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International Journal of Pavement Engineering Volume 10, 2009 - Issue 3
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Original Articles

Evaluation of international roughness index for asphalt overlays placed over cracked and seated concrete pavements

A.M. Rahim CalPoly State University, CEENVE, San Luis Obispo, CA, USACorrespondence[email protected]
,
Gregg Fiegel CalPoly State University, CEENVE, San Luis Obispo, CA, USAView further author information
,
Khalid Ghuzlan Caltrans Division of Research and Innovation, Office of Research and Innovation, Sacramento, CA, USAView further author information
&
Dan Khumann CalPoly State University, CEENVE, San Luis Obispo, CA, USAView further author information
Pages 201-207 | Received 20 Dec 2007, Accepted 12 Jul 2008, Published online: 13 May 2009

Citations (11)

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Read on this site (4)

Mosbeh R. Kaloop, Sherif M. El-Badawy, Jungkyu Ahn, Hyoung-Bo Sim, Jong Wan Hu & Ragaa T. Abd El-Hakim. (2022) A hybrid wavelet-optimally-pruned extreme learning machine model for the estimation of international roughness index of rigid pavements. International Journal of Pavement Engineering 23:3, pages 862-876.
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Mohammad Abdullah Nur, Mohammad Jamal Khattak, Mohammad Reza-Ul-Karim Bhuyan & Kevin Gaspard. (2021) Cracking models for HMA overlay treatment of composite pavements in Louisiana. International Journal of Pavement Engineering 22:14, pages 1821-1832.
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Ahmad Alhasan, David J. White & Kris De Brabanter. (2017) Spatial pavement roughness from stationary laser scanning. International Journal of Pavement Engineering 18:1, pages 83-96.
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Mohammad Jamal Khattak, Mohammad Abdullah Nur, Mohammad Reza-Ul-Karim Bhuyan & Kevin Gaspard. (2014) International roughness index models for HMA overlay treatment of flexible and composite pavements. International Journal of Pavement Engineering 15:4, pages 334-344.
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Articles from other publishers (7)

Amany M. Suliman, Ahmed M. Awed, Ragaa T. Abd El-Hakim & Sherif M. El-Badawy. (2023) International Roughness Index Prediction for Jointed Plain Concrete Pavements Using Regression and Machine Learning Techniques. Transportation Research Record: Journal of the Transportation Research Board.
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Abdulgazi Gedik. (2023) A Retrospective Study Quantifying the Effects of Mixture Design and Constituent Properties on Asphalt Pavement Roughness. Journal of Materials in Civil Engineering 35:1.
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Wei Li, Ju Huyan, Liyang Xiao, Susan Tighe & Lili Pei. (2019) International roughness index prediction based on multigranularity fuzzy time series and particle swarm optimization. Expert Systems with Applications: X 2, pages 100006.
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Aioub H. Guha & Gabriel J. Assaf. 2019. Testing and Characterization of Asphalt Materials and Pavement Structures. Testing and Characterization of Asphalt Materials and Pavement Structures 136 150 .
Panos Georgiou, Christina Plati & Andreas Loizos. (2018) Soft Computing Models to Predict Pavement Roughness: A Comparative Study. Advances in Civil Engineering 2018, pages 1-8.
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Francisco Dalla RosaLitao LiuNasir G. Gharaibeh. (2017) IRI Prediction Model for Use in Network-Level Pavement Management Systems. Journal of Transportation Engineering, Part B: Pavements 143:1.
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Ellie (Elham) H. FiniMahour Mellat-Parast. (2012) Effect of Pavement Type on Overlay Roughness Progression. Journal of Transportation Engineering 138:12, pages 1558-1562.
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