4.5 Article

In-situ spot test measurements and ICMVs for asphalt pavement: lack of correlations and the effect of underlying support

Journal

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/10298436.2023.2198770

Keywords

Intelligent compaction; asphalt pavements; intelligent compaction measurement value; underlying support correction; phase angle; non-nuclear density gauge; lightweight deflectometer

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The main aim of this paper is to analyze and compare different intelligent compaction measurement values (ICMVs) with spot test measurements for asphalt pavement. A two-layer asphalt testbed was constructed and all ICMVs were calculated using the same accelerometer data. The analysis showed strong correlations between certain ICMVs, but none of them showed acceptable correlation with asphalt densities. A correction method for the influence of underlying support on one of the ICMVs was developed and validated.
The main aim of this paper is to analyse the performance of different intelligent compaction measurement values (ICMVs) and compare them with spot test measurements for asphalt pavement. To accomplish this, a two-layer asphalt testbed was constructed using an instrumented double-drum roller. All ICMVs [compaction meter value (CMV), compaction control value (CCV), roller-integrated stiffness (k(b)), and vibratory modulus (E-VIB)] were calculated using the same accelerometer data collected during the construction of the asphalt testbed. The analysis of ICMV data showed a strong correlation between k(b) and E-VIB, while CMV and CCV demonstrated a strong correlation only when double jump of the roller drum did not occur. Further, none of the ICMVs recorded during the last roller pass of asphalt compaction showed an acceptable correlation with asphalt densities [measured using a non-nuclear density gauge (NNDG)], mainly due to the influences of the underlying support and asphalt temperature on ICMVs. A correction method to decouple the influence of underlying support on E-VIB was developed and validated using existing data from the literature. The applicability of this method for different field scenarios was demonstrated using numerical modelling.

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