Abstract
Abstract Dynamic behavior of subgrade soils greatly affects the serviceability of a railway/highway line, where the critical dynamic stress (σcri) mainly determines the dynamic stability of a subgrade. In this study, a series of large-scale dynamic triaxial tests on saturated specimens with different confining pressures (σ3) and dynamic deviatoric stresses (σd) were performed to investigate the dynamic stability of a coarse-grained subgrade soil. A Grey Relational Analysis was first established, where the analyzed results demonstrating that the dynamic stability of the coarse-grained soil (CGS) strongly correlated with σ3 and σd. The accumulative plastic strain (ep) versus cycle number (N) curve patterns (i.e., failure, critical, and stable) of the tested specimens were then analyzed using the back-propagation (BP)-neural network, illustrating that the latter can effectively reflect the variation trend of ep with respect to σ3 and σd. Finally, an empirical method was proposed to predict the critical dynamic stress of the CGS, and a shakedown limit criterion was introduced to analyze the dynamic strength properties of the CGS under shakedown limit states, revealing that the critical dynamic stress approximately linearly increased with increasing confining pressure.
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