Open-graded aggregates (OGAs) are free-draining materials often used as the base layer of permeable pavements to allow the infiltration or drainage of stormwater. Despite their widespread use, the compaction quality of OGA base layers has not been specified properly. The currently used density-based compaction quality control (QC) has limitations; obtaining the field density and maximum dry density of OGAs by typical methods is challenging, due to their unique properties. To overcome these limitations, modulus-based compaction QC can be used as an alternative. In this study, five different OGAs were chosen and compacted into a specially built soil chamber to measure their densities. The light weight deflectometer (LWD) and the soil stiffness gauge (SSG) were used to evaluate the modulus of the compacted OGAs. The vibratory hammer compaction test was conducted to obtain the maximum dry density of the aggregates. Through these tests, the relationship between the modulus of the compacted aggregates and the relative density was obtained, and efforts to find a modulus range that ensures proper compaction were made. It was found that the LWD and SSG are valid and reliable devices for monitoring the modulus change of OGAs due to compaction.
The impermeable cover in urban area has been growing due to rapid urbanization, which prevents stormwater from being naturally infiltrated into the ground. There is a higher chance of flooding in urban area covered with conventional concretes and asphalts. The permeable pavement is one of Low-Impact Development (LID) technologies that can reduce surface runoff and water pollution by allowing stormwater into pavement systems. Unlike traditional pavements, permeable pavement bases employ open-graded aggregates (OGAs) with highly uniform particle sizes. There is very little information on the engineering properties of compacted OGAs. In this study, the moduli of open-graded aggregates under various compaction energies are investigated based on the Plate Load Test (PLT) and Light-Weight Deflectometer (LWD). Artificial Neural Network (ANN) and Linear Regression (LR) models are employed for estimation of the moduli of the aggregates based on the material type and level of compaction. Overall, the moduli from PLT and LWD steeply increase until the number of roller passes reaches 4, and they gradually increase until the number of roller passes becomes 8. A set of simple linear equations are proposed to evaluate the moduli of open-graded aggregates from PLT and LWD based on the material type and the number of roller passes.
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