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contributor authorWei Hu
contributor authorXiang Shu
contributor authorXiaoyang Jia
contributor authorBaoshan Huang
date accessioned2017-12-16T09:18:15Z
date available2017-12-16T09:18:15Z
date issued2017
identifier other%28ASCE%29CO.1943-7862.0001361.pdf
identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4241166
description abstractIntelligent compaction (IC) technology provides an innovative way for continuously and instantaneously evaluating asphalt compaction quality. However, there is a lack of well-accepted standard as to what IC parameters should be used and how they should be interpreted during the compaction. In this study, by analyzing IC parameters in six asphalt resurfacing projects in Tennessee, the feasibility of adopting IC parameters in IC specifications for the asphalt compaction quality was evaluated. Comprehensive laboratory tests were performed on the field cores, including bulk specific gravity, permeability, and indirect tensile (IDT) strength. Results indicated that there is linear relationship among the laboratory test results. Although there were no significant relationships between the final compaction meter value (CMV) and the core results, the difference in 1/CMV between two passes in one project showed significant correlations with the laboratory results. Other IC parameters, especially the starting surface temperature of the breakdown roller, also had a strong correlation with the core density. Based on the results from this study, it is recommended that three IC parameters—the difference in 1/CMV, the starting surface temperature of compaction (>110°C), and the total number of passes (>2 passes)—be adopted for evaluating the compaction quality of the resurfacing asphalt.
publisherAmerican Society of Civil Engineers
titleRecommendations on Intelligent Compaction Parameters for Asphalt Resurfacing Quality Evaluation
typeJournal Paper
journal volume143
journal issue9
journal titleJournal of Construction Engineering and Management
identifier doi10.1061/(ASCE)CO.1943-7862.0001361
treeJournal of Construction Engineering and Management:;2017:;Volume ( 143 ):;issue: 009
contenttypeFulltext


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