1. Introduction
Sustainable energy sources such as wind, hydro and solar are critical and under utilized. Global warming and increasing CO
2 in the atmosphere and the fears of increasing frequency and severity of natural disasters such as extreme weather, flooding and tsunamis have driven government bodies, research institutes and the industry to move at a higher pace towards cultivating more energy from these sources in a bid to reduce dependency on fossil fuels. Specifically, exponential growth of wind energy has been achieved from onshore and offshore wind farms (OWF) with offshore wind turbines (OWTs) reaching a capacity of 14MW already available on the market (Alsharedah et al., 2023).
Figure 1 shows the energy output from offshore wind farms in Europe between 2000-2016. This increase in capacity is realized by using heavier and taller turbines, often leading to very large foundation systems which can consume up to 40% of the total cost (Alsharedah et al., 2022; Prendergast and Igoe, 2022).
Different foundation systems are employed to support wind turbines such as fixed gravity base foundations (GBF), tripod structures, jackets, suction caissons, monopiles (MP), and buoyant fixed structures (Abdelkader, 2016; Poulos, 2016; El-Marassi, 2011; Byrne and Houlsby, 2003).
Figure 2 presents some of the foundation systems used to support OWT. The foundation design process is iterative in nature and begins with estimate of the lateral applied loads from wind, waves and currents in addition to aerodynamic forces. Since the geometry of the foundation is unknown, it is usually assumed, and the foundation response is evaluated. If the assumed foundation geometry is insufficient to meet the ultimate limit state or serviceability limit state, a new geometry is assumed. This loop repeats itself until a suitable foundation geometry is found (Alsharedah, 2022).
Strong records of performance of monopiles from other offshore structures, such as oil platforms, helped engineers with the design of early developments of OWFs. For these piles, the design is based on the famous p-y approach (Byrne et al., 2015, Wang et al., 2017; Biosi and Halder, 2014; Jeanjean, 2009). In this approach, the soil layers are replaced by independent springs each having a different load-displacement curve, called the p-y curve. This approach was firstly proposed by McClelland and Focht (1955) and validated by Matlock (1970) for the case of slender pile in soft soil and then by Reese (1975) who proposed p-y formulae for stiff soil. However, a few issues are raised when applying this method to offshore wind turbines. Firstly, the p-y approach was validated by Matlock (1970) by testing slender piles in soft soil with a diameter of 0.32m and a length of 12.8m, giving L/D ratio of 39.5; however, a typical offshore wind turbine has an order of magnitude larger diameters monopiles with lower L/D ratios. Numerous researchers pointed out that diameter effects were not included in the original method (e.g., Lai et al., 2020; Zhu et al., 2017, Byrne et al, 2015a; Byrne et al., 2015b; Lau, 2015). Other deficiencies arise from the fact that the tested pile has only experienced 20 cycles of loading whereas expected cycles of loads the OWT experiences in its lifetime can be of the order of 107. Thirdly, the ratio of vertical loads to lateral loads in the oil platforms is much higher than the wind turbines, making direct application of API recommendations for monopile design questionable. Finally, the effect of cyclic loading is treated uniformly across pile depth with a reduction factor A of 0.9 irrespective of load level (Haigh, 2014). Improved p-y formulae have since been focused on closing these gaps in literature such as the recent PISA project. The PISA project is an improved version of the p-y approach where additional resistance is added by the side and the base friction (Zhu et al., 2017; Byrne et al., 2015a; Byrne et al, 2015b). For instance, Lau (2015) conducted 9 centrifuge tests on monopiles installed in kaolin clay and subjected to monotonic and cyclic loading. The results demonstrated that the API p-y curves of Matlock (1970) underestimated the stiffness properties of the monopiles, and that the displacement and rotation under cyclic loading depend on number of load cycles and cyclic loads amplitude, which is not accounted for in the API p-y approach. Zhu et al. (2017) conducted field tests on large diameter open ended driven piles in soft clay offshore China. Their tests involved driving 2 monopiles of 2.2 diameter in soft clay and were subjected to both monotonic and low frequency cyclic lateral loading. Their results showed the API p-y curves underestimated both initial stiffness and ultimate capacity, possibly due to reconsolidation from pile driving, which is in line with results from Lau (2015). They proposed a hyperbolic function for p-y curves which provided excellent match to field tests. Additionally, their p-y curves included a degradation factor, t, as a function of depth and cyclic load level. Other methods to obtain the lateral ultimate capacity and deflection at mudline of monopiles include physical testing, FE modelling or Bender’s approach (e.g., Heyer et al (2019) : Gerolymos et al. (2019); Wang et al. (2018); Hong et al. (2017); Abdelkader (2016); Cherchia (2014); Heidari et al. (2014); Klinkvort and Hededal (2014); El-Marassi (2011); Lahane et at. (2010); Powrie and Daly (2007); Murph and Hamilton, 1993; O’Neill et al. (1987); Brown (1978)).
While monopiles lateral behavior has been investigated widely, there is no available easy way to deduce pile capacity. Hence, using a new normalization approach for monopiles for OWTs, the authors are hopeful the new approach can be beneficial and insightful for OWTs monopile design. The results obtained from this study can verify the results from Beam on Nonlinear Winkler Foundation (BNWF) analyses and benchmark new FEM results.
1.1. Methodology
The aim of this research is to establish quick method for estimating monopiles lateral ultimate capacity based on few soil parameters and design inputs. This is done by the study the monopile behavior under eccentric lateral loading similar to that of a 5MW wind turbine in a medium depth water. To do so, several prototype dimensions of MP models were established. A series of finite element models employing displacement-controlled loading were conducted. Models’ responses were evaluated for their bending behavior and lateral ultimate capacity. A new normalization study examines whether the lateral capacity can be described by only the L/D ratio, a combination of L/D and normalized stiffness of monopile. The effects of footing rigidity on the lateral ultimate capacity of monopiles foundation is studied, by changing the ground conditions, and generic curves are established relating the ultimate lateral capacity of the foundation with respect to L/D and the foundation normalized stiffness E
p* given by:
Ep*: normalized stiffness; Ep: pile Young’s modulus; Es: soil elastic modulus; Ip: pile moment of inertia; Iscp: moment of inertia of a solid cross-section pile of same diameter as actual pile.
Specifically, we investigate the mode of contribution to by normalization procedure of the ultimate capacity of monopiles considering the effects of soil profile and pile/soil relative rigidity given by Ep*/E50, where Ep* is the foundation normalized stiffness and E50 is the soil Youngs modulus at 50% of qf, where qf is the ultimate deviatoric load causing failure of soil specimen in a triaxial apparatus, and by normalizing lateral ultimate capacity by soil shear strength and pile’s diameter. Design charts are established to develop MP lateral ultimate capacity considering L/D and Ep*/Es ratios for the given eccentricity. Finally, predictive equations are proposed to calculate MP lateral ultimate capacity based on best fit data from FE results. The normalization method used paves the way for use of same framework with other eccentricities.
Three-dimensional (3D) finite element models (FEMs) were conducted to simulate the MP foundations. Tetrahedron 10 node elements were used to discretize the soil while plate elements were used to discretize the tower and the pile. The FEM was validated against the results of field tests by Zhu et al. (2017), and the pile was simulated using embedded beam elements confined with solid elements instead of plate elements to enable evaluating the structural forces. To account for slippage and gap formation, 6 node interface elements were used to simulate contact between solids (pile) zone and soil. The strength of the interface elements was defined through a reduction factor, Rint, applied to the soil properties, which varied between 1 and 0.3 for soft and stiff soils, respectively. The tower was simulated as a beam element having unit weight, diameter, E and thickness of 77kN/m3, 6m, 200GPa and 0.035m, respectively. It is rigidly connected to surrounding solid elements to ensure the load is transferred uniformly over the pile area. In all models, x and y boundaries were set at 7D from model center and restricted to move horizontally while allowed to move vertically. The bottom, z, boundary was fixed and placed at least 3D below pile tip to avoid any boundary effects and to model rotational stiffness correctly. The FEM had on average 25000 elements.
The soil behaviour was simulated employing the hardening soil (HS) model obeying Mohr-Coulomb (MC) failure criterion (Schanz 1998). The HS model can simulate the behaviour of both soft and stiff soils. It accounts for the stiffness stress dependency, allows plastic straining due to deviatoric and primary compression loading and can simulate the unloading stiffness being higher than loading stiffness, hence accounting for plastic straining before failure is reached. The clay behavior is accounted for by considering effects of two strain hardening; namely volumetric hardening (cap) and shear where contraction and densification cause the yield surface to expand. The soil stiffness parameters in the HS model can be determined as follows.
The analysis involved four stages, including: Initial stage (initiation of geostatic stresses) in which equilibrium is established based on lateral earth pressure coefficient at rest, ko; Construction stage in which all structures and interface elements are activated; Loading stages: where displacement-controlled loading is applied until failure is reached; and finally, the output stage at which the structural forces and soil deformation are examined to establish the failure load. In the FE model calculations, the lateral ultimate capacity was determined as either the maximum reached load at 3m displacement at tower head or the load causing yield stresses in the structural elements.
1.1.1. Validation
The FEM model was bench marked using a case study of field tests carried out on a 2.2 m diameter open ended pile driven offshore China (Zhu et al., 2017). The pile has a thickness of 0.03m and a depth of 57.4 m below seabed. Soil was characterised by mechanical cone penetrometer (CPT) equipped with soundings for shear wave velocity. Tip resistance was converted to S
u values using equation 5.
Undrained shear strength profile was checked with the equation by retrieving soil samples and doing CIUC tests and results plot well on the Su profile validating the use of the equation 5. Figure 5 shows the Su profile and OCR with depth while Figure 6 shows ko with depth.
Table 1 presents the soil properties established from the SCPT sounding and the model parameters utilized in the FEM of the filed test. A convergence analysis was conducted to establish proper locations of model boundaries to minimize the effects of the rigid boundary on the stress and strain distributions. The vertical boundaries were paced at 7D from the center of the model and the bottom boundary was placed more than (3D) below the pile tip. The vertical boundaries were restricted horizontally and allowed to move vertically while the bottom boundary was fixed in all directions (i.e., x, y, and z). A medium mesh size was considered after performing the sensitivity analysis, in which the FEM comprised 25000 elements approximately. The mesh was refined within a zone of 3D adjacent to the pile to increase accuracy of results.
Figure 3 and
Figure 4 show the developed mesh.
The load-displacement curve obtained from the FE analysis is plotted in
Figure 5 along with the field data.
Figure 5 demonstrates that there is excellent agreement between the calculated and measured load-displacement curves, validating the ability of the developed finite element model to simulate the behaviour of large diameter piles installed cohesive soil. Bending moment and inclinometer data are also compared and excellent agreement is obtained as shown in
Figure 6.
The load-displacement curve obtained from the FE analysis is plotted in Figure 7 along with the tested data. Figure 7 demonstrates that there is excellent agreement between the calculated FEM and measured load-displacement curves from centrifuge testing, validating the ability of the developed finite element model to simulate the behaviour of large diameter piles installed cohesive soil. Bending moments data are also compared across various stages of testing and excellent agreement was obtained as shown in Figure 8.
Figure 6.
Displacement and bending moment data (dots) versus FE data (solid line).
Figure 6.
Displacement and bending moment data (dots) versus FE data (solid line).
1.1.2. Convergence study
Once the final set of soil parameters were defined, the convergence analysis was carried out. The purpose of this was to test the FE sensitivity to the model boundary conditions and increase accuracy of results and to define the reference geometry and mesh size that will be followed in the parametric analysis.
Figure 7 explains the dimensions studied herein while
Figure 8 displays the effects of model dimensions on displacement at mudline. In all analyses considered, the global element size was chosen to be medium, a refinement zone of 3D, 5D, and 7D were conducted with changing coarseness factor, cf. Based on the convergence analyses, the selected boundary conditions are 7D in x,y from pile centerline in all directions with refinement zone of 3D and refinement factor of 0.2 yielding approximately 25000 elements. This range in good agreement with data reported by Lai et al. (2020).
Figure 1.
Capacity of wind farms installed in Europe (EWE, 2017).
Figure 1.
Capacity of wind farms installed in Europe (EWE, 2017).
Figure 2.
Available foundation options for offshore wind turbines (a) GBF (b) monopile (c) suction caisson (d) tripod/tetrapod piles (e) tripod/tetrapod suction caissons (f) multiple foundation options (h) guys with anchors (Byrne, 2013).
Figure 2.
Available foundation options for offshore wind turbines (a) GBF (b) monopile (c) suction caisson (d) tripod/tetrapod piles (e) tripod/tetrapod suction caissons (f) multiple foundation options (h) guys with anchors (Byrne, 2013).
Figure 3.
Developed mesh and location of lateral point load.
Figure 3.
Developed mesh and location of lateral point load.
Figure 4.
Cross section showing developed mesh.
Figure 4.
Cross section showing developed mesh.
Figure 5.
Load displacement curve using Hs undrained A parameters.
Figure 5.
Load displacement curve using Hs undrained A parameters.
Figure 7.
Boundary conditions varied in convergence analyses.
Figure 7.
Boundary conditions varied in convergence analyses.
Figure 8.
Sample of convergence analysis results.
Figure 8.
Sample of convergence analysis results.
Figure 9.
The considered monopile foundation system geometric notations (Not to scale).
Figure 9.
The considered monopile foundation system geometric notations (Not to scale).
Figure 10.
load displacement curves of different lengths monopiles in a) Clay1, b) Clay6.
Figure 10.
load displacement curves of different lengths monopiles in a) Clay1, b) Clay6.
Figure 11.
Effects of relative rigidity on normalized ultimate lateral load.
Figure 11.
Effects of relative rigidity on normalized ultimate lateral load.
Figure 12.
Normalized ultimate lateral capacity versus L/D for different soil profiles considered .
Figure 12.
Normalized ultimate lateral capacity versus L/D for different soil profiles considered .
Figure 13.
Bending moment versus normalized depth for MP in soft soil (su=4.2 kPa).
Figure 13.
Bending moment versus normalized depth for MP in soft soil (su=4.2 kPa).
Figure 14.
Bending moment versus normalized depth for stiff soil (clay 6) profile.
Figure 14.
Bending moment versus normalized depth for stiff soil (clay 6) profile.
Figure 15.
Comparison of predicted and calculated utimate capacity.
Figure 15.
Comparison of predicted and calculated utimate capacity.
Table 1.
Soil properties and model parameters of case study (Zhu et al., 2017) used in validation.
Table 1.
Soil properties and model parameters of case study (Zhu et al., 2017) used in validation.
Parameter |
Clay1 |
c' |
15 |
Ψ |
0 |
φ' |
8 |
|
15 |
|
41 |
eini. |
4.23 |
ɣ, kN/m3 |
17.9 |
|
1406 |
|
1758 |
|
5000 |
vur |
0.2 |
M |
0.6 |
PI, % |
30 |
Ko,NC |
0.86 |
Rf |
0.9 |
Depth, m |
0-5 |
Type of analysis |
Undrained A |
Table 2.
Properties of considered clay profiles.
Table 2.
Properties of considered clay profiles.
Parameter |
Clay1 |
Clay2 |
Clay3 |
Clay4 |
Clay5 |
Clay6 |
c' |
4.23 |
24 |
44 |
87 |
170 |
354 |
Ψ |
0 |
0 |
0 |
0 |
0 |
0 |
θ' |
8 |
10 |
10 |
10 |
10 |
10 |
|
13 |
51 |
83 |
140 |
240 |
414 |
|
41 |
100 |
100 |
100 |
100 |
100 |
e(ini). |
4.209 |
4.209 |
4.209 |
4.209 |
4.209 |
4.209 |
ɣ, kN/m3
|
17.9 |
17.9 |
17.9 |
17.9 |
17.9 |
17.9 |
|
1406 |
3461 |
14747 |
29040 |
56628 |
113134 |
|
1758 |
4000 |
18439 |
36310 |
70805 |
141457 |
|
5000 |
10000 |
52444 |
103271 |
201380 |
402326 |
vur |
0.2 |
0.2 |
0.2 |
0.2 |
0.2 |
0.2 |
M |
0.6 |
0.6 |
0.6 |
0.6 |
0.6 |
0.6 |
PI |
30 |
30 |
30 |
30 |
30 |
30 |
Ko, NC |
0.54 |
0.54 |
0.54 |
0.54 |
0.54 |
0.54 |
Depth, m |
0-25 |
0-26 |
0-27 |
0-28 |
0-29 |
0-30 |
Rf |
0.9 |
0.9 |
0.9 |
0.9 |
0.9 |
0.9 |
Table 3.
Range of parameter analyses.
Table 3.
Range of parameter analyses.
L, m |
L/D/(Lp/W) |
Foundation system |
e/Dt
|
V, kN |
20 |
3.33 |
Monopile |
6.83 |
Own weight1
|
30 |
5 |
6.83 |
40 |
6.67 |
6.83 |
50 |
8.33 |
6.83 |
60 |
10 |
6.83 |
70 |
11.67 |
6.83 |
80 |
13.33 |
6.83 |