Shear behavior of concrete–soil interfaces in geopolymer post-grouted bored piles: Insights into green grouting mechanisms

Abstract

Post-grouting technology is an effective method to enhance the bearing performance of the pile foundation, where cement is the most commonly applied due to outstanding performance. However, cement production accounts for a relatively high proportion of global carbon dioxide emissions, which doesn’t agree with the dual carbon target. Geopolymer is a green and sustainable material, since consisting of natural minerals rich in aluminosilicate and industrial waste. To promoting the application of geopolymer post-grouting technology, this study, based on the actual stress environment of post-grouting bored piles, explores the influence laws of mudcake, grouting volume, grouting pressure, interfacial roughness, normal stress, and grouting material on the shear characteristics of the geopolymer post-grouting concrete–soil interface through the interfacial shear test, and the shear stress–displacement curves are fitted by using a hyperbolic function model. The results showed that the shear stress–displacement curves conformed to the hyperbolic model, with shear stress–displacement behavior following Mohr-Coulomb failure criteria and showing shear hardening. The presence of mudcake significantly reduced the interfacial shear strength, but geopolymer grouting enhanced the interfacial shear strength by 0.52 to 1.66 times and the cohesion by 1.09 to 2.24 times compared with the ungrouted treatment. Sufficient grouting volume and normal stress mitigate mudcake’s adverse effects. Geopolymer grouting improves interface shear strength 1.45 to 2.41 times more than ordinary Portland cement. This study provides theoretical insights and a scientific basis for geopolymer post-grouting pile application, offering an eco-friendly solution to enhance foundation performance.

Graphical abstract

Keywords

geopolymer grouting / concrete–soil interface / shear strength / mudcake effects / shear stress–displacement model

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