–109.

Miyamoto

, Kusida

, Adachi

, and Matsumoto

. Development of Bridge Management System (BMS). JSCE, Vol. 560, No. VI-34, 1997, pp. 91-106 (in Japanese).

Miyamoto

, Kawamura

, and Nakamura

. Multiobjective Optimization of Maintenance Planning for Existing Bridges by Using Bridge Management System (BMS). JSCE, Vol. 588, No. VI-38, 1998, pp. 191-208 (in Japanese).

Goldberg

D. E.

Genetic Algorithm in Search, Optimization and Machine Learning. Addison-Wesley Publishing Company, Reading, Mass., 1989.

Gen

, and Chebg

. Genetic Algorithms and Engineering Design. John Wiley & Sons, New York, 1997.

Gen

, and Chebg

. A Survey of Techniques in Genetic Algorithms. Proc., Third IEEE Conference on Evolutionary Computation, IEEE Press, Nagoya, Japan, 1996, pp. 804–809.

10.

Michalewicz

A Survey of Constraint Handling Techniques in Evolutionary Computation Methods. Evolutionary Programming IV. MIT Press, Cambridge, Mass., 1995, pp. 135–155.

11.

Orvosh

, and Davis

. Using a Genetic Algorithm to Optimize Problems with Feasibility Constraints. Proc., First IEEE Conference on Evolutionary Computation, IEEE Press, Orlando, Fla., 1994, pp. 548–552.

12.

Kusida

, Miyamoto

, and Kinoshita

. Development of Concrete Bridge Rating Prototype Expert System with Machine Learning. ASCE Journal of Computing in Civil Engineering, Vol. 11, No. 4, 1997, pp. 238–247.

13.

Nishimura

, Fujii

, and Miyamoto

. Diagnosis of Reinforced Concrete Slabs for Highway Bridges. Memoirs of the Faculty of Engineering Kobe University, Vol. 30, 1983, pp. 51–69.

14.

Morikawa

, Miyamoto

, and Takeuchi

. Structural Safety Evaluation and Remaining Life Prediction of Concrete Bridges Based on Statistical Analysis. Concrete Library of JSCE No. 28, Dec. 1996, pp. 51–64.

Practical Applications of a Bridge Management System in Japan

Abstract

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