Accounting for Intrinsic Soil Properties and State Variables on Liquefaction Triggering

TLDR: In this article , a new mechanistically based Kγ factor is proposed that can be incorporated in penetration test, stress-based simplified liquefaction triggering models in place of the currently used Kσ factor.

Abstract: This paper proposes a new approach for incorporating the positive attributes of the small-strain shear wave velocity (VS), stress-based simplified procedure and the cyclic strain procedure into penetration test, stress-based simplified liquefaction triggering models, with the objective of more fully accounting for the influence of intrinsic soil properties and soil state variables on liquefaction triggering. Current simplified liquefaction procedures are limited in their ability to capture the effects of intrinsic properties (grain size, mineralogy, grain shape, etc.) and the state properties (stress state, void ratio, fabric, etc.). To overcome these limitations, a new mechanistically based Kγ factor is proposed that can be incorporated in penetration test, stress-based simplified liquefaction triggering models in place of the currently used Kσ factor. However, Kγ is conceptually very different from Kσ. While most Kσ relationships have largely been empirically based and relate to the soil’s cyclic resistance to liquefaction, Kγ is more mechanistically based and relates to the loading imposed on the soil. Specifically, Kγ is based on equating the shear strain induced in a given soil at given initial stress state and subjected to a given shear stress to the induced shear strain when the soil is confined at a reference initial stress state, all else being equal. Analyses show that Kγ is able to capture the liquefaction triggering behavior in both lab and field data in a wide range of soils and stress states. Numerically, Kγ and Kσ are similar for young, normally consolidated sandy soils when the factor of safety (FS) against liquefaction triggering is close to one, but may differ significantly for other scenarios and/or conditions. This has important implications for probabilistic-based analyses which consider a range of shaking intensities imposed on the soil, not just the case where FS=1.