A quantitative evaluation method for granular skeleton state of binary soils at arbitrary relative density. (January 2023)

• Record Type: Journal Article
• Authors: Xie, Yipeng; Yang, Junsheng; Zhang, Cong; Qu, Tongming; Wang, Shuying; Fu, Jinyang
• Is Part Of: Computers and geotechnics. Volume 153(2023)
• Publication Date: 2023-01
• Subjects: Binary soils -- Granular skeleton state -- Relative density -- Discrete element method -- Micro-mechanical behavior; Engineering geology -- Data processing -- Periodicals; Soil mechanics -- Data processing -- Periodicals; Rock mechanics -- Data processing -- Periodicals; 624.1510285
• DOI: 10.1016/j.compgeo.2022.105083
• Languages: English
• ISSNs: 0266-352X

Abstract

Abstract: The granular skeleton state relates closely to the mechanical behavior of granular soils but its characterization remains an open challenge. This study aims to develop a novel method to quantify the skeleton state of binary granular soils with arbitrary relative density D r . Inspired by a linear correlation between the maximum and minimum void ratios, the dual-skeleton packing model was extended to incorporate the effect of D r . A standard procedure of determining the dual-skeleton index ψ at arbitrary D r was proposed. Furthermore, a series of numerical binary soil samples with 27 PSDs were simulated in multiple D r via discrete element method (DEM). The results indicated that the granular skeleton state experienced a typical three-phase evolution pattern of "coarse-dominated → transitional → fine-dominated" with increasing f c . Through the calculated ψ value, critical f c values of phase transition in skeleton state evolution for samples with multiple D r and the ratio of maximum to minimum particle diameter R d were unveiled. The micro-mechanical behaviors were observed to be strongly related to the variation of ψ value. Furthermore, a quantitative correlation between ψ and the stress contribution of fine particles was revealed. The simulation results demonstrated the dual-skeleton index ψ can serve as an indicator to characterize the micromechanical behavior of granular media.