The void ratio limits and their range are mostly governed by their grain size, distribution, particle shape and fabric for cohesionless soils. For the purpose of developing a probability-based predictive model, a database, which consists of minimum and maximum void ratios, their range, as well as particle morphology (roundness, sphericity), size and distribution (mean grain size, fines content and coefficient of uniformity) parameters, is compiled. A set of predictive models, which use the combinations of C_u, D₅₀, FC, R, and S parameters, is proposed. The models with C_u and/or D₅₀, R and S, produce the most precise predictions. The probabilistic forward use of the proposed models is illustrated by a practical example. They are also presented in the form of deterministic chart solutions, illustrating the variation of in-situ void ratios for varying density states as functions of uniformity coefficient or mean grain size.

空隙率的限值及其范围主要取决于无粘性土壤的粒度，分布，颗粒形状和织物。为了开发基于概率的预测模型，需要一个数据库，该数据库由最小和最大空隙率，其范围以及颗粒形态（圆度，球形度），尺寸和分布（平均晶粒尺寸，细粉含量和系数）组成均匀性）参数进行编译。提出了一组预测模型，这些模型使用C _u，D ₅₀，FC，R和S参数的组合。具有C _u和/或D _50的模型R和S产生最精确的预测。一个实际的例子说明了所提出模型的概率向前使用。它们也以确定性图表解决方案的形式呈现，说明了随着密度系数或平均晶粒尺寸变化而变化的密度状态下原位空隙率的变化。