7.2 Ingenieurbau
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Die Anwendung von Leichtbauprinzipien im Stahlbau, wie z.B. die Verwendung von aufgelösten Tragstrukturen, sog. Jackets-Fundamenten, bietet ein großes Potential zur Reduzierung des Ressourcenverbrauchs, insbesondere im Hinblick auf die benötigte Stahlmenge.
In diesem Vortrag zeigen wir die Potenziale einer vollständigen Digitalisierung der schweißtechnischen Fertigungs- und Prüfkette auf, um eine vollautomatische Fertigung sowie Qualitätsprüfung von Rohrknoten als Schlüsselelement von Jackets-Fundamenten zu ermöglichen. Darüber hinaus wird der Zusammenhang zwischen der Geometrie der Nahtform und der resultierenden Ermüdungsfestigkeit durch numerische Methoden unter Einbeziehung bionischer Prinzipien bewertet. Es wird gezeigt, dass Hohlprofilknoten vollautomatisch unter Berücksichtigung von Geometrietoleranzen geschweißt werden können. Darüber hinaus konnte die Nahtform gemäß den numerischen Modellen hergestellt werden, was ein großes Potenzial für eine verlängerte Lebensdauer bietet. Anschließend werden die Verbesserungen bei der Ressourceneffizienz und die Reduzierung der Kohlendioxidemissionen durch eine Lebenszyklusanalyse bewertet.
Structural health monitoring (SHM) intends to improve the management of engineering structures. The number of successful SHM projects – especially SHM research projects – is ever growing, yielding added value and more scientific insight into the management of infrastructure asset. With the advent of the data age, the value of accessible data becomes increasingly evident. In SHM, many new data-centric methods are currently being developed at a high pace. A consequent application of research data management (RDM) concepts in SHM projects enables a systematic management of raw and processed data, and thus facilitates the development and application of artificial intelligence (AI) and machine learning (ML) methods to the SHM data. In this contribution, a case study based on an institutional RDM framework is presented. Data and metadata from monitoring the structural health of the Maintalbrücke Gemünden for a period of 16 months are managed with the RDM system BAM Data Store, which makes use of the openBIS data management software. An ML procedure is used to classify the data. Feature engineering, feature training and resulting data are performed and modelled in the RDM system.
Remediation of Cracks Formed in Grouted Connections of Offshore Energy Structures under Static Loads
(2018)
The future energy demand necessitates the exploration of all potential energy sources both onshore and offshore. Global trend has shifted towards offshore energy, which can be obtained from either carbon intensive or renewable options, hence requiring structures such as rigs, platforms, and monopiles. Most of these structures adopt easily installable construction techniques, where lower foundation need to be connected with the super structure by mean of grouted composite joints. Generally, these composite connections have exterior sleeve, interior pile and infill grout. Being located in remote offshore conditions, connections can experience considerable adverse loading during their lifetimes. Degradations were reported inside similar connections, which were installed in last three decades. Besides, grouting in the offshore sites may often be proven difficult, which eventually leads to reduced capacity of connections in the long run. Thus, repair and rehabilitation of such connections should be planned ahead to minimize operational delays and costs in the future. This study aims at characterizing the nature of crack generation in grouted connections and thereby identifying the potential of repair using suitable repair material. Scaled grouted joints were manufactured using a novel mold, and connections were loaded under static load to visualize the main failure pattern. The failure mechanism and loading capacity are found compatible to previous results from earlier literature. Grouted connection was then repaired using cementitious injectable grout. The effectiveness of the repair system is also discussed.
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.
Grouted connections are intensively used in offshore rigs, platforms as well as jacket and monopile offshore wind turbine structures. Being located in remote offshore conditions, these connections can experience considerable adverse loading during their lifetimes. Degradation was reported inside similar connections, which were installed in the last three decades. Grouting in the offshore sites may often be proven difficult, which eventually leads to reduced load-bearing capacity of connections in the long run. Thus, repair and rehabilitation of such connections should be planned ahead to minimize operational delays and costs. In this study, scaled grouted connections were manufactured using a novel mould, whose integrity were monitored using digital image correlation (DIC). The connections were loaded under static load to visualize the main failure pattern using distributed fibre optic sensors and acoustic emission (AE) analysis. Grouted connections were then repaired using a cementitious injectable grout. The effectiveness of the grout injection was monitored using dye penetration technique. Finally, specimens are reloaded to identify the potential of such repair for grouted connections.
A significant number of new wind farms has to be installed and, at the same time, existing wind farms reaching the end of their planned life need to be reused efficiently to ensure that the ambitous goals for deploying offshore wind are met. Some relevant reuse alternatives for offshore wind farms are lifetime extension, repowering utilizing existing substructures and full replacement. In this presentation - starting from experience gained from extending the lifetime of the of the U1 metro viaduct in Berlin - we discuss end-of-life decision making in offshore wind. We focus particularly on issues concerning substructures and highlight existing challenges and opprtunities in research and development.
Information on the condition and reliability of an offshore jacket structure provided by a vibration-based structural health monitoring system can guide decisions on inspection and maintenance. When selecting the sensor setup, the designer of the monitoring system must assess its overall benefit compared to its costs before installation. The potential benefit of continuously monitoring the dynamic response of a jacket structure can be formally quantified through a value of information analysis from Bayesian decision theory. In this contribution, we present a framework for optimizing the placement of vibration sensors on offshore jacket structures by maximizing the value of information of the monitoring system. To solve the resulting discrete optimization problem, we adapt a genetic algorithm. The framework is demonstrated in a numerical example considering a redundant jacket-type steel frame. The numerical study shows that monitoring the vibration response of the frame is beneficial. Good sensor setups consist of relatively few sensors located towards the upper part of the
frame. The adapted genetic algorithm performs similarly well as established sequential sensor placement algorithms and holds substantial promise for application to real jacket structures.
A digital structural integrity management of offshore structures enables an optimized planning of inspections and repairs with risk-based methods. In a risk-based approach, the inspection and repair strategy that minimizes the expected lifetime costs consisting of the expected inspection, repair and failure costs is determined. In addition to inspections, information on the structural condition can be continuously obtained by monitoring the vibration response of the structural system. Changes in the vibration characteristics quantified in terms of modal properties can be an indication of structural damage. In risk-based inspection and repair planning, the effect of monitoring results is determined via Bayesian updating of the structural condition and reliability. This information should be applied to inform decisions on inspections and may result in a reduced inspection effort. The benefit of continuously monitoring the structural health can be quantified in terms of the value of information, which corresponds to the difference between the expected lifetime costs with and without monitoring. In this work, we demonstrate in a numerical example how an optimized sensor placement for a vibration-based structural health monitoring system can be determined by maximizing the value of information.