7.2 Ingenieurbau
Filtern
Dokumenttyp
- Vortrag (170) (entfernen)
Referierte Publikation
- nein (170) (entfernen)
Schlagworte
- Structural Health Monitoring (16)
- Offshore wind energy (9)
- Ground vibration (8)
- Brücken (7)
- Fatigue (7)
- Offshore (7)
- Design methods (6)
- Physical phenomenology (6)
- Pile foundations (6)
- Structural health monitoring (6)
Organisationseinheit der BAM
- 7.2 Ingenieurbau (170) (entfernen)
Der Vortrag stellt die Durchführung und die ersten Ergebnisse der Belastungsfahrten der BAM im Rahmen des AISTEC Projekts an der Maintalbrücke am 19.05. und 20.05.2021 vor. Es wurden Tragwerksreaktionen des Bauwerks mit dem installierten Dauermonitoringsystem und insbesondere dem Betongelenk mit zusätzlich installierter Sensorik aufgezeichnet. Für die Ermittlung der Lastposition wurden mehrere Verfahren eingesetzt und verglichen.
Identifying optimal inspection and repair strategies for offshore jacket structures is a challenging task. We pre-sent an approach, which is based on recent developments in the field of risk-based operation and maintenance planning at the structural system level. The approach utilizes heuristics to define inspection and repair strate-gies at the system level and to reduce the search space of possible strategies. For each defined strategy, the expected service life cost of inspection, repair and failure is evaluated based on simulated inspection and re-pair histories. Subset simulation is applied to compute the conditional repair and failure probabilities required for this analysis. It also forms the basis for simulating inspection and repair histories. The strategy that mini-mizes the expected service life cost is the optimal one in the set of pre-selected strategies. The underlying condition and performance model accounts for the stochastic dependence among the deterioration states of the different structural elements and the structural redundancy. The approach is demonstrated in a case study considering a jacket-type frame. In this study, we essentially vary the inspection interval, the minimum num-ber of inspected components and the target reliability, and identify the combination that minimizes the ex-pected total service life cost.
In this presentation, a framework for integrating vibration-based structural health monitoring data into the optimization of inspection and maintenance of deteriorating structural systems is presented. The framework is demonstrated in an illustrative example considering a steel frame subject to fatigue.
The passage of the train is dominated by the impulses of the static axle loads. The response of the regular homogeneous and irregular soils has been calculated by the finite-element method in frequency domain. The superposition of the impulse responses yields the quasi-static component of the ground vibration which is restricted to very low frequencies and to the close near-field of the track. In case of an irregular soil or ballast of which the stiffness varies randomly in space, a mid-frequency ground vibration component is generated by the scattering of the axle impulses. Measurements will be shown which prove the existence of the mid-frequency ground vibration component and the unique explanation by the scattered axle impulses: many international measurements with a raised mid-frequency component, axle-box measurements with a too low mid-frequency dynamic load, amplitude-speed dependencies which are incompatible with irregularity-induced dynamic loads, and ground vibration reductions due to stiff track elements.
Driven steel piles are commonly used as deep foundations for a wide range of engineering structures, particularly in the offshore branch. They are also an interesting example among the broad spectrum of geotechnical applications where the fluid-solid interaction at the pore-scale can play a major role for the macromechanical behaviour of the whole system.
In the context of the geotechnical practice for offshore wind-farm structures, both the industrial design and the actual dimensions of the large piles used as foundations in the seabed are often driven by factors such as the soil resistance to driving (SRD), which are still not well understood and often estimated based on mere empirical correlations or overly simplified one-dimensional models. In particular, the role of the micromechanical effects during the installation process (e.g. local dilatancy or contractancy) and their consequences on the pore pressure levels at the pile-tip and on the effective resistance to driving, are generally either disregarded or at most assumed to be covered by the simplified engineering “black-box” solutions.
Here, we propose a general framework to address such local aspects of a geotechnical application involving fluid-saturated soils while retaining the focus on the micro-scale phenomena. We advocate for an approach that combines the relative simplicity of the Discrete Element Method (DEM) for the solid mechanics with the capabilities of the Lattice Boltzmann Method (LBM) for the fluid dynamics. In this sense, we aim to compile some useful techniques and practical recommendations for an efficient GPU-based implementation of a micromechanical LBM-DEM simulation tool.
The response of many geotechnical systems, whose structural behavior depends on shearing effect, is closely related to soil structure interaction phenomenon. Experimentally it is found that the localisation of these effect happens at a narrow soil layer next to the structure. Numerically, this behavior can be modelled through interface elements and adequate constitutive models. In this work, a constitutive model in the framework of Generalized Plasticity for sandy soils has been chosen to be adapted for the interface zone.
From the direct shear experiments a sandy soil at loose and dense states under different normal pressures is considered. The adapted constitutive model is able to reproduce contraction and dilatation of the soil according to its relative density and it shows a good agreement with the experimental data.
Support structures of wind turbines in German offshore wind farms are regularly inspected. Currently, inspection outcomes are generally not systematically recorded. This prevents their consistent handling and processing, which is a key requirement to enable an efficient structural integrity management. As part of the DiMoWind-Inspect project, a data model and reference designation system for such inspection results is developed to facilitate their identification, localization, quantification, tracing and linking throughout the lifetime of a wind farm and beyond. The inspection results together with structural health monitoring results and information on repairs form the basis for assessing and predicting the structural condition, estimating the remaining lifetime, and planning of future inspections, structural health monitoring, and repairs. As a basis for developing a digital structural integrity management, a generic framework is proposed in this paper, which describes the stakeholders, data, models, processes and workflows of the integrity management of support structures in offshore wind farms and their interrelations. The framework adopts a building information modelling approach to describe the information relevant to the structural integrity management. The central digital space of the framework is a common data environment. An implementation of the framework will enable a digital structural integrity management in which inspection, structural health monitoring, repair, assessment and planning outcomes generated throughout the life cycle of a wind farm can be consistently collected, managed, shared and processed by the relevant shareholders.
The new crack luminescence method offers the possibility of making fatigue surface cracks in metallic materials more visible during inspections through a special coating system. This coating system consists of two layers, whereby the first layer has fluorescent properties and emits visible light as soon as it is irradiated by UV light. The top layer is black and is designed to prevent the fluorescent layer from emitting if no crack develops in the underlying material.
The technique proved particularly useful in a wide variety of fatigue tests of steel components under laboratory conditions. Moreover, it has the potential to be used in various industrial applications. To enable industrial deployment and integration into maintenance strategies, a concept study is developed in this contribution, resulting in a qualification framework that can serve as a foundation for determining the reliability of the crack luminescence system in terms of a probability of detection curve. Within this study, factors causing measurement variability and uncertainty are being determined and their influences assessed. Due to the extension of the system by a moving computer vision system for automated crack detection using artificial intelligence, additional long-term effects associated with structural health monitoring systems need to be incorporated into an extended probability of detection study as part of the technical justification.
Finally, important aspects and findings related to design of experiments are discussed, and a framework for reliability assessment of a new optical crack monitoring method is presented, emphasizing the influence of various uncertainty parameters, including long-term effects such as system ageing.
We present our approach and methodology for simulating piping erosion, which occurs during the installation process of suction bucket foundations for offshore wind turbines. We show several simulations and analyze the hydrodynamic and contact forces acting on the granular fabric and the differential pressure of the fluid phase. We demonstrate weak scaling performance on the LUMI supercomputer with a parallel efficiency of up to 90% for 4096 Graphics Compute Dies.
The aim of the study is to infer the soil stratification from the provided CPT and borehole data. We infer the soil type at any location within the domain of interest from the SBT index Ic (Robertson, 2009). This index can be directly related to the CPT data through an empirical correlation model. In addition, the soil classes contained in the borehole logs can be expressed as bounds on Ic. A log-transformation was applied to Ic, Y = ln(Ic), and Y was modelled by a 3D Random Field, with a fully Bayesian hierarchical Gaussian Process model to explicitly capture uncertainties.