This paper presents the results of the intelligent compaction data that were collected from various layers including subgrade soil, lime-treated subgrade, cement-treated base and flexible aggregate base layers. Sets of proof-mapping data were collected from each layer upon completion of compaction. The data was then downloaded and analyzed using a computer program. Based on the data analysis and field compaction observation, a new statistical methodology for analyzing intelligent compaction data is proposed. The method is used to assess the uniformity of soil and base compaction quality and this is successfully demonstrated through a case study. A typical normal distribution of an intelligent compaction dataset indicates that a good and uniform compaction is achieved. It is, therefore, possible to assess the compaction quality by evaluating the perfection of normal districtuion of an intelligent compaction (IC) dataset. The compaction uniformity is evaluated by a compaction uniformity index, which is defined as the ratio of the probability within the specified limits in a field compaction data distribution to the probability in a target normal distribution.


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    Title :

    Intelligent Compaction for Quality Control and Acceptance for Soil and Base Compaction through Statistical Analysis


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2018-06-06




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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