Large diameter, short monopiles are the preferred foundation type for offshore wind turbines. These piles demonstrate a rigid response with significant rotation of the pile base under ultimate lateral load. As traditional empirical p-y curves used in lateral loaded pile analysis have been derived from tests on small diameter onshore piles, there is some doubt about their applicability to rigid monopiles, particularly in view of the significant difference in the response of the pile base compared with a typical onshore pile. To address this issue, this paper reports on a unique series of field tests using instrumented driven pipe piles, complimented by numerical analysis, which was performed to examine explicitly the contribution of the pile base to the response under lateral load. The field tests, which included tests on pipe piles that had the sand plug removed to below pile tip level prior to testing, confirmed that the influence of the base on the lateral response for the tested 273- and 457-mm-diameter piles was negligible. Numerical analyses that were calibrated using the field test data showed that the contribution of the base to the lateral capacity of a monopile with a diameter as large as 10 m is negligible. Results also indicated that p-y curves are not affected by the length to diameter ratio and can be used to predict the response of monopiles in sand.

The influence of two-phase flows containing suspension particles, which are common in nature, on internal erosion with coupling effect of clogging remains unclear. This paper presents a three-dimensional coupled computational fluid dynamics and discrete element method (CFD–DEM) analysis of internal erosion considering different concentrations of suspension C (i.e., mass of the suspended particles in unit volume of fluid) in gap-graded granular soils with different fine fraction F_c (i.e., the percentage by mass of the fine particles in the gap-graded sample). The influences of C and F_c on the erosion and clogging behavior of soils are investigated from both the macroscopic and microscopic perspectives. It is found that for gap-graded samples being underfilled with F_c = 15%, the suspension flow (i.e., influent fluid with suspending particles) decreases the cumulative eroded fine particle loss and the increasing rate of soil hydraulic conductivity due to clogging at the top of the sample. The degree of clogging is found to jointly be determined by both constriction size distribution and the suspension concentration. Clogging in a local area usually occurs with the formation of the clusters, which have a high resistance to the drag force applied by the fluid flow.

Scouring of soil around large-diameter monopile will alter the stress history, and therefore the stiffness and strength of the soil at shallow depth, with important consequence to the lateral behavior of piles. The existing study is mainly focused on small-diameter piles under scouring, where the soil around a pile is analyzed with two simplified approaches: (I) simply removing the scour layers without changing the strength and stiffness of the remaining soils, or (II) solely considering the effects of stress history on the soil strength. This study aims to investigate and quantify the scour effect on the lateral behavior of monopile, based on an advanced hypoplastic model considering the influence of stress history on both soil stiffness and strength. It is revealed that ignorance about the stress history effect (due to scouring) underestimates the extent of the soil failure wedge around the monopile, while overestimates soil stiffness and strength. As a result, a large-diameter pile (diameter D = 5 m) in soft clay subjected to a souring depth of 0.5 D has experienced reductions in ultimate soil resistance and initial stiffness of the p-y curves by 40% and 26%, and thus an increase of pile head deflection by 49%. Due to the inadequacy to consider the stress history effects revealed above, the existing approach (I) has led to non-conservative estimation, while the approach (II) has resulted in an over-conservative prediction.