Statewide Performance Function for Steel Bridge Protection Systems
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VIEW THE REPLYPublication: Journal of Performance of Constructed Facilities
Volume 16, Issue 2
Abstract
A performance function is the relationship between the bridge paint condition rating and time. This function reflects the level of service of the bridge paint. The performance functions of steel bridge paint for state structures maintained by the Indiana Department of Transportation (INDOT) were developed using both regression analysis and Markov chains. The regression and Markov models were used to predict the condition rating of a bridge’s paint at a given age. The probabilistic model that was developed with Markov chains was used to reflect the stochastic nature of bridge paint conditions. These deterministic and stochastic methods have been applied to the existing and the new bridges’ paint systems in INDOT structures. The existing paint systems are lead-based and zinc-vinyl. On the other hand, the new paint system is three-coat. The results indicate that both models are very efficient in representing the deterioration model for bridge paint systems based on historical data.
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References
Abraham D. M., Wirahadikusumah R., Short T. J., and Shahbahr-ami S. ( 1998 ). “ Optimization modeling for sewer network management. ” J. Constr. Eng. Manage., 124 ( 5 ), 402 – 410.
Butt, A. A., Shahin, M. Y., Carpenter, S. H., and Carnahan, J. V. (1994). “Application of Markov process to pavement management systems at network level.” Proc., 3rd Int. Conf. On Managing Pavements, National Research Council, Washington, D.C., 2, 159–172.
Butt, A. A., Shahin, M. Y., Feighan, K. J., and Carpenter, S. H. (1987). “Pavement performance prediction model using the Markov process.” Transportation Reseach Record 1123, Transportation Research Board, Washington, D. C., 12–19.
General Algebraic Modeling System (GAMS), Version 2.0. (1998). GAMS Development Corporation, Washington, D. C.
Jiang, Y., and Sinha, K. C. (1990). “The development of optimal strategies for maintenance, rehabilitation, and replacement of highway bridges.” Final Rep., Vol. 6: Performance Analysis and Optimization, Joint Highway Research Project No. C-36-731.
Jiang, Y., Saito, M., and Sinha, K. C. (1998). “Bridge performance prediction model using Markov chains.” Transportion Research Record, Transportation Research Board, Washington, D. C., 939–946.
Neter, J., Kutner, M. H., Nachtsheim, C. J., and Wasserman, W. (1996). Applied linear statistical models, McGraw-Hill, New York.
SAS 6.12 for Windows, Version 4.0. (1996). SAS Institute, Cary, N.C.
Wirahadikusumah, R. (1998). “Sewer management life cycle cos tapproach.” PhD research proposal, Purdue Univ., West Lafayette, Ind.
Zayed, T. M., and Fricker, J. D. (1999). “Life-cycle cost analysis and maintenance plan.” Rep. prepared for INDOT, Construction Division, School of Civil Engineering, Purdue Univ., West Lafayette, Ind.
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Information
Published In
Journal of Performance of Constructed Facilities
Volume 16 • Issue 2 • May 2002
Pages: 46 - 54
Copyright
Copyright © 2002 American Society of Civil Engineers.
History
Received: Feb 22, 2001
Accepted: Oct 26, 2001
Published online: Apr 15, 2002
Published in print: May 2002
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