基于多元线性回归的细粒土永久变形预测:虚拟变量

M. Khasawneh, Rabea AL-Jarazi
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引用次数: 0

摘要

-在反复的交通负荷下,了解和了解路基土(细粒土)的累积永久变形和破坏机制,对路面结构的适当设计和维修规划至关重要。换句话说,考虑到路基土对路面结构整体性能的巨大贡献,提供永久变形行为的最佳预测至关重要。本文利用拟变量多元线性回归技术建立了细粒土(a -4a和a -6a土)永久变形的预测方程。永久变形(PD)结果表明,A-4a在OMC下表现出最小的塑性变形,而A-6a在OMC湿度为2%时表现出最大的塑性变形。所得结果可用于帮助工程师表征细粒度材料。根据本研究的统计分析,永久性变形的虚拟回归并没有显著提高模型的预测能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Prediction of Permanent Deformation of Fine-Grained Soils Using Multiple Linear Regression: Dummy Variables
— Under repeated traffic loading, knowledge and understanding of cumulative permanent deformation and failure mechanisms for subgrade soils (fine-grained soils) are crucial for the proper design and maintenance planning of pavement structures. In other words, considering the great contribution of subgrade soils to the overall performance of pavement structures, it is crucial to provide the best prediction of permanent deformation behavior. This paper presents a new predictive equation for the permanent deformation of fine-grained soils (A-4a and A-6a soils) utilizing the dummy-variable multiple linear regression technique. The permanent deformation (PD) results revealed that A-4a at OMC exhibited the least plastic deformation versus the highest plastic deformation assigned to A-6a compacted at 2% wet of OMC. The results obtained could be used to help engineers in characterizing fine-grained materials. As per the statistical analysis carried out in this study, the dummy regression for permanent deformation did not greatly improve the prediction power of the model.
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