离散元素模型的实时优化,用于在中尺度上研究青混合物的紧缩特性
Xue Wang1, Zifang Wang2, Xuanye Luo1
1School of Highway, Chang'an University, Xi'an 710064, China.
Sensors (Basel, Switzerland)
|February 13, 2025
概括
这项研究优化了使用SmartKli传感器数据对青混合物紧缩的离散元素建模 (DEM). 校准模型通过分析旋转压缩过程中的粒子旋转来准确预测中等尺度的压缩行为.
科学领域:
- 土木工程 土木工程是指土木工程.
- 材料科学 材料科学 材料科学
- 计算力学 计算力学 计算力学
背景情况:
- 了解中等尺度的青混合物压缩对于提高路面质量至关重要.
- 离散元件建模 (DEM) 是研究青压缩中的粒子尺度现象的强大工具.
- 提高DEM模拟精度和青压缩的计算效率仍然是一个挑战.
研究的目的:
- 建立和优化青混合物旋转压缩的DEM模型.
- 将实时实验室SmartKli传感数据集成到DEM模型校准中.
- 为了研究压缩过程中的粒子旋转特征.
主要方法:
- 实现了卡尔曼波器,用于实时数据融合和DEM模型校准.
- 在Superpave Gyratory Compaction (SGC) 测试和DEM模拟期间,在样本中使用了两个SmartKli传感器.
- 分析了粒子旋转特征在中等尺度.
主要成果:
- 青混合物的上层显示出比下层更高的压缩.
- 校准的DEM模型粒子旋转与SmartKli传感数据密切匹配.
- 观察到SmartKli和粗聚合物颗粒的相对旋转趋势有所改善.
结论:
- 经过SmartKli数据校准的优化DEM模型准确地表示了青混合物的紧缩.
- 智能Kli模拟球有效地预测了周围粗聚合物的旋转行为.
- 中尺度动力学反应为青混合物紧缩特征提供了可靠的见解.
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