Probabilistic Modeling of Performance-Related Pay Adjustment for In-Place Air-Void Contents of Asphalt Pavements
Publication: Journal of Infrastructure Systems
Volume 23, Issue 2
Abstract
There is a growing interest in development of performance-related specification for pavement construction. This paper presents the development of performance-related pay adjustments with probabilistic models of pavement performance, with application to in-place air-void contents of asphalt pavements. Quality-assurance data were collected from construction database and pavement-performance data were extracted from pavement-management system. Performance-related pay adjustments were formulated using lifecycle cost analysis considering two different scenarios of maintenance strategy and the variations of pavement overlay life. The results show that the Bayesian approach with Markov-chain Monte Carlo methods can capture unobserved variations in pavement-condition data and relate the quality measure of in-place air-void contents to the expected pavement life with high goodness of fit. The analysis results indicate that there may be significant variations in the model parameters for estimating the expected pavement life due to deviations in acceptance-quality characteristics. This implies that addressing the variations in pavement-performance modeling is a critical issue in deriving performance-related pay adjustments. The probabilistic modeling results facilitate considering the level of reliability in decision making of pay adjustments.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The authors would like to acknowledge the financial support provided by the New Jersey Department of Transportation. The contents do not necessarily reflect the official views or policies of the New Jersey Department of Transportation. This paper does not constitute a standard, specification, or regulation.
References
Apuzzo, M., and Nicolosi, V. (2010). “A new methodology for stochastic modelling of pay factors in hot-mix asphalt pavements.” Road Mater. Pavement Des., 11(Suppl 1), 559–585.
Archilla, A. R. (2006). “Repeated measurement data analysis in pavement deterioration modeling.” J. Infrastruct. Syst., 163–173.
Choi, J., and Bahia, H. U. (2004). “Life cycle cost analysis-embedded Monte Carlo approach for modeling pay adjustment at state departments of transportation.” Transp. Res. Rec., 1900, 86–93.
Epps, J. A. (2002). “Recommended performance-related specification for hot-mix asphalt construction: Results of the WesTrack project.”, Transportation Research Board and National Research Council, Washington, DC.
Gao, L., Aguiar-Moya, J. P., and Zhang, Z. M. (2012). “Analysis of heterogeneity in modeling of pavement fatigue cracking.” J. Comput. Civ. Eng., 37–43.
Geweke, J. (1991). “Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments.”, Federal Reserve Bank of Minneapolis, Minneapolis.
Graveen, C., et al. (2009). “Performance-related specifications (PRS) for concrete pavements in Indiana, volume 1: Executive summary.”, Indiana Dept. of Transportation, West Lafayette, IN.
Hong, F., and Prozzi, J. (2006). “Estimation of pavement performance deterioration using Bayesian approach.” J. Infrastruct. Syst., 77–86.
Hughes, C. S. (2005). “State construction quality assurance programs: A synthesis of highway practice.”, Transportation Research Board, Washington, DC.
Jackson, N. C., Deighton, R., and Huft, D. L. (1996). “Development of pavement performance curves for individual distress indexes in South Dakota based on expert opinion.” Transp. Res. Rec., 1524, 130–136.
Johnson, N. L., Samuel, K., and Balakrishnan, N. (1994). Lognormal distributions, continuous univariate distributions, Wiley, New York.
Karunarathna, W. (2013). “Bridge deterioration modeling by Markov chain Monte Carlo (MCMC) simulation method.” Proc., 8th World Congress on Engineering Asset Management & 3rd Int. Conf. on Utility Management & Safety, International Society of Engineering Asset Management (ISEAM), Hong Kong, 1–13.
Kobayashi, K., Kaito, K., and Lethanh, N. (2012). “A statistical deterioration forecasting method using hidden Markov model with measurement errors.” Transp. Res. Part B, 46(4), 544–561.
Kobayashi, K., Kaito, K., and Lethanh, N. (2014). “A competing Markov model for prediction of pavement cracking process.” Transp. Res., 68, 345–362.
Linden, R. N., Mahoney, J. P., and Jackson, N. C. (1989). “Effect of compaction on asphalt concrete performance.” Transp. Res. Rec., 1217, 38–45.
Liu, L., and Gharaibeh, N. G. (2014). “Bayesian model for predicting the performance of pavements treated with thin hot-mix asphalt overlays.” Transp. Res. Rec., 2431, 33–41.
Liu, L., and Gharaibeh, N. G. (2015). “Simulation-based methodology for developing performance-related specifications for pavement preservation treatments.” J. Transp. Eng., 04015011.
Lytton, R. L. (1969). “Concepts of pavement performance prediction and modeling.” Proc., 2nd North American Conf. on Managing Pavements, Vol. 2, Ontario Ministry of Transportation, Toronto, ON.
Mensching, D. J., McCarthy, L. M., Mehta, Y. A., Albert, J., and Moulthrop, J. (2013). “Exploring pay factors based on hot mix asphalt performance using quality-related specification software.” Road Mater. Pavement Des., 14(4), 792–809.
Mills, L., Attoh-Okine, N., and McNeil, S. (2012). “Hierarchical Markov chain Monte Carlo simulation for modeling transverse cracks in highway pavements.” J. Transp. Eng., 700–705.
NJDOT (New Jersey Dept. of Transportation). (2007). Standard specifications for road and bridge construction, Trenton, NJ.
Ntzoufras, I. (2009). Bayesian modeling using WinBUGS, Wiley, NJ.
Stampley, B. E., Smith, R. E., Scullion, T., and Miller, B. (1995). “Pavement management information system concepts, equations, and analysis of pavements.”, Texas Transportation Institute, Texas A&M Univ. System, College Station, TX.
Stantec Consulting. (2006). “Development and implementation of Arizona Department of Transportation (ADOT) pavement management system.”, Charlotte, NC.
Weed, R. M. (2001). “Derivation of equation for cost of premature pavement failure.” Transp. Res. Rec., 1761, 93–96.
Weed, R. M. (2006). “Mathematical modeling procedures for performance-related specifications.” Transp. Res. Rec., 1946, 63–70.
Whiteley, L., Tighe, S., and Zhang, Z. (2005). “Incorporating variability into pavement performance, life-cycle cost analysis, and performance-based specification pay factors.” Transp. Res. Rec., 1940, 13–20.
WinBug version 1.4 [Computer software]. MRC Biostatistics Unit, Cambridge, U.K.
Zaghloul, S., Helali, K., Ahmed, Z., Sauber, R., and Jumikis, A. (2006). “Cash flow control of New Jersey interstate needs.” Transp. Res. Rec., 1974, 54–62.
Information & Authors
Information
Published In
Journal of Infrastructure Systems
Volume 23 • Issue 2 • June 2017
Copyright
© 2016 American Society of Civil Engineers.
History
Received: Nov 25, 2015
Accepted: Jul 5, 2016
Published online: Aug 19, 2016
Discussion open until: Jan 19, 2017
Published in print: Jun 1, 2017
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.