In this section the numerical model used for the evaluation of the critical load for slender pile embedded in soft clay is proposed. After the general description of the model, the large-scale experimental results used for the model validation and calibration are presented. The material parameters selection is shown, and in the last subsection, a comparison of numerical–experimental results is illustrated.
Description of the Numerical Model
A commercial finite element software ADINA [33] is used to model the behaviour of micropiles axially loaded. The pile is meshed through 2-node beam elements of linear elastic material; the software requires the introduction of the cross-sectional area and the moment of inertia for these elements, so that piles with different cross sections can be considered.
For the soil, 9-node quadrangular elements in plane–strain conditions are used, with a mesh more discretised close to the pile, where accurate information is required. Literature examples show that a plane–strain modelling for the soil in problems of piles axially loaded provides a stiffer confinement (numerical displacements smaller than the experimental reality), but the deflection profile is well captured [34, 35]. A modified Mohr–Coulomb criterion is used to model the soil’s constitutive behaviour. At its boundaries, the soil is pinned horizontally in order to avoid outward movement; the vertical degree of freedom is allowed for the development of the geostatic stress.
Static analyses are performed through an automatic time stepping (ATS) scheme; large displacements and small deformations are considered as kinematic assumptions. Loads are applied in two main phases: in the first phase, the soil’s self-weight is applied gradually; in the second phase, the pile head is axially loaded with an incremental axial force. A target node is chosen on the pile, half-way up, where the vertical load and the horizontal displacements are read; the critical load is associated with a horizontal asymptote in the load–displacement curve.
One of the factors mainly influencing the numerical results of a pile–soil interaction problem is the interface; a “constraint function algorithm” is used [36]: two (or more) surfaces are coupled, giving rise to a frictional contact governed by the friction coefficient μ. The normal and tangential contact forces are smoothed out with the distance from the contact according to two “model-dependent” parameters, respectively, εN and εT; the latter also controls the switch of the contact nodes from stick to slip condition. Finally, the compliance factor CF allows to artificially soften the contact surfaces and help the convergence. In the following, the calibration of the numerical model with a proper choice of the material, as well as the interface parameters, is shown, based on experimental results found in the literature; this is essential to evaluate the quality of the numerical modelling.
Calibration and Validation of the Numerical Modelling
Description of the Experimental Tests Used for the Numerical Model Validation
In the literature, there are different examples of experimental tests performed on pile foundations for different purposes [37, 38]; the results of an experimental campaign consisting of axial load tests on model piles performed at the Geotechnical Centre of the Technical University of Munich [31, 32] are used for the validation of the FE model. A large-scale model has been set up consisting of a cylindrical container, which the pile is pinned to (Fig. 1a). Authors consider two pile types, in both cases 4 m long: Type I with circular concrete–steel composite section (d = 100 mm, L/d = 40) and Type II with a rectangular aluminium section (40 × 100 mm, L/d ~ 100).
As reported in introduction, according to most building codes, buckling is likely to happen in slender piles when embedded in weak soils of poor properties; the plastic China clay (liquid limit wL = 55%, plastic limit wP = 28% and plasticity index IP = 27%, unit weight γsat = 19 kN/m3, friction angle φ′ = 25°) was used and pumped inside the container (Fig. 1b). The clay was first preconsolidated using dead loads; then, its consolidation process was accelerated by means of electro-osmosis and geotextile vertical drains; the undrained shear strength cu was measured through vane tests, performed at different depths in the soil inside the experimental container, revealing a linear increase with depth. The authors have assumed a mean cu value equal to 15 kN/m2; this value represents the upper limit under which buckling assessment is required according to DIN 1054.
Different axial loads have been applied to the pile head; for each load, the lateral displacements have been measured thanks to displacement transducers placed every metre in depth (Fig. 1c). In the paper, along with the experimental tests available from Vogt et al., the results of tests performed on pile Type II are considered, because aluminium shows fewer uncertainties related to material characteristics; the lateral displacements for different axial loads N related to this pile type are illustrated in Fig. 2. Authors have revealed that the pile failure occurs at N = 220 kN, with any noticeable plastic deformations; in this case, the ultimate load has therefore been linked to the loss of stability and it deals with a critical load PCR. Figure 2 shows us that the maximum horizontal displacement for each applied axial load is recorded at the middle of pile’s length; the experimental displacements recorded at this point will be compared to the numerical results.
Definition of Material and Interface Parameters for the Numerical Simulation of the Experimental Results
The FE model described in Sect. 2.1 is now used to numerically simulate the experimental tests. For the pile, a rectangular cross section 40 × 100 mm2 is put into the beam element; Young’s modulus E = 64,000 MPa is used for the aluminium section. The pile ends are pinned horizontally, in coherence with the experimentation.
The soil modelling is crucial because the horizontal displacements of the pile and its lateral stability, in general, depend on it, together with a proper modelling of the pile–soil interface. According to the constitutive law adopted (modified Mohr–Coulomb’s model), the soil confinement is given by Young’s modulus; values of the undrained modulus Eu are derived from the undrained shear strength cu measured in the experimental tests. A soft clay with a plasticity index lower than 30% shows Eu/cu ranging from 600 to 5000 ([39]; Bowles, 1988 in [40]). For Ip = 27% the value of 800 is chosen; considering the soil modulus decay, this value is usually associated with a great strain level, of approximately 0.05–0.1% [40], compatible with the maximum strain of this experimentation.
As reported in the previous paragraph, the experimental cu was noticed to increase linearly with depth (cu = 15 kPa is a mean value); a variation of cu with depth wants to be introduced into the model. According to the soil type, the ratio \(\frac{{c}_{u}}{{{\sigma }^{^{\prime}}}_{v0}}\) is constant, the effective vertical stress being \({{\sigma }^{^{\prime}}}_{v0}\) [41]; in the case presented, at a middle point \({{\sigma }^{^{\prime}}}_{v0}=\) 18 kPa and consequently = \(\frac{{c}_{u}}{{{\sigma }^{^{\prime}}}_{v0}}\)0.83 (this value appears to be coherent with values reported in [41]). Evaluating \({{\sigma }^{^{\prime}}}_{v0}\) at different depths, a cu value corresponding to this depth can be calculated, so introducing a linear variation with depth; being Eu depending on cu, a variation of Young’s modulus is consequently considered. In the numerical model the soil surface is therefore divided into eight layers (Fig. 3) and a mean value is assumed for each layer. Table 1 contains the values adopted, corresponding to the mean depth z of each layer.
Table 1 Soil parameter evaluation for each layer of the numerical analysis Other than the material parameter choice, the section’s aim is also the calibration of the numerical interface parameters so that the model could capture the experimental PCR. The friction coefficient μ is set to 0.36, assuming an angle of friction soil–pile of 20°; different values of εN, εT and CF are analysed, in order to study their influence on the PCR (εN = 10–15 ÷ 10–7, εT = 10–7 ÷ 1, CF = 10–7 ÷ 10–2).
Numerical vs Experimental Results
The numerical outputs are the loads and the horizontal displacements in the target node; the buckling load is reached when a horizontal asymptote is observed in the load–displacement curve. The values of PCR by changing the interface parameters are reported in Fig. 4. It is evident that εN and εT do not affect the critical load value: they represent a sort of normal/tangential contact stiffness, which influences only the magnitude of lateral displacement. On the other hand, CF strongly affects the PCR: values less than or equal to 10–5 determine a stable FE critical load. εN = 10–12, εT = 10–3 and CF = 10–5 are finally assumed.
In order to evaluate the accuracy of the calibration in relation to the critical load, Fig. 5 shows an experimental–numerical comparison of the load–displacement curve in the target node, which corresponds to the point where maximum displacements are recorded experimentally; it is observed how the numerical model is able to capture the experimental critical load with only 18% of difference, which is considered much more than reasonable. In the following, the application of the numerical model is therefore extended to a parametric study, focusing on the influence of slenderness L/d on the ultimate behaviour of piles of different geometries.