Permeability Estimation of Engineering-Adapted Clay–Gravel Mixture Based on Binary Granular Fabric

Abstract

Clay–gravel mixture is an increasingly popular material used in geotechnical engineering for its engineering adaptability and easy accessibility. Among various granulometric factors, gravel content plays a critical role in the alteration of mixture microstructure. Its influence on mechanical behavior has been comprehensively investigated, yet the hydraulic models accounting for the paired impact of clay and gravel particles are seldomly discussed. In an effort to enhance the permeability prediction capability of this soil, a generalized binary model derived from a theoretical hydraulic conductivity expression is proposed, with the participation of two fundamental compound seepage models. High accuracy between test and calculation results indicates the reliability of this model, as well as its supremacy over conventional models. The parameter sensitivity analysis demonstrates that the proposed model, being of convincing parametric stability regardless of variant particle size distribution characteristics, has the potential to be applicable to a wide range of engineering-adapted CGMs. The predictive formula for cohesive fraction and the anomaly coefficient, as is integrated into the binary model, are explicitly discussed. Suitable for clay–gravel materials under a transitional soil state for engineering applications, this model provides a quantitative and reasonable evaluation of hydraulic conductivity with high practicality. The above findings might work as a perspective for the credible assessment of structure seepage safety behavior, as well as a quantitative evaluation method regarding the mixing quality of CGMs.

Keywords

• clay–gravel mixture
• hydraulic conductivity
• binary model
• parameter sensitivity analysis
• mixing quality