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In this contribution, we consider two applications in which probabilistic approaches can potentially complement or enhance the design and assessment of offshore wind turbine foundations. First, we illustrate in a numerical example that probabilistic modelling can be helpful in dealing with chang-es in turbine locations during the planning phase of an offshore wind farm. In this case, spatial probabilistic modelling of the ground conditions enables (a) an inference of the soil properties at the modified turbine location from field data collected at different locations across an offshore wind farm site and (b) an optimisation of further site investigations. Second, we discuss the uncer-tainties and risks associated with the installation of large diameter monopiles in soils with hetero-geneities such as strong layers and/or embedded boulders. Subsequently, we present a concept for modelling, understanding, and managing these risks based on a probabilistic model of the subgrade conditions, monopile, and subgrade-pile-interaction.
This article presents a solid cohesion model for the simulation of bonded granular assemblies in the frame of 3D discrete element approaches (DEM). A simple viscoplastic cohesion model for 2D geometries is extended to 3D conditions, while its yield criterion is generalized as a hyper-surface in the space of bond solicitations to include torsional moments. The model is then calibrated using experimental results of uniaxial traction at both the microscopic and macroscopic scales with an artificial granular cohesive soil. The paper finally presents some simulated results on the macromechanical sample traction application and briefly discusses the model's current limitations and promising prospects for subsequent works.
The shaft bearing capacity often plays a dominant role for the overall structural behaviour of axially loaded piles in offshore deep foundations. Under cyclic loading, a narrow zone of soil at the pile-soil interface is subject to cyclic shearing solicitations. Thereby, the soil may densify and lead to a decrease of confining stress around the pile due to microphenomena such as particle crushing, migration and rearrangement. This reduction of radial stress has a direct impact on the shaft capacity, potentially leading in extreme cases to pile failure. An adequate interface model is needed in order to model this behaviour numerically. Different authors have proposed models that take typical Interface phenomena in account such as densification, grain breakage, normal pressure effect and roughness. However, as the models become more complex, a great number of material parameters need to be defined and calibrated. This paper proposes the adoption and transformation of an existing soil bulk model (Pastor- Zienkiewicz) into an interface model. To calibrate the new interface model, the results of an experimental campaign with the ring shear device under cyclic loading conditions are here presented. The constitutive model shows a good capability to reproduce typical features of sand behaviour such as cyclic compaction and dilatancy, which in saturated partially-drained conditions may lead to liquefaction and cyclic mobility phenomena.
The aim of an ongoing research project is to develop a design approach for typical offshore driven piles (e.g. Jacket piles) based on the application of injections by compaction grouting directly at the pile shaft. The paper aims to present the results of laboratory and in-situ tests, which reveal the efficiency and the promising potential of the optimised foundation concept for a more economic dimensioning of pile foundations and to increase their bearing capacity in non-cohesive soil at any moment after installation.
Monopiles are currently the predominant foundation type for offshore wind turbines in Europe. Due to the increasing dimensions of the turbines, pile diameters beyond 10m become necessary. A design-relevant failure mode of monopiles is the local buckling of the pile wall in the embedded sections. Relevant buckling guidelines do not consider the soil-structure interaction specifically, although the embedment may allow for a reduction of wall thickness. However, Eurocode-based design concepts require a validation with comparative buckling cases for validation, either in terms of buckling curve parameters for both the algebraic stress-based and semi-numerical LBA/MNA design concept or as a calibration factor kGMNIA for fully numerical GMNIA calculations. These parameters are not yet available for embedded shells. To close this gap, we have conducted experiments on piles embedded in sand to investigate local buckling under soil-structure-interaction. The results will be used to calibrate numerical models. This research was carried out as part of the VERBATIM research project, funded by PTJ/BMWK and supported by the Carbon Trust's Offshore Wind Accelerator consortium.
Quantifying uncertainties in subsurface properties and stratigraphy can lead to better understanding of the ground conditions and enhance the design and assessment of geotechnical structures. Several studies have utilized Cone Penetration Test (CPT) data and employed Bayesian and Machine Learning methods to quantify the geological uncertainty, based on the Robertson’s soil classification charts and the Soil Behaviour Type Index (Ic). The incorporation of borehole data can reduce the stratigraphic uncertainty. Significant challenges can arise, however, mainly due to the intrinsic differences between field and laboratory-based soil classification systems, which can potentially lead to inconsistent soil classification. To this end, this study proposes a multivariate Gaussian Process model that utilizes site-specific data and: i) jointly models multiple categorical (USCS labels) and continuous (Ic) variables, ii) learns a (shared) spatial correlation structure and the betweenoutputs covariance, and iii) produces two types of dependent classification outputs. The results indicate that the integration of geotechnical and geological information into a unified model can provide more reliable predictions of the subsurface stratification, by allowing simultaneous interpretation of USCS and Ic profiles. Importantly, the model demonstrates the potential to integrate multiple variables of different types, aiming to contribute to the development of a methodology for joint modeling of geotechnical, geological and geophysical data.