Sean D. Hinchberger

Geosynthetic reinforced embankments on soft clay foundations: predicting reinforcement strains at failure

Geosynthetic reinforced embankments can fail before the ultimate tensile strength of the reinforcement is mobilized. For the purpose of embankment design, engineers must often rely on experience when selectinga reinforcement strain for analysis usinglimit equilibrium methods or resort to complicated numerical methods such as those based on the finite element method. This paper presents a simple procedure for estimatingthe undrained stability of geosynthetic reinforced embankments founded on soft clayey soils where the shear strength increases with depth. Finite element results are summarized in a design chart for establishing geosynthetic reinforcement strains suitable for design. The procedure is illustrated using worked examples and tested against a well documented case history. r 2003 Elsevier Science Ltd. All rights reserved.

Viscoplastic constitutive approach for rate-sensitive structured clays

This paper extends an existing elastic–viscoplastic (EVP) constitutive model using a state-dependent viscosity parameter to describe the engineering response of undisturbed structured clay. The term structure refers to the effects of fabric and weak cementation bonds between clay particles. The extended constitutive model is coupled with the Biot consolidation theory and is formulated to describe the intrinsic or unstructured response of clay using overstress viscoplasticity, an elliptical cap yield surface, Drucker–Prager failure envelope, and a hardening law from critical state theory. The clay structure is mathematically accounted for by assuming that the initial fluidity of structured clay at yield and failure is very low and that the fluidity increases with increasing plastic strain. This process is usually referred to as “destructuration.” The formulation is evaluated using Saint-Jean-Vianney (SJV) clay by comparing calculated and measured behaviour during consolidated isotropically undrained triaxi...

An analytical solution for jointed tunnel linings in elastic soil or rock

This paper presents a closed-form solution for tunnel linings that can be idealized as an inner jointed segmental lining and an outer thick-walled cylinder embedded in a homogeneous infinite elastic soil or rock. Solutions for moment and thrust have been derived for cases involving slip and no slip at the lining–ground and lining–lining interfaces. In addition, the closed-form solution is verified by comparing it with finite element results where it is shown to agree well with this more sophisticated method of analysis.

A closed-form solution for composite tunnel linings in a homogeneous infinite isotropic elastic medium

This paper presents a closed-form solution for composite tunnel linings in a homogeneous infinite isotropic elastic medium. The tunnel lining is treated as an inner thin-walled shell and an outer thick-walled cylinder embedded in linear elastic soil or rock. Solutions for moment and thrust have been derived for cases involving slip and no slip at the lining–ground interface and lining–lining interface. A case involving a composite tunnel lining is studied to illustrate the usefulness of the solution.

Case studies of three-dimensional effects on the behaviour of test embankments

This paper uses both two-dimensional (2D) and three-dimensional (3D) finite element (FE) analyses to examine three cases involving the construction of full-scale test embankments to failure on soft clay deposits. By comparing the calculated fill thickness at failure from 2D and 3D analyses, it is shown that 3D effects are significant for all test fills, de- spite the dramatically different locations, fill thicknesses, and underlying clay deposits. In addition, the calculated un- drained displacement and extent of failure from 3D analysis agree well with those measured in each case. The risk of neglecting 3D effects is highlighted by the analyses, where it is shown that failure to account for 3D effects while inter- preting the response of a test embankment can lead to unsatisfactory performance of the actual long embankment. Finally, by comparing FE analysis results with well-known bearing capacity factors, it is shown that test embankments with a base length to width ratio less than 2 are more strongly influenced by 3D effects than spread footings on similar soil profiles. The analyses presented in this paper provide practical insight into some factors that should be taken into account for the design and construction of embankments and test fills on soft clay deposits.

Influence of Pore Fluid Viscosity on the Dynamic Properties of an Artificial Clay

This paper presents the results of vane shear, laboratory compaction, isotropic consolidation, cyclic triaxial, bender element, and resonant-column tests that were performed to characterize the dynamic properties of an artificial soil called modified glyben. Modified glyben comprises a mixture of glycerin, water, and bentonite that can be used in scaled model tests performed at 1 G or  n G in a centrifuge to study seismic soil–structure interaction. The results described in this paper show that the vane shear strength, coefficient of consolidation, dynamic modulus, and damping ratio are strongly influenced by the viscosity of the pore fluid which can be varied by altering the ratio of glycerin-to-water. In addition, the properties of modified glyben are stable during prolonged exposure to air and multiple largestrain load cycles making it a suitable model soil for scaled model tests involving seismic soil–structure interaction.

Predicting the dynamic properties of glyben using a modular neural network (MNN)

Glyben is an artificial soil comprised of bentonite and glycerin that is used in scaled physical model testing. The dynamic properties of glyben are strongly influenced by the percent glycerin by mass in the artificial soil, temperature, time after mixing, shear strain amplitude, excitation frequency, and confining stress. This paper describes the development and testing of a modular neural network (MNN) that is suitable for predicting the dynamic properties of glyben. The MNN architecture comprises an input layer, two expert modules (neural networks) linked by a gating network, and an output layer. The MNN is trained using 124 datasets obtained from the literature and tested as part of the current study to evaluate its accuracy. It is shown that the developed MNN can adequately predict the dynamic properties of glyben.