This paper presents a review of two models (i.e., arching and lateral squeezing) developed for predicting earth pressures in soil-bentonite (SB) cutoff walls. The assumptions of these existing models are discussed, a modified lateral squeezing (MLS) model is presented, and all three models are compared based on predicted horizontal stresses for representative field conditions. Each model predicts that the stress distribution within a SB cutoff wall may be considerably lower than a geostatic distribution, particularly at depth. The arching model yields the lowest stress distribution but may underestimate the true distribution due to the assumption of rigid trench sidewalls. The MLS model (1) allows sidewall deformation and (2) accounts for the stress-dependent nature of SB backfill compressibility. The study also finds that additional model development is needed to characterize the stress state of a SB cutoff wall in three dimensions.
This paper presents a self-made apparatus which has been used for estimating the adverse influence induced by some factors. There are two main factors that can make significant impact on the result of slope model tests: boundary effect and porosity effect. The relationship between the sliding angle and boundary effect can be achieved when the soil is at a loose condition of packing. The angle will decrease as the slope thickness increases and it will keep at a rough constant value when the thickness is relatively big, namely, the influence induced by the boundary effect which can be ignored at that time. In this paper, a theoretical method is employed to quantify and confirm this relationship. Corresponding predicted results agree well with the experimental results. But this conclusion is not suitable to dense soil. Special attention is also given to dense soil within a given porosity range, and a comparison between boundary effect and porosity is described. It could be seen clearly that the porosity is a stronger factor to the variation of the sliding angle than the boundary condition. These conclusions are valuable to a practitioner in taking modification work for such type of apparatus to get an optimal resolution for the latter experiment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.