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Offshore-Pfähle in Mehrpfahlgründungsstrukturen wie Jacket-Gründungen müssen nach der Rammung überwiegend zyklisch axialen Belastungen widerstehen. Die Abmessungen der Pfähle werden sowohl von der inneren Tragfähigkeit und dem Ermüdungsverhalten des Stahlquerschnittes als auch von der äußeren Tragfähigkeit und der Pfahl-Boden-Interaktion bestimmt. Aufgrund der großen Zahl von Pfahlgründungen, die für aktuelle und zukünftige Windparkprojekte benötigt werden, besteht ein dringender Bedarf, die Dimensionierung und die damit verbundenen Kosten des Einzelpfahles zu optimieren. Bezüglich der Pfahltragfähigkeit sind wichtige aktuelle Forschungsthemen eine mögliche Traglaststeigerung durch Anwachsen und die geeignete Abschätzung der zyklischen Degradation. Zur Untersuchung beider Effekte wurde eine großmaßstäbliche Versuchsanlage auf dem Testgelände BAM TTS in Horstwalde nahe Berlin errichtet. Auf diesem Versuchsfeld können große Stahlrohrammpfähle zyklisch druck- und zugbelastet werden. Zudem kann die Untersuchung von Alterungseffekten durch zeitlichen Versatz zwischen den Messkampagnen untersucht werden. Erste Ergebnisse zeigen einen Anstieg der Pfahltragfähigkeit bis zu ca. 60 % nach einer Standzeit von ca. 18 Monaten. Für die Degradation der Tragfähigkeit der zyklisch belasteten Pfähle zeigen die ersten vorläufigen Ergebnisse ein zum Teil unerwartetes Verhalten. Zusätzliche Untersuchungen werden derzeit zur weiteren Abklärung durchgeführt.
The focus of this study is the experimental characterization of cemented granular materials, with the aim of identifying the microscopic properties of the solid bonds and describing the extension to macroscopic mechanical strength of cemented samples.We chose to use artificially bonded granular materials, made of glass beads connected by solid paraffin bridges. The results of several sets of laboratory tests at different scales are presented and discussed. Micromechanical tests investigate the yield strength of single solid bonds between particles under traction, shearing, bending and torsion loading, as a function of variations in particle size, surface texture and binder content. Macro-scale tensile tests on cemented samples explore then the scale transition, including influence of confining walls through homothetic variations of the sample size. Despite the large statistical dispersion of the results, it was possible to derive and validate experimentally an analytical expression for micro tensile yield force as a function of the binder content, coordination number and grain diameter. In view of the data, an adhesive bond strength at the contact between bead and solid bond is deduced with very good accuracy and it is even reasonable to assume that the other threshold values (shear force, bending and torsion moments) are simply proportional to the tensile yield, thus providing a comprehensive 3D model of cemented bond. However, the considerable dispersion of the data at the sample scale prevents validation of the extended model for macroscopic yield stress. A final discussion examines the various factors that may explain intrinsic variability. By comparison with other more realistic systems studied in the literature in the context of bio-cementation, our artificial material nevertheless appears suitable for representing a cemented granular material. Being easy to implement, it could thus enable the calibration of discrete cohesion models for simulation of practical applications.
Current supercomputers often have a heterogeneous architecture using both conventional Central Processing Units (CPUs) and Graphics Processing Units (GPUs). At the same time, numerical simulation tasks frequently involve multiphysics scenarios whose components run on different hardware due to multiple reasons, e.g., architectural requirements, pragmatism, etc. This leads naturally to a software design where different simulation modules are mapped to different subsystems of the heterogeneous architecture. We present a detailed performance analysis for such a hybrid four-way coupled simulation of a fully resolved particle-laden flow. The Eulerian representation of the flow utilizes GPUs, while the Lagrangian model for the particles runs on conventional CPUs. Two characteristic model situations involving dense and dilute particle systems are used as benchmark scenarios. First, a roofline model is employed to predict the node level performance and to show that the lattice-Boltzmann-based Eulerian fluid simulation reaches very good performance on a single GPU. Furthermore, the GPU-GPU communication for a large-scale Eulerian flow simulation results in only moderate slowdowns. This is due to the efficiency of the CUDA-aware MPI communication, combined with the use of communication hiding techniques. On 1024 A100 GPUs, an overall parallel efficiency of up to 71% is achieved. While the flow simulation has good performance characteristics, the integration of the stiff Lagrangian particle system requires frequent CPU-CPU communications that can become a bottleneck, especially when simulating the dense particle system. Additionally, special attention is paid to the CPU-GPU communication overhead since this is essential for coupling the particles to the flow simulation. However, thanks to our problem-aware co-partitioning, the CPU-GPU communication overhead is found to be negligible. As a lesson learned from this development, four criteria are postulated that a hybrid implementation must meet for the efficient use of heterogeneous supercomputers.
Accurate prediction of subsurface stratigraphy and geotechnical properties, along with quantification of associated uncertainties, is essential for improving the design and assessment of geotechnical structures. Several studies have utilized indirect data from Cone Penetration Tests (CPTs) and employed statistical and Machine Learning methods to quantify the geological and geotechnical uncertainty. Incorporating direct borehole data can reduce uncertainties. This study proposes a computationally efficient multivariate Gaussian Process model that utilizes site-specific data and: (i) jointly models multiple categorical (USCS labels) and continuous CPT variables, (ii) learns a non-separable covariance structure leveraging the Linear Model of Coregionalization, and (iii) predicts a USCS based stratigraphy and CPT parameters at any location within the 3D domain. The results demonstrate that integrating geotechnical and geological data into a unified model yields more reliable predictions of subsurface stratification, enabling the parallel interpretation of both USCS classification and CPT profiles. Importantly, the model demonstrates its potential to integrate multiple variables from different sources and data types, contributing to the advancement of methodologies for the joint modeling of geotechnical, geological, and geophysical data.
The saturated sand surrounding an offshore pile
foundation under quasi-static cyclic lateral load can show the
physical phenomena of macromechanical densification and
convective granular flow. Based on the results from physical
model tests at different geometrical scales, this paper
provides a certain quantification of such phenomena and discusses
their causes and consequences. The progressive sand
densification leads to subsidence of the soil surface and a significant
stiffening of the pile behaviour. Conversely, the ratcheting
convective motion of two closed cells of soil beneath
the pile-head is responsible for an endless grain migration at
the soil surface, the inverse grading of the convected material
and a direct shear of the sand at the distinct boundary of the
revolving soil domain. In this respect, and from a macromechanical
perspective considering the soil as a continuum, it
appears that the convecting material tends to follow gradient
lines of shear stress during its ratcheting motion. Concluding
the paper, the practical relevance of these phenomena and
their extrapolation to other conditions are briefly discussed.
Pore-Pressure Accumulation and Soil Softening around Pile Foundations for Offshore Wind Turbines
(2012)
This article deals with the relevance and practical feasibility of micromechanical simulations for their application to general geomechanical problems involving fluid-saturated granular assemblies, whether frictional or cohesive. A set of conceptual and numerical tools is here presented, advocating for a parallel computation using graphical processing units (GPUs) to treat large numbers of degrees of freedom with conventional Desktop computers. The fluid phase is here simulated with a particle-resolved approach in the frame of the Lattice Botzmann Method (LBM) while the granular solid phase is modelled as a collection of discrete particles from a Molecular Dynamics DEM perspective. The range of possible material behaviours for the solid granular phase is intended here to cover a broad spectrum from purely frictional to viscous cohesive materials with either brittle or transient debonding features. Specific details of the implementation and some validation cases are put forward.
Finally, some exemplary applications in the fields of soil erosion and geotechnical profile installation are provided along with a discussion on the parallel performance of the presented models. The results show that a micromechanical approach can be feasible and useful in practice, providing meaningful insights into complex engineering problems like the erosion kinetics of a soil under an impinging jet or the penetration resistance of a deep foundation in a layered soil profile.
Large-diameter monopiles are the most common foundation structures for offshore wind turbines. One relevant failure mode during installation is plastic failure of the pile tip which may increase progressively during further driving (pile tip buckling; extrusion buckling). This paper presents the details and results of a large-scale field-test campaign with dynamic pile installation for the validation and calibration of different numerical approaches concerning pile-tip buckling phenomena. The phenomenology of observed pile-tip failures is here described in detail and a first quantitative approach is evaluated based on the field-test data. As the number of new projects continues to grow and the necessity to construct wind farms in challenging terrain increases, such field data-sets will become increasingly relevant.
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.
Tip damage of monopiles from boulder collisions during installation has emerged as a critical design issue, primarily due to the combination of the widespread use of large-diameter piles and the complexity of the ground conditions at the available sites. Recently, a framework relating potential pile tip damage to cone tip resistance from Cone Penetration Tests (CPTs) has been proposed in the literature. Gaussian processes are powerful stochastic models that enable probabilistic spatial interpolation of soil data at any location within a site. On this basis, this study utilizes sparse CPT data from a site in the North Sea, to first develop an efficient Gaussian process regression model, which is used to derive a three-dimensional (3D) probabilistic predictive map of the cone tip resistance. Assuming deterministic loading conditions and a factual collision with a boulder of pre-defined properties, the cone tip resistance predictive model is subsequently used for a probabilistic preliminary assessment of potential pile tip damage. Results of the analysis are realistic 3D probability maps of potential damage that aim to support engineering judgment and contribute towards cost-effective site investigation planning and offshore wind farm design.