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dc.contributor.authorYuan Ma
dc.contributor.authorYingcheng Luan
dc.contributor.authorYang Zhang
dc.contributor.authorTao Ma
dc.date.accessioned2023-11-28T00:08:06Z
dc.date.available2023-11-28T00:08:06Z
dc.date.issued8/30/2023 12:00:00 AM
dc.date.issued2023-08-30
dc.identifier.otherJPEODX.PVENG-1419.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4294074
dc.description.abstractTo improve the efficiency and reliability of intelligent compaction technology, there is a need to evaluate the influencing factors during the compaction process. However, available research is limited, especially in terms of studies based on the dynamic theory. In this paper, the intelligent compaction process is divided into two stages: the compaction process stage, and the compaction completion stage. By establishing dynamic models for different compaction stages, the existing intelligent compaction dynamic model is modified to achieve refined modeling of the intelligent compaction process. The influencing weight of compacting parameters on intelligent compaction quality was analyzed by designing controlled tests. From the results of this study, it was found that roller weight affects the static compaction depth, whereas vibration force amplitude and frequency dominantly affect the amplitude of displacement period changes during compaction but are not predominant influences of the static compaction depth. The influence proportions of roller weight, vibration force amplitude, and vibration frequency on the final compaction quality were 82.62%, 4.92%, and 12.46%, respectively. In addition, a larger-tonnage vibratory roller and a larger vibration model with low frequency and high vibration force amplitude are suggested for compaction roadworks if rapid subgrade compaction is required. The research in this paper provides theoretical support for intelligent compaction technology so that intelligent compaction will become more applicable in practical engineering.
dc.publisherASCE
dc.titleInvestigation of Compacting Parameters on Intelligent Compaction Quality Based on Dynamic Model
dc.typeJournal Article
dc.journal.volume149
dc.journal.issue4
dc.journal.titleJournal of Transportation Engineering, Part B: Pavements
dc.identifier.doi10.1061/JPEODX.PVENG-1419
dc.journal.fristpage04023027-1
dc.journal.lastpage04023027-9
dc.page9
dc.treeJournal of Transportation Engineering, Part B: Pavements:;2023:;Volume ( 149 ):;issue: 004
dc.contenttypeFulltext


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