Transportation Research Congress 2017
Pavement Performance Index Differences among General Pavement, Bridge Deck Pavement, and Tunnel Pavement Based on Inspection Data
Publication: Transportation Research Congress 2017: Sustainable, Smart, and Resilient Transportation
ABSTRACT
The performance of road pavement is the key factor in determining the scheme and expenditure of maintenance. The historical pavement quality index (PQI) of asphalt pavement, taken from six expressways that were over five years old, were analyzed by comparative analysis of the absolute values and the different values of the PQI. The analysis of absolute values demonstrated that the general road pavement had the same variation tendency with the 300–500 m and 500–1000 m bridge decks. The difference of the PQI was within 1. A completely different tendency was present within the big bridge decks, where a maximum PQI difference 3.54 was found. The same variation tendency was found within the short and the medium tunnel pavement, where the PQI was within 1.5. The long tunnel pavement was far higher, with the maximum PQI difference being 7.31. The analysis of different values showed that as the bridge length and the tunnel length increase, the PQI difference of general road pavement and bridge decks varied from a general difference to a large difference. The PQI difference of the general road pavement and the tunnel pavement shifted from a general difference to a significant difference. The results of the study on the PQI absolute values and different values of the three types of pavement showed that the big bridge decks, long tunnel pavement, and especially long tunnel pavements need to be treated differently than other pavements when forming a pavement routine maintenance scheme, and estimating the maintenance quantity, and the calculation of expenditures. This would improve the accuracy of the routine maintenance budgets.
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ACKNOWLEDGMENT
The work described herein is part of a research project on“Research on the annual consumption index of routine maintenance of highway” funded by Shaanxi Provincial Department of Transportation under Grant no. 16-34k and Shaanxi Provincial Communications Group Corporation under Grant no.16-16k and the Central University Basic Research Business Funding Project under Grant no.300102218112 with data support from Shaanxi Provincial Communications Group Corporation. Their support is gratefully acknowledged.
REFERENCES
Amirhossein, Norouzi, Richard, “Application of viscoelastic continuum damage approach to predict fatigue performance of Binzhou perpetual pavements”, Journal of Traffic & Transportation Engineering, vol.3, no. 2, pp 104-115, 2016.
Cao, YH, Liu, JH, “Pavement preventive maintenance decision-making in the period of road design”, International Conference on Transportation Infrastructure and Materials (ICTIM 2016) ISBN: 978-1-60595-367-0.
Giuseppe Loprencipe, Pablo Zoccali. Use of generated artificial road profiles in road roughness evaluation[J]. Journal of Modern Transportation, 2017.
Halil Ceylan, Mustafa Birkan Bayrak, Kasthurirangan Gopalakrishnan. Neural Networks Applications in Pavement Engineering:A Recent Survey[J]. International Journal of Pavement Research and Technology, 2014.
Hong F, Prozzi JA, Prozzi J, “A new approach for allocating highway costs”, Journal of the Transportation Research Forum, vol.46, no.2, pp 5-19, 2007.
Lai, JX, Fan, HB, Chen, JX, et al., “Blasting vibration monitoring of undercrossing railway tunnel using wireless sensor network”, International Journal of Distributed Sensor Networks, vol. 2015, Article ID 703980, 7 pages, 2015.
Lai, JX, Mao, S, Qiu, JL, et al., “Investigation progresses and applications of fractional derivative model in geotechnical engineering”, Mathematical Problems in Engineering, vol. 2016, Article ID 9183296, 15 pages, 2016.
Lai, JX, Qiu, JL, Fan, HB, et al., “Fiber bragg grating sensors-based in situ monitoring and safety assessment of loess tunnel”, Journal of Sensors, vol. 2016, Article ID 8658290, 10 pages,2016.
Lai, JX, Wang, KY, Qiu, JL, et al., “Vibration response characteristics of the cross tunnel structure”, Shock and Vibration, vol. 2016, Article ID 9524206, 16 pages,2016.
Lai, JX, Wang, XL, Qiu, JL, et al., “A state-of-the-art review of sustainable energy based freeze proof technology for cold-region tunnels in China”, Renewable and Sustainable Energy Reviews, 2017. in press.
Lei, J, Wang, XC, Wang, L, “Pavement performance prediction based on self-adaptive grey model”. Control & Automation, vol 26. no. 5, pp 28-29,2010.
Lu CJ, Research on pavement maintenance technology and pavement condition evaluation of Expressway asphalt pavement [Ms.thesis], South China University of Technology, Guangzhou, China, 2016.
Mao, M, Yu, X. A Method of Expressway Pavement Performance Prediction[C]. International Conference on Transportation Engineering, pp 433-438, 2009.
Mehran Mazari, Daniel D. Rodriguez. Prediction of pavement roughness using a hybrid gene expression programming-neural network technique[J]. Journal of Traffic and Transactions Engineering(English Edition), 2016.
Ministry of Transport of the People's Republic of China, JTG D-2004. Code for design of road tunnel[S]. Beijing: China Communication Press, 2004.
Ministry of Transport of the People's Republic of China, JTG D40-2011. Specifications for design of highway cement concrete pavement[S]. Beijing: China Communication Press, 2011.
Ministry of Transport of the People's Republic of China, JTG D60-2015. General specifications for design of highway bridges and culverts[S]. Beijing: China Communication Press, 2015.
Ministry of Transport of the People's Republic of China, JTJ014-97 Specifications for design of highway asphalt pavement[S]. Beijing: China Communication Press. 2006.
Mofreh Saleh. Prediction of Rigid Pavement Responses under Axle Loads Using Artificial Neural Network[J]. International Journal of Pavement Research and Technology, 2015.
Nueraihemaitijiang Abulizi, Akira Kawamura, Kazuya Tomiyama, Shun Fujita, “Measuring and evaluating of road roughness conditions with a compact road profiler and ArcGIS”, Journal of Traffic and Transportation Engineering (English Edition), vol. 3, no. 5, pp 398-411,2016.
Ryu, S W, Park, J Y, Kim, H B, et al., “ Behavior and performance evaluation of a concrete pavement considering the temperature condition in a tunnel”, International Journal of Highway Engineering, vol. 18, no. 2, pp 11-18, 2016.
S. Mathavan, M. M. Rahman, M. Stonecliffe-Jones. Unsupervised Artificial Neural Network for Efficient Mapping of Doweled Concrete Pavement Joints Condition[J]. International Journal of Pavement Research and Technology, 2014.
Shaanxi Provincial Department of Transportation traffic engineering ration stations.Highway maintenance engineering budget quota in Shaanxi province[S]. Beijing: China Communication Press, 2012.
Shi, CX, Guo, ZY, “Mechanical properties of asphalt pavement structure in highway tunnel”, Journal of Shanghai Jiaotong University, vol.13, no.2, pp 206-210,2008.
Ya-Bin, HE, Tong, SJ, Wen, J, “ The stress analysis of continuous concrete bridge deck pavement”, Technology & Economy in Areas of Communications, vol.11, no.4, pp 39-41, 2009.
Yang, K, Analysis and experimental study on the mechanical properties of asphalt concrete bridge deck pavement [Ph.D. thesis], Chang'an University, Xi’an, China, 2015.
Zhang, L, Aspahlt pavement performance predication and analysis of selecting preventive maintenance schemes [Ms.thesis], South China University of Technology, Guangzhou, China, 2012.
Information & Authors
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Published In
Transportation Research Congress 2017: Sustainable, Smart, and Resilient Transportation
Pages: 174 - 188
Editors: Linbing Wang, Ph.D., Virginia Polytechnic University, Hongren Gong, Ph.D., University of Tennessee, Knoxville, and Baoshan Huang, Ph.D., University of Tennessee, Knoxville
ISBN (Online): 978-0-7844-8251-3
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© 2019 American Society of Civil Engineers.
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Published online: Oct 3, 2019
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