用实验结果和机器学习模型评估用低密度聚乙烯和高密度聚乙烯修改的青混合物
Muhammad Junaid1, Chaozhe Jiang2, Uneb Gazder3
1School of Transportation and Logistics, Southwest Jiaotong University (SWJTU), Chengdu, China.
Scientific reports
|October 19, 2024
概括
像低密度聚乙烯 (LDPE) 和高密度聚乙烯 (HDPE) 这样的废塑料可以为可持续的高速公路增强青混凝土 (AC). 经过修改的交流混合物表现出更好的耐永久变形和更高的动态模量 (DM).
科学领域:
- 材料科学 材料科学 材料科学
- 土木工程 土木工程是指土木工程.
- 环境科学 环境科学
背景情况:
- 来自低密度聚乙烯 (LDPE) 和高密度聚乙烯 (HDPE) 的塑料废物越来越多,需要可持续的处置和再利用策略.
- 将废塑料纳入青混凝土 (AC) 混合物为开发更可持续的高速公路基础设施提供了一个有希望的途径.
研究的目的:
- 研究用LDPE和HDPE修改的交流混合物的性能.
- 为了评估这些改造的交流混合物的耐永久变形和动态模量 (DM).
- 评估各种机器学习模型对DM的预测准确度.
主要方法:
- 流量数 (FN),流量时间 (FT) 和动态模量 (DM) 测试在Superpave旋转压缩样本上进行.
- 使用了机器学习模型,包括多层感知子 (MLP),辐射基函数神经网络 (RBFNN),通用回归神经网络 (GRNN) 和支持矢量机器 (SVM).
- 模型性能使用根平均平方误差,平均相对误差和确定系数进行评估.
主要成果:
- 与对照混合物相比,LDPE和HDPE修饰的交流混合物对永久变形的耐力分别是2.07倍和1.27倍.
- 经过修改的交流混合物显示的DM值是对照混合物的2.1 (LDPE) 和1.4 (HDPE) 倍.
- 在预测DM方面,MLP模型显示了最高的准确性 (R2 = 0.98),频率是最有影响力的参数.
结论:
- 用LDPE和HDPE修改AC显著提高了对永久变形的抵抗力,并增加了动态模量.
- 机器学习,特别是MLP,是预测修改AC混合物的DM的强大工具.
- 在AC中利用废弃LDPE和HDPE为塑料废物管理提供了可持续的解决方案,并提高了路面的性能.
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