AI 中文总结
本文构建了含2854项试验的大型土壤压实语料库，用表格基础模型等机器学习方法预测干密度与含水率，验证了击实能量的条件决定性，为相关研究提供基准与工具。
AI 中文摘要
每种工程填土都需规定最大干密度和最优含水率，每项测定都需要完整的Proctor试验。已发表的相关研究依赖1至400个试样，通常来自单个实验室的单一击实能量，且相关成果极少公开。本文公开了一个不受这些限制的语料库，包含来自6个公共来源的2854项实验室压实试验，涵盖162个来源组和4种Proctor能量水平，细粒含量范围为1.5%至100%。每条记录均按其来源标注的Proctor方法进行审核，未对任何击实能量进行推断。对零孔隙空气条件的筛选移除了11.8%的 harmonised 记录，以及5.7%具有实测比重的记录。已发表的压实数据中有一部分在物理上是不可能的。该语料库的最优饱和度为0.815，变异系数为11%，这是一个基准值而非常数。随后从一个分类套件和压实标准中估计这两个参数。表格基础模型在随机交叉验证下对密度的决定系数R²达到0.824，对含水率的R²达到0.784；在按来源分组的交叉验证下，两者分别为0.727和0.696；在留出整个来源的交叉验证下，两者分别为0.520和0.614。击实能量在边际上影响可忽略，但在条件上具有决定性：在66项改良Proctor记录上，纳入击实能量时对密度的预测R²为0.740，未纳入时为-0.651。符号回归产生通过相位关系耦合的闭式表达式，由此得到的预测对均不超过零孔隙空气线。这些预测用于筛选，而非验收。
英文摘要
Every engineered fill is specified by a maximum dry density and an optimum moisture content. Each determination needs a full Proctor test. Published correlations rest on one to four hundred specimens, usually from one laboratory at one compactive energy, and are seldom released. This paper releases a corpus without those limits. It holds 2,854 laboratory compaction tests from six public sources, across 162 provenance groups and four Proctor energy levels, with fines from 1.5 to 100%. Every record is audited to the Proctor method its source names, and no energy is inferred. Screening on the zero-air-voids condition removed 11.8% of harmonised records, and 5.7% of those with a measured specific gravity. A material share of published compaction data is physically impossible. The optimum degree of saturation over the corpus is 0.815 at a coefficient of variation of 11%. That is a baseline, not a constant. Both parameters are then estimated from one classification suite and the compaction standard. A tabular foundation model reaches R2 0.824 for density and 0.784 for water content under random folds. It reaches 0.727 and 0.696 with folds drawn around provenance, and 0.520 and 0.614 with a whole source held out. Compactive energy is negligible marginally yet decisive conditionally. Density on the 66 modified-Proctor records is predicted at R2 0.740 with it and -0.651 without. Symbolic regression yields closed forms coupled through a phase relation. No predicted pair can then exceed the zero-air-voids line. The predictions are for screening, not acceptance.
