Scientific approaches to pile design have advanced enormously in recent decades and yet, still, the most fundamental aspect of pile design—that of estimating the axial capacity—relies heavily upon empirical correlations. Improvements have been made in identifying the processes that occur within the critical zone of soil immediately surrounding the pile, but quantification of the changes in stress and fabric is not straightforward. This paper addresses the degree of confidence we can now place (a) on the conceptual and analytical frameworks for estimating pile capacity, and (b) on the quantitative parameters required to achieve a design. The discussion is restricted to driven piles in clays and siliceous sands, with particular attention given to extrapolating from design approaches derived for closed-ended piles of relatively small diameter to the large-diameter open-ended piles that are used routinely in the offshore industry. From a practical viewpoint, we need design approaches that minimise sensitivity...

Science and empiricism in pile foundation design

Uncertainties in probabilistic numerical analysis of structures and solids-Stochastic finite elements

An analytical method for developing a theoretical load-settlement curve for axially loaded piles in clay is presented. The method is based on the correlation of the ratio of load transfer to soil shear strength as a function of pile movement. The results of studies of field tests of instrumented piles and laboratory tests of small piles in clay are used to obtain the desired correlation. The correlation is presented in the form of a family of curves that are obtained when the ratios of load transfer to soil shear strength versus pile movement are plotted as a function of depth. The validity of the family of correlation curves is checked by comparing computed and actual load-settlement curves for some typical field tests. Results obtained by this method indicate that the method may be used effectively to determine load-carrying capacity for axially loaded piles in clay.

Closure to “Load Transfer for Axially Loaded Piles in Clay”

Over the last few years or so, the use of artificial neural networks ( ANNs) has increased in many areas of engineering. In particular, ANNs have been applied to many geotechnical engineering problems and have demonstrated some degree of success. A review of the literature reveals that ANNs have been used successfully in pile capacity prediction, modelling soil behaviour, site characterisation, earth retaining structures, settlement of structures, slope stability, design of tunnels and underground openings, liquefaction, soil permeability and hydraulic conductivity, soil compaction, soil swelling and classification of soils. The objective of this paper is to provide a general view of some ANN applications for solving some types of geotechnical engineering problems. It is not intended to describe the ANNs modelling issues in geotechnical engineering. The paper also does not intend to cover every single application or scientific paper that found in the literature. For brevity, some works are selected to be described in some detail, while others are acknowledged for reference purposes. The paper then discusses the strengths and limitations of ANNs compared with the other modelling approaches. The engineering properties of soil and rock exhibit varied and uncertain behaviour due to the complex and imprecise physical processes associated with the formation of these materials (Jaksa 1995). This is in contrast to most other civil engineering materials, such as steel, concrete and timber, which exhibit far greater homogeneity and isotropy. In order to cope with the complexity of geotechnical behaviour, and the spatial variability of these materials, traditional forms of engineering design models are justifiably simplified. An alternative approach, which has been shown to have some degree of success, is based on the data alone to determine the structure and parameters of the model . The technique is known as artificial neural networks ( ANNs) and is well suited to model complex problems where the relationship between the model variables is unknown (Hubick 1992). This paper is intended to be for readers in the field of geotechnical engineering who are not familiar with artificial neural networks. The paper aims to detail some features associated with ANNs through a review for some of their applications to-date in geotechnical engineering. It is hoped that this review may attract more geotechnical engineers to pay better attention to this promising tool. The paper starts with a brief overview of the structure and operation of the ANNs and gives a general overview of most ANN applications that have appeared in the geotechncial engineering literature. Finally, the paper discusses the relative success of ANNs in predicting various geotechnical engineering properties and behaviour.

Artificial neural network applications in geotechnical engineering

Phase field modeling of fracture in multi-physics problems. Part III. Crack driving forces in hydro-poro-elasticity and hydraulic fracturing of fluid-saturated porous media

An approach is presented for the analysis of linear and non-linear responses of vertically loaded pile groups. The soil behaviour of individual piles in modelled using load-transfer curves and the pile-soil-pile interaction is determined based on Mindlin's solution. Good agreement between the present method of analysis and the rigorous boundary integral method is observed for the computation of the response of pile groups embedded in a homogeneous, isotropic elastic half-space. The computed non-linear response of pile groups compares favourably with measured results from field load tests.

Analysis of vertically loaded pile groups

Finite element analysis of tunnel–soil–pile interaction using displacement controlled model

A series of centrifuge model tests has been conducted to examine the behavior of laterally loaded pile groups in normally consolidated and overconsolidated kaolin clay. The pile groups have a symmetrical plan layout consisting of 2, 2 32, 233, 333, and 434 piles with a center-to-center spacing of three or five times the pile width. The piles are connected by a solid aluminum pile cap placed just above the ground level. The pile load test results are expressed in terms of lateral load-pile head displacement response of the pile group, load experienced by individual piles in the group, and bending moment profile along individual pile shafts. It is established that the pile group efficiency reduces significantly with increasing number of piles in a group. The tests also reveal the shadowing effect phenomenon in which the front piles experience larger load and bending moment than that of the trailing piles. The shadowing effect is most significant for the lead row piles and considerably less significant for subsequent rows of trailing piles. The approach adopted by many researchers of taking the average performance of piles in the same row is found to be inappropriate for the middle rows, of piles for large pile groups as the outer piles in the row carry significantly more load and experience considerably higher bending moment than those of the inner piles.

Centrifuge Model Study of Laterally Loaded Pile Groups in Clay

Neural network: an alternative to pile driving formulas

The numerical analysis of an object penetrating deep into the seabed is a fundamentally challenging problem. This paper presents the application of a novel Eulerian-based finite-element technique to simulate the continuous penetration of a jack-up spudcan foundation into seabed of different soil profiles. The finite-element mesh is kept stationary throughout the analysis and the material is allowed to move independent of the element nodal points. Consequently, termination of computing execution from severe mesh distortion does not occur despite the material undergoing large deformation. The first part of the paper elucidates the mesh density requirement, the effect of penetration rates, and factors influencing the simulation time. The applicability of the Eulerian finite-element model is then validated through comparison with published experimental data for different soil profiles. In general, the Eulerian finite-element model is able to replicate the experimental observations well. With the Eulerian appr...

Yean Khow Chow

Papers

Analysis of vertically loaded pile groups

Finite element analysis of tunnel–soil–pile interaction using displacement controlled model

Centrifuge Model Study of Laterally Loaded Pile Groups in Clay

Neural network: an alternative to pile driving formulas

Eulerian Finite-Element Technique for Analysis of Jack-Up Spudcan Penetration