基于大型动三轴试验和神经网络的粗粒土临界动应力研究

Study on Critical Dynamic Stress of Coarse-grained Soil Based on Large-scale Dynamic Triaxial Test and Neural Network

为研究基床粗粒土填料的累积塑性变形特性、动力稳定性和临界动应力,开展不同围压、动应力和含水量的系列大型动三轴试验。结果表明:粗粒土的累积塑性应变ε_(p)随动荷载振动次数N的关系曲线可分为破坏型、稳定型和临界型。建立分析εp-N曲线类型与土体围压、含水量及动应力相关性的灰色关联模型,结果表明曲线类型受围压、动应力及含水量的影响显著,且三者对决定粗粒土的动力稳定状态具有同等重要作用。构建预测粗粒土临界动应力的BP神经网络模型,分析表明粗粒土的临界动应力随围压增加而近似线性增大,随含水量的增加而非线性减小;综合试验和模型分析结果,提出考虑围压和含水量影响效应的粗粒土临界动应力经验公式。

A series of large-scale dynamic triaxial tests under different confining pressures,dynamic stresses,and water contents were performed to study the accumulative plastic deformation characteristics,dynamic stability,and critical dynamic stress of a typical coarse-grained subgrade bed soil.The test results demonstrate that the relationship curves between the accumulative plastic strainε_(p) of the coarse-grained soil and cycle number N of dynamic loads can be divided into failure,stable,and critical types.A grey relation model was then developed to analyze the correlation characteristics of theεp-N curve patterns with respect to the confining pressure,dynamic stress,and water content,where the analytic results show that the curve patterns are significantly affected by the three factors,and they have similar importance in determining the dynamic stability state of the soil.A back-propagation(BP)-neural network model was then established to predict the critical dynamic stress of the coarse-grained soil.The results illustrate that the critical dynamic stress of the coarse-grained soil approximately linearly increases with the increase of the confining pressure but nonlinearly decreases as the water content increases.Finally,an empirical formula considering the effect of confining pressure and water content was proposed to evaluate the critical dynamic stress of the coarse-grained soil based on the test and BP-neural network analytic results.