GPR-Based Fuzzy Model for Bridge Deck Corrosiveness Index
Publication: Journal of Performance of Constructed Facilities
Volume 30, Issue 4
Abstract
Ground-penetrating radar (GPR) is a rapid technology for evaluating condition of concrete bridge decks subject to rebar corrosion. In this paper, based on a threshold model recently proposed in the literature, a bridge deck corrosiveness index (BDCI), is developed to have an idea where a bridge deck is during its continuous service life and to suggest corresponding maintenance activity. Based on fuzzy set theory, expert opinions were used to calibrate fuzzy membership function for each condition category found by GPR. Then, for a particular bridge deck, area percentages of all condition categories would be utilized to aggregate these functions into a BDCI using weighted fuzzy union (WFU) operation. The benefit of the developed system is twofold. First, it is based on GPR, a more accurate inspection technology. Second, it employs the knowledge provided by bridge community, and, in the meantime, has the capability to deal with fuzzy information associated with expert responses. Using an automated software, the system is illustrated for several concrete bridge decks in North America. Because the case studies show that the developed system is easy to be implemented, it would be an effective tool for transportation agencies in North America where the corrosion of rebar in concrete bridge decks is one of biggest concerns.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The authors of this paper appreciate the Ministry of Transportation of Quebec (MTQ), Radex Detection Inc., and Mitacs for their funding and support of this study. In addition, they would like to thank Dr. Nenad Gucunski, Rutgers University, and Mr. Francisco Romero, Romero NDT&E Inc. for providing part of the data used in this research. Finally, the authors are grateful to Mr. Thai Hoa Le who helped them in the development of the computer program.
References
AASHTO. (1994). Manual for condition evaluation of bridges, Washington, DC.
Arslan, A., and Kaya, M. (2001). “Determination of fuzzy logic membership functions using genetic algorithms.” Fuzzy Sets Syst., 118(2), 297–306.
ASCE. (2013). “Report card for America’s infrastructure.” 〈http://www.infrastructurereportcard.org/bridges/〉 (May 12, 2014).
ASTM. (2008). “Standard test method for evaluating asphalt-covered concrete bridge decks using ground penetrating radar.” D6087-08 West Conshohocken, PA.
Baruch, Y. (1999). “Response rate in academic studies—A comparative analysis.” Human Relat., 52(4), 421–438.
Beliakov, G. (1996). “Fuzzy sets and membership functions based on probabilities.” Inform. Sci., 91(1–2), 95–111.
Dinh, K., et al. (2015). “Clustering-based threshold model for condition assessment of concrete bridge decks with ground penetrating radar.” Transportation Research Record 15-1123, Transportation Research Board, Washtington, DC.
Dombi, J., and Gera, Z. (2005). “The approximation of piecewise linear membership functions and Łukasiewicz operators.” Fuzzy Sets Syst., 154(2), 275–286.
FHWA (Federal Highway Administration). (2001). “Reliability of visual inspection for highway bridges, volume I: Final report.” FHWA-RD-01-020, U.S. Dept. of Transportation, McLean, VA.
Golabi, K., and Shepard, R. (1997). “Pontis: A system for maintenance optimization and improvement of U.S. bridge networks.” Interfaces, 27(1), 71–88.
Gucunski, N., Romero, F., Imani, A. S., and Fetrat, F. (2013). “NDE-based assessment of deterioration progression in concrete bridge decks.” Transportation Research Board 92nd Annual Meeting, Transportation Research Board, Washington, DC.
Hadipriono, F. C. (1988). “Fuzzy set concepts for evaluating performance of constructed facilities.” J. Perform. Constr. Facil., 209–225.
Hisdal, E. (1986). “Infinite-valued logic based on two-valued logic and probability, Part 1.2.” Int. J. Man-Mach. Stud., 25(2), 113–138.
Ishibuchi, H., Nozaki, K., and Tanaka, H. (1993). “Efficient fuzzy partition of pattern space for classification problems.” Fuzzy Sets Syst., 59(3), 295–304.
Kawamura, K., and Miyamoto, A. (2003). “Condition state evaluation of existing reinforced concrete bridges using neuro-fuzzy hybrid system.” Comput. Struct., 81(18–19), 1931–1940.
Kumar, S., and Taheri, F. (2007). “Neuro-fuzzy approachs for pipeline condition assessment.” Nondestr. Test. Eval., 22(1), 35–60.
Lee, K. H. (2005). First course on fuzzy theory and application, Springer, Heidelberg, Germany.
Liang, M., Wu, J., and Liang, C. (2001). “Multiple layer fuzzy evaluation for existing reinforced concrete bridges.” J. Infrastruct. Syst., 144–159.
Lin, C. C., and Chen, A. P. (2002). “Generalization of Yang et al.’s method for fuzzy programming with piecewise linear membership functions.” Fuzzy Sets Syst., 132(3), 347–352.
Medasani, S., Kim, J., and Krishnapuram, R. (1998). “An overview of membership function generation techniques for pattern recognition.” Int. J. Approximate Reasoning, 19(3–4), 391–417.
Najjaran, H., Sadiq, R., and Rajani, B. (2005). “Condition assessment of water mains using fuzzy evidential reasoning.” Systems, Man, and Cybernetics, IEEE Int. Conf., Vol. 4, IEEE, 3466–3471.
Roberts, J. E, and Shepard, D. (2000). “Bridge management for the 21st century.” Transportation Research Record 1696, Transportation Research Board, Washington, DC, 197–203.
Sasmal, S., and Ramanjaneyulu, K. (2008). “Condition evaluation of existing reinforced concrete bridges using fuzzy based analytic hierarchy approach.” Expert Syst. Appl., 35(3), 1430–1443.
Sasmal, S., Ramanjaneyulu, K., Gopalakrishnan, S., and Lakshmanan, N. (2006). “Fuzzy logic based condition rating of existing reinforced concrete bridges.” J. Perform. Constr. Facil., 261–273.
Scherschligt, D., and Kulkarni, R. B. (2003). “Pontis-based health indices for bridge priority evaluation.” 9th Int. Bridge Management Conf., Transportation Research Board, The National Academies, Washington, DC, 29–45.
Sun, L., and Gu, W. (2011). “Pavement condition assessment using fuzzy logic theory and analytic hierarchy process.” J. Transp. Eng., 648–655.
Tamaki, F., Kanagawa, A., and Ohta, H. (1998). “Identification of membership functions based on fuzzy observation data.” Fuzzy Sets Syst., 93(3), 311–318.
Tarighat, A., and Miyamoto, A. (2009). “Fuzzy concrete bridge deck condition rating method for practical bridge management system.” Expert Syst. Appl., 36(10), 12077–12085.
Tarussov, A., Vandry, M., and De La Haza, A. (2013). “Condition assessment of concrete structures using a new analysis method: Ground-penetrating radar computer-assisted visual interpretation.” J. Constr. Build. Mater., 38, 1246–1254.
Tee, A. B. (1988). “The application of fuzzy mathematics to bridge condition assessment.” Ph.D thesis, Purdue Univ., West Lafayette, IN.
Thompson, P. D, and Shepard, R. W. (2000). “AASHTO commonly-recognized bridge elements, successful applications and lessons learned.” National Workshop on Commonly Recognized Measures for Maintenance.
Valliappan, S., and Pham, T. D. (1993). “Constructing the membership function of a fuzzy set with objective and subjective information.” Comput. -Aided Civ. Infrastr. Eng., 8(1), 1–8.
Yan, J. M., and Vairavamoorthy, K. (2003). “Fuzzy approach for pipe condition assessment.” Int. Conf. on Pipeline Engineering and Construction, ASCE, Reston, VA, 466–476.
Yang, C. C., and Bose, N. K. (2006). “Generating fuzzy membership function with self-organizing feature map.” Pattern Recognit. Lett., 27(5), 356–365.
Yang, T., Ignizio, J. P., and Kim, H. J. (1991). “Fuzzy programming with nonlinear membership functions: Piecewise linear approximation.” Fuzzy Sets Syst., 41(1), 39–53.
Yao, I. (1980). “Damage assessment of existing structures.” J. Eng. Mech. Div., 106(4), 785–799.
Zadeh, L. A. (1965). “Fuzzy sets.” Inform. Control, 8(3), 338–353.
Zhao, Z., and Chen, C. (2002). “A fuzzy system for concrete bridge damage diagnosis.” Comput. Struct., 80(7–8), 629–641.
Zhou, Y., Vairavamoorthy, K., and Grimshaw, F. (2009). “Development of a fuzzy based pipe condition assessment model using PROMETHEE.” Proc., World Environmental and Water Resources Congress, ASCE, Reston, VA, 4809–4818.
Information & Authors
Information
Published In
Journal of Performance of Constructed Facilities
Volume 30 • Issue 4 • August 2016
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Jan 17, 2015
Accepted: Jun 17, 2015
Published online: Jul 30, 2015
Discussion open until: Dec 30, 2015
Published in print: Aug 1, 2016
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.