基于SmartRock监测与离散元仿真分析的沥青混合料压密行为研究
Research on Compaction Behavior of Asphalt Mixture Based on SmartRock Monitoring and Discrete Element Simulation Analysis
DOI: 10.12677/MOS.2023.125398, PDF,   
作者: 刘天运：浙江理工大学建筑工程学院，浙江 杭州
关键词: 智能颗粒；离散元；压实；运动行为；迁移规律；Smart Rock； Discrete Element； Compaction； Movement Behaviour； Migration Law
摘要: 为研究沥青混合料中粗集料在压实过程中的迁移演化规律，采用智能颗粒(SmartRock)监测设备模拟粗集料在压实过程中的运动行为，基于PFC 3D建立等尺寸沥青混合料压密模型，通过调整颗粒生成位置来探讨粗集料的迁移规律并与实际监测数据进行对比分析。结果表明：在沥青混合料中部放置智能颗粒不会对原有级配和力学性能造成明显影响，其运动响应可以较好地表征压实程度；集料的迁移行为会影响试样压实度，上层集料在压实过程中主要发生垂直方向的滚动以及竖向迁移，竖向最大迁移距离占试样总压缩高度的60.8%，致使上层试样压实均匀性不佳，水平方向的空隙率极差为2.05%；下层集料倾向于发生水平方向的转动以及侧向堆移，下层试样空隙率分布较为均匀，水平方向的空隙率极差仅为0.95%，但整体压实度低于上层。
Abstract: In order to study the migration and evolution law of coarse aggregate in asphalt mixture during compaction, SmartRock monitoring equipment is used to simulate the movement behavior of coarse aggregate during compaction. Based on PFC 3D, the compaction model of equal-size asphalt mixture is established, and the migration law of coarse aggregate is discussed by adjusting the par-ticle generation position and compared with the actual monitoring data. The results show that placing SmartRock in the middle of asphalt mixture will not have obvious influence on the original gradation and mechanical properties, and its motion response can better characterize the compac-tion degree. The migration behavior of aggregate will affect the compaction degree of the sample. The upper aggregate mainly rolls and migrates vertically during compaction, and the maximum vertical migration distance accounts for 60.8% of the total compression height of the sample, re-sulting in poor compaction uniformity of the upper sample, and the poor horizontal void ratio is 2.05%. The aggregate in the lower layer tends to rotate horizontally and move sideways, and the porosity of the lower layer samples is distributed evenly, with the horizontal porosity range of only 0.95%, but the overall compactness is lower than that of the upper layer.
文章引用：刘天运. 基于SmartRock监测与离散元仿真分析的沥青混合料压密行为研究[J]. 建模与仿真, 2023, 12(5): 4365-4378. https://doi.org/10.12677/MOS.2023.125398

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