Application of Intelligent Compaction Technique in Real Time Evaluation of Compaction Level during the Construction of Subgrade

摘要

The long term performance of an asphalt pavement depends on the quality of the supportingsubgrade. Achieving a proper compaction level is, therefore, very important. Traditionally, thelevel of compaction is monitored through spot checking of moisture content and dry density atsome discrete points on the compacted subgrade. However, randomly selected points do notadequately represent the entire compacted area and could leave undetected soft spots. This paperpresents the findings of a study investigating the ability of the Intelligent Asphalt CompactionAnalyzer (IACA), developed at the University of Oklahoma, in estimating the subgrade resilientmodulus (M_r), in real-time. Field study was conducted at two different project sites. A vibratorycompactor was instrumented with the IACA and the M_r values (M_(r-IACA)) were continuouslyrecorded during the compaction of the stabilized subgrade. In the first project, IACA wasevaluated by comparing the M_(r-IACA) values with the Falling Weight Deflectometer (FWD)backcalculated subgrade modulus (M_(FWD)) (R~2 = 0.63; error = ±15%). In the second project,M_(r-IACA) values were compared with the M_r values obtained from regression models (M_(r-reg))developed based on the laboratory Mr test results (R~2 =0.63; error = ±15%). In both the projects,it was found that IACA can provide the estimates of M_r with an acceptable accuracy, in realtime.