级配碎石横观各向同性动态回弹模量预估研究

Prediction of cross-anisotropic resilient modulus for unbound aggregates

【目的】建立一种快速且高效预估级配碎石横观各向同性动态回弹模量的方法。【方法】首先,选取四种碎石材料,通过级配试验、击实试验、亚甲蓝试验、细骨料含量试验和集料成像系统试验表征级配碎石材料特性。接着,提出可以表征应力水平和湿度状态对回弹模量影响的级配碎石横观各向同性动态回弹模量本构模型。然后,通过开展室内快速动三轴试验并采用系统识别方法得到四种碎石材料在不同级配组合、应力水平和湿度状态下的竖向、横向和剪切模量。最后,利用相关性系数评估模型的拟合精度,采用JMP统计软件并基于多元线性逐步回归方法建立级配碎石材料特性与横观各向同性回弹模量模型参数之间的回归关系。【结果】级配碎石横向模量与竖向模量比为0.3~0.6,剪切模量与竖向模量比为0.2~0.4;中级配碎石横观各向同性回弹模量普遍高于粗级配或细级配碎石的回弹模量;在不同的应力水平条件下,级配碎石的横向、竖向和剪切模量均随含水率的增加而减小。【结论】新的横观各向同性动态回弹模量模型通过引入基质吸力和汉克儿应力因子,能够精确拟合快速动三轴试验得到的级配碎石试件在不同应力水平和湿度状态下的横观各向同性回弹模量,平均拟合相关系数高达0.98;级配碎石的干密度、含水率、亚甲蓝值、细骨料含量、级配、棱角性和形状等材料特性均显著影响横观各向同性回弹模量模型参数。

This Study aims to develop an accurate and efficient methodology to predict the cross-anisotropic resilient modulus for unbound aggregates. [Methods] First,four unbound aggregates were collected and analyzed by the gradation test, compaction-density test, methylene blue test, percent fines content test, and aggregate imaging system test. Next, a new cross-anisotropic resilient modulus model was developed to characterize the stress-dependency and moisture-sensitivity of unbound aggregates. Subsequently, the laboratory rapid triaxial test was performed to determine the vertical,horizontal,and shear moduli of unbound aggregates with different gradations,stress levels,and moisture conditions. Finally,the R-squared values were used to evaluate the model’s fitting accuracy. The JMP statistical software and multiple linear stepwise regression method were used to establish the correlation between unbound aggregate material properties and their cross-anisotropic resilient modulus model coefficients. [Findings] The unbound aggregates had a horizontal/vertical modulus ratio ranging from 0.3 to 0.6 and a shear/vertical modulus ratio ranging from 0.2 to 0.4. The intermediate-graded unbound aggregates had higher vertical, horizontal, and shear moduli than those of coarse-or fine-graded unbound aggregates. At different stress levels,the vertical,horizontal,and shear moduli of unbound aggregates decreased with the increased moisture content. [Conclusions] This study concluded that the new cross-anisotropic resilient modulus model accurately captured the influences of stress level and moisture conditions via the incorporation of matric suction and Henkerl stress terms,and the correlation of fitting coefficient was above 0.98. The multiple regression analysis indicated that the dry density,moisture content,methylene blue value,percent fines content,aggregate gradation, angularity, and shape are statistically significant variables affecting the cross-anisotropic resilient modulus model coefficients.