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Eingeladener Vortrag
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Dieser Artikel enthält aktuelle Forschungsergebnisse im Bereich des überwachungsgestützten Managements der Tragwerksintegrität. Das Management der Tragwerksintegrität hat zum Ziel, die Funktionalität eines Tragwerks während des gesamten Lebenszyklus durch Einhaltung der Zielzuverlässigkeiten sicherzustellen. Ausgehend von Forschungsergebnissen über die Charakteristik von Überwachungsverfahren und -daten im Rahmen von Zuverlässigkeitsanalysen, wird ein Ansatz vorgestellt, wie die erwarteten Kosten für das Management der Tragwerksintegrität durch Überwachungsverfahren optimiert werden können. Dazu wird eine Kosten-Nutzen-Analyse für den Lebenszyklus einer Gründungstruktur von Offshore-Windenergieanlagen durchgeführt. Im Rahmen der Bayes'schen Entscheidungstheorie werden durch eine Prä-posteriori-Entscheidungsanalyse die optimalen Entscheidungsparameter für den Entwurf eines Überwachungssystems bestimmt. Als Fallstudie wird ein Überwachungssystem für die Gründungsstruktur eines Multibrid-M5000-Prototyps konzipiert und die mögliche Reduktion der Risiken und erwarteten Betriebskosten quantifiziert. --------------------------------------------------------------------------------------------------------------------------------------------------------------------
This paper contains recent research results in the field of monitoring supported structural integrity management. The structural integrity management aims at ensuring the functioning of a structure throughout the life cycle by compliance with the target reliabilities. Building upon research results concerning the characteristics of monitoring techniques and data within the framework of reliability analyses, an approach is introduced for the optimisation of the expected structural integrity management costs by monitoring information. For this aim, a life cycle cost benefit analysis for offshore wind turbine support structures is formulated. The optimal monitoring decision parameters are then assessed utilizing the Bayesian pre-posterior decision theory. As a case study a monitoring system for a Multibrid M5000 offshore wind turbine prototype support structure is designed and possible reductions of the risks and expected costs are quantified.
This paper establishes the model basis regarding the ultimate limit state consisting of structural, loading, and probabilistic models of the support structure of offshore wind energy converters together with a sensitivity study. The model basis is part of a risk based assessment and monitoring framework and will be applied for establishing the 'as designed and constructed' reliability as prior information for the assessment and as a basis for designing a monitoring system. The model basis is derived considering the constitutive physical equations and the methodology of solving these which then in combination with the ultimate limit state requirements leads to the specific constitutive relations. As a result finite element models based on shell elements incorporating a structural and a loading model are introduced and described in detail. Applying these models the ultimate capacity of the support structure and the tripod structure are determined with a geometrically and materially nonlinear finite element analysis. The observed failure mechanisms are the basis for the definition of the ultimate limit state responses. A probabilistic model accounting for the uncertainties involved is derived on the basis of literature review and measurement data from a prototype Multibrid M5000 support structure. In combination with the developed structural and loading models, sensitivity analyses in regard to the responses are performed to enhance the understanding and to refine the developed models. To this end, as the developed models necessitate substantial numerical efforts for the probabilistic response analysis predetermined designs of numerical experiments are applied for the calculation of the sensitivities using the Spearman rank correlation coefficient. With this quantification of the sensitivity of the random variables on the responses including nonlinearity the refinement of the model is performed on a quantitative basis.