Lee Yunje, Choi Yongjin, Ahn Donghyun, Ahn Jaehun
Department of Civil and Environmental Engineering, Pusan National University, Busan 46241, Korea.
Materials (Basel). 2021 Mar 4;14(5):1199. doi: 10.3390/ma14051199.
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.
由于快速城市化，城市地区不透水覆盖物不断增加，这使得雨水无法自然渗入地下。在覆盖传统混凝土和沥青的城市地区，发生洪水的可能性更高。透水路面是低影响开发（LID）技术之一，它通过让雨水进入路面系统来减少地表径流和水污染。与传统路面不同，透水路面基层采用粒径高度均匀的开级配集料（OGAs）。关于压实OGAs工程性质的信息非常少。在本研究中，基于平板载荷试验（PLT）和轻型弯沉仪（LWD），研究了不同压实能量下开级配集料的模量。基于材料类型和压实程度，采用人工神经网络（ANN）和线性回归（LR）模型来估计集料的模量。总体而言，PLT和LWD得到的模量在碾压遍数达到4之前急剧增加，在碾压遍数达到8之前逐渐增加。提出了一组简单的线性方程，根据材料类型和碾压遍数来评估PLT和LWD得到的开级配集料的模量。
