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Effect of the particle-size distribution variability on the SWCC predictions of coarse-grained materials

机译:粒度分布变异性对粗粒材料SWCC预测的影响

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The particle-size distribution (PSD) is the key information required by several models for prediction of the soil-water characteristic curve (SWCC). The performance of these models has been extensively investigated in the literature; however, limited studies have been undertaken with respect to the uncertainty associated with the SWCC predictions resulting from the variability in the PSD. This study aims to investigate the influence of the variability of the PSD in the prediction of SWCCs using five different models applied to three different glass beads (GBs). The PSD curves were determined by sieve analysis, laser diffraction, and image analysis. The various testing procedures were statistically evaluated to understand the influence of variability of the PSD in terms of the coefficient of uniformity ( C _(U)) and de size of particles corresponding to 10% in the PSD ( D _(10)). For each prediction model, a combination of PSD curves and their coefficient of variation were used to estimate the SWCCs. Both the C _(U)and D _(10)proved to have a strong relationship with the predicted SWCCs. The C _(U)appears to influence more the residual suction prediction while the D _(10)seems to have a major role for the transition and residual stages.
机译:粒度分布(PSD)是几种模型所需的关键信息,用于预测土壤 - 水特征曲线(SWCC)。这些模型的表现已在文献中进行广泛调查;然而,已经对与PSD中变异性导致的SWC​​C预测相关的不确定性进行了有限的研究。本研究旨在调查PSD可变性在使用施加到三种不同玻璃珠(GBS)的不同模型预测SWCC的影响。通过筛分分析,激光衍射和图像分析来确定PSD曲线。在统计上评估各种测试程序以了解PSD可变性的影响,就均匀性系数(C _(u))和PSD中对应于10%的颗粒(D _(10))的颗粒的影响。对于每个预测模型,使用PSD曲线的组合及其变异系数来估计SWCC。 C _(U)和D _(10)都证明与预测的SWCC有很强的关系。 C_(U)似乎影响更多的剩余抽吸预测,而D _(10)似乎对过渡和残差阶段具有重要作用。

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