TY - CONF A1 - Eichner, Lukas T1 - Design of offshore jacket support structure for experimental fatigue life evaluation N2 - One crucial metric of interest to wind farm operators is the remaining useful life (RUL) of single components, wind turbines, or even entire wind farms. Occasionally, questions arise regarding how to operate a turbine, even in the presence of manufacturing or design errors, which from a computational design standpoint reduce the remaining lifetime below the intended service life. A typical measure involves adapting the monitoring and inspection plan. Using such a maintenance plan, the author intends to simulate the lifetime of jacket-type structure in a fatigue test. The objective of the experiment is to demostrate that systems like three-dimensional jackets possess redundancies that enable reliable continued operation, despite the reduced fatigue life of individual components due to technical flaws, if an appropriate maintenance concept is in place. This presentation discusses the steps leading to the procedure of the experiment including the design process and the maintenance planning. T2 - 19th eawe PhD Seminar CY - Hannover, Germany DA - 06.09.2023 KW - Offshore wind energy KW - Jacket support structure KW - Simulation and experiment KW - Structural integrity management KW - Risk-based maintenance planning PY - 2023 AN - OPUS4-58240 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Eichner, Lukas T1 - LUKAS’ JACKET: A test structure for model and monitoring based lifetime management of offshore jacket support structures N2 - The goal of the experiments is to demonstrate that systems like three-dimensional jackets possess redundancies that, despite the reduced fatigue life of individual components, enable reliable operation if an appropriate maintenance concept is in place. In practice, individual potentially faulty components in the structure have been handled conservatively so far. To move away from this approach, methods and strategies in the field of life cycle management that enable economically optimal and reliable operation must be transferred from scientific research to practice. Experiments are the preferred method to establish the proof of concept. To realistically simulate the operational lifetime of a jacket structure through an experiment, cyclic loads must be applied to the structure to replicate typical fatigue processes. To ensure that the test structure is not a "disposable product" and can undergo multiple test cycles, the experimental concept includes system-level and component-level tests. The latter are conducted on removable joints. These elements at the nodes of the structure have been manufactured in multiple variations, both to potentially contain mentioned flaws and to undergo more load cycles individually than the main structure. Once the removable joint is sufficiently pre-damaged and thus the reduced remaining fatigue life is established, the element is inserted into the overall structure. The defined maintenance strategy is then implemented on the entire system. This strategy consists of structural health monitoring (SHM), inspections, and repairs. At defined intervals, cyclic loading is interrupted to apply dynamic loads. Using the installed monitoring system and coupled operational modal analysis (OMA), the modal parameters of the structure are determined, which can help identify potential system damage. Optimal sensor placement (OSP) can be determined based on a maximum value of information (VoI) across the entire pre-posterior predicted service life. For detailed investigations at the hotspots, inspections are conducted using non-destructive methods, among others. Overall global and local information about the structure's condition is gathered these methods, which are then incorporated into models describing the structure through Bayesian updating. This allows for initial system identification based on different system responses and later updating of the predicted parameters of analytical and numerical models. Utilizing the updated models, decisions regarding maintenance actions, such as further inspections or repairs, are made, which are subject to uncertainties. The probabilistic models enable a reliability- and risk-based maintenance strategy, where, for example, maximum failure rates can act as triggers for maintenance actions. These decisions are relevant for the planned duration of the simulated operational lifetime, as well as for potential lifetime extensions, which are currently of significant importance in practice. Optimizing the maintenance strategy for the operational lifetime of the structures with these methods will lead to a higher utility of the offshore wind farm. The work associated with the test structure encompasses a variety of topics (including fatigue, damage detection and identification, reliability, Bayesian updating, system identification, SHM, maintenance planning, decisions under uncertainties), which are integrated through corresponding models and methods. All these models have been and are being applied in the numerical accompaniment of the experiments. By applying them to a structure that includes the relevant locations and aspects of real-world structures, both well-functioning and suboptimal parts of the established framework will be revealed. T2 - 20th EAWE PhD Seminar on Wind Energy CY - Visby, Sweden DA - 23.09.2024 KW - Offshore Jacket Support Structure KW - Test Structure KW - Fatigue KW - Lifetime Management KW - Structural Health Monitoring PY - 2024 AN - OPUS4-61146 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Eichner, Lukas T1 - Optimal sensor placement for vibration-based structural health monitoring obtained via value of information analysis as part of a digital structural integrity management of offshore structures N2 - 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. T2 - 3rd International Conference on Health Monitoring of Civil & Maritime Structures (HeaMES 2022) CY - Online meeting DA - 08.06.2022 KW - Bayesian System Identification KW - Offshore Wind Energy KW - Optimal Sensor Placement KW - Structural Health Monitoring KW - Value of Information PY - 2022 AN - OPUS4-55473 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Eichner, Lukas T1 - A framework for data and structural integrity management for support structures in offshore wind farms based on building information modelling N2 - 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. T2 - 8th International Symposium on Reliability Engineering and Risk Management CY - Hannover, Germany DA - 04.09.2022 KW - Offshore wind energy KW - Support structures KW - Building information modelling KW - Structural health monitoring KW - Structural integrity maintenance PY - 2022 AN - OPUS4-55651 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Baeßler, Matthias A1 - Eichner, Lukas A1 - Weise, Sigurd T1 - Digital building management for OWEC-structures N2 - The presentation summarizes the data management and Digital modeling processes in the recurring inspection of wind turbines as developed in DiMoWind-Inspect. T2 - Windforce 2024 CY - Bremerhaven, Germany DA - 10.06.2024 KW - DiMoWind RDS-PP Maintenance Digital Twin Offshore Wind Energy PY - 2024 AN - OPUS4-60351 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -