Infrastructure asset management system for bridge projects in South Korea

Abstract

While there have been many studies on life cycle cost analysis and preventive maintenance planning, this study proposes an innovative method of bridge asset management in South Korea. Two different levels of approaches were used in this study. First, in the level of bridge elements, deterioration modeling and optimized maintenance repair and rehabilitation (MR&R) planning on bridge assets are proposed, using the bridge historical data of Han River in the city of Seoul. Second, the network level of bridge asset management is suggested, using historical MR&R cost and budget, overall-condition assessment results, and health index data. These two levels of approaches were developed into an Internet-based application so that facility managers can use them to review their past budgets and to plan their future budget based on historical data.

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References

  1. Bulusu, S. and Sinha, K. C. (1997). “Comparison of methodologies to predict bridge deterioration.” Transportation Research Record: Journal of the Transportation Research Board, No. 1597, pp. 34–42.

    Google Scholar 

  2. Butt, A. A., Shahin, M. Y., Feighan, K. J., and Carpenter, S. H. (1987). “Pavement performance prediction model using the Markov process.” Transportation Research Record, No. 1123, pp. 12–19.

    Google Scholar 

  3. Cady, P. D. and Weyers, R. E. (1984). “Deterioration rates of concrete bridge decks.” Journal of Transportation Engineering, Vol. 110, No. 1, pp. 34–44.

    Article  Google Scholar 

  4. Cesare, M. A., Santamarina, C., Turkstra, C., and Vanmarcke, E. H. (1992). “Modeling bridge deterioration with markov chains.” Journal of Transportation Engineering, Vol. 118, No. 6, pp. 820–833.

    Article  Google Scholar 

  5. Chae, M. J. and Abraham, D. M. (2001). “Neuro-fuzzy approaches for sanitary sewer pipeline condition assessment.” Journal of Computing in Civil Engineering, Vol. 15, No. 1, pp. 4–14.

    Article  Google Scholar 

  6. DeStefano, P. D. and Grivas, D. A. (1998). “Method for Estimating transition probability in bridge deterioration models.” Journal of Infrastructure Systems, Vol. 4, No. 2, pp. 56–62.

    Article  Google Scholar 

  7. Durango-Cohen, P. L. (2004). “Maintenance and repair decision making for infrastructure facilities without a deterioration model.” Journal of Infrastructure Systems, Vol. 10, No. 1, pp. 1–8.

    Article  Google Scholar 

  8. Hong, T. and Hastak, M. (2005). “MEMRRES: Model for evaluating maintenance, repair and rehabilitation strategies in concrete bridge decks.” Civil Engineering & Environmental Systems, Vol. 22, No. 4, pp. 233–248.

    Article  Google Scholar 

  9. Hong, T. and Hastak, M. (2007). “Evaluation and determination of optimal MR&R strategies in concrete bridge decks.” Automation in Construction, Vol. 16, No. 2, pp. 165–175.

    Article  Google Scholar 

  10. Hong, F. and Prozzi, J. A. (2006). “Estimation of pavement performance deterioration using Bayesian approach.” Journal of Infrastructure Systems, Vol. 12, No. 2, pp. 77–86.

    Article  Google Scholar 

  11. Jiang, Y. and Sinha, K. C. (1989). “Bridge service life prediction model using the Markov chain.” Transportation Research Record, No. 1223, pp. 24–30.

    Google Scholar 

  12. Morcous, G., Lounis, Z., and Mirza, M. S. (2003). “Identification of environmental categories for markovian deterioration models of bridge decks.” Journal of Bridge Engineering, Vol. 8, No. 6, pp. 353–361.

    Article  Google Scholar 

  13. Morcous, G., Rivard, H., and Hanna, A. M. (2002). “Modeling bridge deterioration using case-based reasoning.” Journal of Infrastructure Systems, Vol. 8, No. 3, pp. 86–95.

    Article  Google Scholar 

  14. Ortiz-Garcia, J. J., Costello, S. B., and Snaith, M. S. (2006). “Derivation of transition probability matrices for pavement deterioration modeling.” J. Transp. Eng., Vol. 132, No. 2, pp. 141–161.

    Article  Google Scholar 

  15. Shepard, R. W. (2005). “Bridge management issues in a large agency, structure & infrastructure engineering: Maintenance, management.” Life-Cycle Design & Performance, Vol. 1, No. 2, pp. 159–164.

    Google Scholar 

  16. Shepard, R. W. and Johnson, M. B. (2001). California bridge health index: A diagnostic tool to maximize bridge longevity investment, TR News, TRB, pp. 6–11.

    Google Scholar 

  17. Thompson, P. D. and Johnson, M. B. (2005). “Markovian bridge deterioration: Developing models from historical data.” Structure & Infrastructure Engineering, Vol. 1, No. 1, pp. 85–91.

    Article  Google Scholar 

  18. Veshosky, D., Beidleman, C. R., Buetow, G. W., and Demir, M. (1994). “Comparative analysis of bridge superstructure deterioration.” Journal of Structural Engineering, Vol. 120, No. 7, pp. 2123–2136.

    Article  Google Scholar 

  19. Winston, W. L. (1994). Operations research: Applications and algorithms 3rd edition, Duxbury Press, ISBN 0534520200, Philadelphia.

    MATH  Google Scholar 

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Correspondence to Taehoon Hong.

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Hong, T., Chae, M.J., Kim, D. et al. Infrastructure asset management system for bridge projects in South Korea. KSCE J Civ Eng 17, 1551–1561 (2013). https://doi.org/10.1007/s12205-013-0408-8

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Keywords

  • bridge management system
  • asset management
  • markov chain
  • life cycle costs
  • deterioration modeling