Abstract Frost heave of railway roadbed leads to track geometry degradation during the cold season, seriously threatening the safety of high-speed trains. An accurate estimation of freezing-induced deformation in subgrade aggregates is thus critical to construction and maintenance of transportation infrastructure in seasonally frozen regions. This paper proposes a practical approach to assessing the frost heave susceptibility of gravelly soils under unidirectional freezing conditions. Typical frost heave tests are first performed on gravel columns in closed and open systems. The multivariate adaptive regression splines algorithm is subsequently applied to develop a predictive model for the normalized heave of a specimen. Experimental data of freezing tests were collected from this study and available literature to compile a dataset. A randomly selected subset is used for training, while the complement of the subset is intended for testing. Relative importance analysis and analysis of variance are finally performed to examine the general and coupling effects of initial moisture content, fines, relative compaction, and stress level on the frost heave susceptibility of compacted soil. Hopefully, the developed model and comprehensive analysis of coarse fills could assist railway agencies in understanding the appropriate characterization of frost heave and provide an evaluation guideline for optimized railway roadbed.

中文翻译：

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基于多元自适应回归样条模型的砾石土冻胀敏感性评估

摘要 铁路路基冻胀导致寒冷季节轨道几何形状退化，严重威胁高铁运行安全。因此，准确估计路基集料中冻结引起的变形对于季节性冻结地区交通基础设施的建设和维护至关重要。本文提出了一种评估单向冻结条件下砾石土壤冻胀敏感性的实用方法。典型的冻胀试验首先在封闭和开放系统中的砾石柱上进行。随后应用多元自适应回归样条算法来开发样本标准化升沉的预测模型。冷冻试验的实验数据是从这项研究和现有文献中收集的，以编制数据集。随机选择的子集用于训练，而子集的补集用于测试。最后进行相对重要性分析和方差分析，考察初始含水量、细粒、相对压实和应力水平对压实土冻胀敏感性的一般和耦合效应。希望所开发的粗填土模型和综合分析可以帮助铁路机构了解冻胀的适当特征，并为优化铁路路基提供评估指南。相对压实和应力水平对压实土冻胀敏感性的影响。希望所开发的粗填土模型和综合分析可以帮助铁路机构了解冻胀的适当特征，并为优化铁路路基提供评估指南。相对压实和应力水平对压实土冻胀敏感性的影响。希望所开发的粗填土模型和综合分析可以帮助铁路机构了解冻胀的适当特征，并为优化铁路路基提供评估指南。