Technical Papers
Sep 24, 2020

Effects of Quality Control Parameters on In-Service Performance of Flexible Pavements

Publication: Journal of Materials in Civil Engineering
Volume 32, Issue 12

Abstract

This study investigates the relation of quality measures of asphalt mixture properties during production and construction to long-term in-service performance of flexible pavements. Data from flexible pavement sections taken from the Long-Term Pavement Performance (LTPP) program along with the pavement sections of 30 Wisconsin projects were compiled in a single relational database to establish a georeferenced architecture that embraces the natural variability within the database. An in-depth analysis was performed on seven selected projects using two modeling programs that are based on statistical regression and mechanistic-empirical methods. The three research approaches allowed for assessing the effects of the variation in quality measures during construction and production: air void (Va); voids in mineral aggregates (VMA); and in-place density. The analysis showed that the deviation from the standard target for in-place density influences fatigue, longitudinal, and transverse cracking, as well as the International Roughness Index (IRI). The study showed the shortcomings of over-averaging pavement characteristics in the modeling of predicted in-service performance. Last, this study showed that implementing the proposed georeferenced relational database architecture within LTPP would increase the impact of this program.

Get full access to this article

View all available purchase options and get full access to this article.

Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

This paper is based on a study funded by the Wisconsin Highway Program (No. WHRP-0092-15-05). The authors are grateful for the support received from the WHRP staff. Wisconsin DOT engineers provided significant support to this study, namely Daniel Kopacz, Barry Paye, and Judith Rayan. Brett Williams and Stacy Glidden of Payne and Dolan Inc., and Ervin Dukatz of Mathy Construction Company provided vital information and data for this research effort.

References

Arabzadeh, A., and M. Guler. 2019. “Thermal fatigue behavior of asphalt concrete: A laboratory-based investigation approach.” Int. J. Fatigue 121 (Apr): 229–236. https://doi.org/10.1016/j.ijfatigue.2018.11.022.
ARA, Inc., ERES Consultants Division. 2004. Guide for mechanistic-empirical design of new and rehabilitated pavement structures: Appendix GG-1: Calibration of permanent deformation models for flexible pavements. Washington, DC: Transportation Research Board National Research Council.
ASTM. 2011. Standard practice for roads and parking lots pavement condition index surveys. ASTM D6433. West Conshohocken, PA: ASTM.
Bahia, H., H. Tabatabaee, and A. Faheem. 2013. Field evaluation of Wisconsin modified binder selection guidelines—Phase II. Madison, MI: Wisconsin Highway Research Program Project, Univ. of Wisconsin Madison.
Bianchini, A., and P. Bandini. 2010. “Prediction of pavement performance through neuro-fuzzy reasoning.” Comput.-Aided Civ. Infrastruct. Eng. 25 (1): 39–54. https://doi.org/10.1111/j.1467-8667.2009.00615.x.
Brown, E. R., P. S. Kandhal, and J. Zhang. 2001. Performance testing for hot mix asphalt. Auburn, AL: National Center for Asphalt Technology.
Buddhavarapu, P., S. Andre, P. Jorge, and Z. G. Wei Fan. 2014. Revised pay adjustment factors for HMA and concrete pavements (FHWA 0-6675-1). Austin, TX: Center for Transportation Research, Univ. of Texas at Austin.
Buttlar, W. G., and M. Harrell. 2000. Development of end-result and performance-related specifications for asphalt pavement construction in Illinois. Urbana, IL: Univ. of Illinois.
Choi, J. H., T. M. Adams, and H. U. Bahia. 2004. “Pavement roughness modeling using back-propagation neural networks.” Comput.-Aided Civ. Infrastruct. Eng. 19 (4): 295–303. https://doi.org/10.1111/j.1467-8667.2004.00356.x.
Crovetti, J. A., and K. T. Hall. 2012. Local calibration of the mechanistic empirical design software for Wisconsin. Madison, WI: Wisconsin DOT Highway Research Program.
Dong, Q., and B. Huang. 2014. “Evaluation of influence factors on crack initiation of LTPP resurfaced-asphalt pavements using parametric survival analysis.” J. Perform. Constr. Facil. 28 (2): 412–421. https://doi.org/10.1061/(ASCE)CF.1943-5509.0000409.
Faheem, A., A. Hosseini, H. H. Titi, and S. Schwandt. 2018. Evaluation of WisDOT quality management program (QMP) activities and impacts on pavement performance. Madison, WI: Wisconsin Highway Research Program.
Fathi, A., M. Mazari, M. Saghafi, A. Hosseini, and S. Kumar. 2019. “Parametric study of pavement deterioration using machine learning algorithms.” In Airfield and highway pavements 2019: Innovation and sustainability in highway and airfield pavement technology, 31–41. Reston, VA: ASCE.
Hand, A. J., J. L. Stiady, T. D. White, A. S. Noureldin, and K. Galal. 2007. “Gradation effects on hot-mix asphalt performance.” Transp. Res. Rec. 1767 (1): 152–157. https://doi.org/10.3141/1767-19.
Hattie, J., H. W. Marsh, J. T. Neill, and G. E. Richards. 1997. “Adventure education and outward bound: Out-of-class experiences that make a lasting difference.” Rev. Educ. Res. 67 (1): 43–87. https://doi.org/10.3102/00346543067001043.
Hosseini, A., A. Faheem, H. Titi, and M. Alsalihi. 2019a. “Evaluation of influence of production and construction quality control measures on asphalt pavements long-term performance.” In Airfield and highway pavements 2019: Innovation and sustainability in highway and airfield pavement technology, 142. Reston, VA: ASCE.
Hosseini, A., A. Faheem, H. Titi, and S. Schwandt. 2019b. “Developing a geo-relational framework for assessing influence of quality control data on long-term performance of flexible pavements.” In Proc., Conf. of Transportation Research Board 98th Annual Meeting. Washington, DC: Transportation Research Board.
Jackson, N., and J. Puccinelli. 2006. Long-term pavement performance program (LTPP) data analysis support: National pooled fund study TPF-5 (013). Effects of multiple freeze cycles and deep frost penetration on pavement performance and cost. McLean, VA: Turner-Fairbank Highway Research Center.
Leverett, B. C. 2008. “Effects of incentive/disincentive program on pavement performance.” M.Sc. thesis, Dept. of Civil Engineering, Michigan State Univ.
Majidifard, H., B. Jahangiri, W. G. Buttlar, and A. H. Alavi. 2019. “New machine learning-based prediction models for fracture energy of asphalt mixtures.” Meas.: J. Int. Meas. Confederation 135 (Mar): 438–451. https://doi.org/10.1016/j.measurement.2018.11.081.
Morian, N., E. Y. Hajj, and P. E. Sebaaly. 2013. “Significance of mixture parameters on binder aging in hot-mix asphalt mixtures.” Transp. Res. Rec. 2370 (1): 116–127. https://doi.org/10.3141/2370-15.
NCHRP (National Cooperative Highway Research Program). 2011. A performance-related specification for hot-mixed asphalt. Washington, DC: Transportation Research Board.
NOAA (National Oceanic and Atmospheric Administration). 2020. “Climate data online.” Accessed November 5, 2019. https://www.ncdc.noaa.gov/cdo-web/.
Notani, M. A., F. Moghadas Nejad, A. Khodaii, and P. Hajikarimi. 2018. “Evaluating fatigue resistance of toner-modified asphalt binders using the linear amplitude sweep test.” Road Mater. Pavement Des. 20 (8): 1927–1940. https://doi.org/10.1080/14680629.2018.1474792.
Perera, R. W., and S. D. Kohn. 2002. NCHRP web document 42: Issues in pavement smoothness: A summary report. Washington, DC: Transportation Research Board of the National Academies.
Robert, F. L., P. S. Kandhal, E. R. Brown, Y. L. Dah, and T. Kennedy. 1996. “Hot mix asphalt—Minerals, mixture design and construction.” In Hot mix asphalt materials, mixture design, and construction, 448–461. Lanham, MD: NAPA Research and Education Foundation.
Shen, S., W. Zhang, L. Shen, and H. Huang. 2016. “A statistical based framework for predicting field cracking performance of asphalt pavements: Application to top-down cracking prediction.” Constr. Build. Mater. 116 (Jul): 226–234. https://doi.org/10.1016/j.conbuildmat.2016.04.148.
Siddharthan, R. V., N. Krishnamenon, M. El-Mously, and P. E. Sebaaly. 2002. “Validation of a pavement response model using full-scale field tests.” Int. J. Pavement Eng. 3 (2): 85–93. https://doi.org/10.1080/10298430290030595.
Smit, A. D. F., and J. A. Prozzi. 2009. Developing a sustainable flexible pavement database in Texas. Austin, TX: Center for Transportation Research.
Terzi, S. 2013. “Modeling for pavement roughness using the ANFIS approach.” Adv. Eng. Softw. 57 (Mar): 59–64. https://doi.org/10.1016/j.advengsoft.2012.11.013.
Uzan, J. 2018. “Advancing the design and construction quality control of flexible pavements.” Int. J. Pavement Eng. 19 (2): 164–173. https://doi.org/10.1080/10298436.2016.1172711.
Yang, J., J. Lu, M. Gunaratne, and B. Dietrich. 2007. “Modeling crack deterioration of flexible pavements: Comparison of recurrent Markov chains and artificial neural networks.” Transp. Res. Rec. 1974 (1): 18–25. https://doi.org/10.1177/0361198106197400103.
Zhao, W. 2011. “The effects of fundamental mixture parameters on hot-mix asphalt performance properties.” Ph.D. dissertation, Dept. of Civil Engineering, Clemson Univ.
Ziari, H., J. Sobhani, J. Ayoubinejad, and T. Hartmann. 2016. “Analysing the accuracy of pavement performance models in the short and long terms: GMDH and ANFIS methods.” Road Mater. Pavement Des. 17 (3): 619–637. https://doi.org/10.1080/14680629.2015.1108218.

Information & Authors

Information

Published In

Go to Journal of Materials in Civil Engineering
Journal of Materials in Civil Engineering
Volume 32Issue 12December 2020

History

Received: May 7, 2019
Accepted: Dec 27, 2019
Published online: Sep 24, 2020
Published in print: Dec 1, 2020
Discussion open until: Feb 24, 2021

Permissions

Request permissions for this article.

Authors

Affiliations

Pavement and Geotechnical Engineer, Terracon Consultants, Inc., 4685 South Ash Ave., Suite H-4, Tempe, AZ 85282. ORCID: https://orcid.org/0000-0002-7756-9209. Email: [email protected]
Assistant Professor, Dept. of Civil and Environmental Engineering, Temple Univ., 1947 N. 12th St., Philadelphia, PA 19122 (corresponding author). ORCID: https://orcid.org/0000-0002-2571-1648. Email: [email protected]
H. Titi, A.M.ASCE [email protected]
Associate Professor, Dept. of Civil and Environmental Engineering, Univ. of Wisconsin-Milwaukee, 3200 N. Cramer St., Milwaukee, WI 53211. Email: [email protected]

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.

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share