TY - CONF A1 - Eichner, Lukas A1 - Gerards, Paul A1 - Herrmann, Ralf A1 - Schneider, Ronald A1 - Hille, Falk A1 - Baeßler, Matthias 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 - structural health monitoring KW - building information modelling KW - structural integrity management PY - 2022 DO - https://doi.org/10.3850/978-981-18-5184-1_MS-04-161-cd SP - 111 EP - 117 PB - Research Publishing CY - Singapore AN - OPUS4-55656 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Herrmann, Ralf A1 - Simon, Patrick A1 - Hille, Falk A1 - Said, Samir A1 - Baeßler, Matthias T1 - Sensorbasiertes Monitoring der Maintalbrücke Gemünden N2 - Monitoringsysteme erfassen kontinuierlich Bauwerksdaten wie z.B. Bauwerksbeschleunigungen, auf deren Grundlage Bauwerksschäden mit Hilfe von SHM-Methoden quantifiziert werden können. Mit den gewonnenen Informationen über den aktuellen Bauwerkszustand können Vorhersagen des Bauwerkszustandes und der Bauwerkszuverlässigkeit aktualisiert und erforderliche Inspektionen und Instandhaltungsmaßnahmen vorausschauend geplant werden. Im BMBF-Forschungsvorhaben AISTEC entwickeln der Fachbereich 7.2 „Ingenieurbau“ innovative Monitoringverfahren zur Systemidentifikation und automatischen Detektion, Lokalisierung und Quantifizierung von Schäden an Infrastrukturbauwerken anhand von gemessenen dynamischen und statischen Bauwerksdaten. Im Rahmen dieses Projektes werden die Verfahren an der Maintalbrücke bei Gemünden angewendet, welche Teil der ICE-Strecke Hannover-Würzburg ist. In diesem Vortrag wird das für die Maintalbrücke Gemünden geplante und umgesetzte Monitoingsystem vorgestellt. T2 - 4. Verbundtreffen AISTEC CY - Weimar, Germany DA - 24.09.2020 KW - Zivile Sicherheit KW - Brücken KW - Structural Health Monitoring PY - 2020 AN - OPUS4-51333 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick A1 - Schneider, Ronald A1 - Herrmann, Ralf A1 - Viefhues, Eva A1 - Baeßler, Matthias T1 - Experimente in der Klimakammer N2 - Im Rahmen des Verbundtreffens des Vorhabens AISTEC werden akutelle Versuche aus der Großklimakammer des FB 7.2 präsentiert. T2 - 5. Verbundtreffen AISTEC CY - Online meeting DA - 24.06.2021 KW - Klimakammer KW - Stochastic Subspace Damage Detection KW - Model Update KW - Asphalt PY - 2021 AN - OPUS4-52869 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald T1 - Structural integrity management research at BAM N2 - This presentation provides an overview on the structural integrity management research at BAM. In addition, a framework for monitoring and risk-informed inspection and maintenance planning for offshore steel structures is presented. T2 - Structural Health Monitoring Using Statistical Pattern Recognition CY - Berlin, Germany DA - 20.03.2023 KW - Structural integrity KW - Monitoring KW - Maintenance KW - Inspeciton KW - Bridges KW - Offshore wind PY - 2023 AN - OPUS4-57864 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Eichner, Lukas A1 - Schneider, Ronald A1 - Baeßler, Matthias T1 - Optimal vibration sensor placement for jacket support structures of offshore wind turbines based on value of information analysis N2 - 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. KW - Optimal sensor placement KW - Value of information KW - Jacket support structure KW - Offshore wind turbine KW - Monitoring-informed inspection and maintenance planning PY - 2023 DO - https://doi.org/10.1016/j.oceaneng.2023.115407 SN - 0029-8018 VL - 288 IS - 2 PB - Elsevier Ltd. CY - Amsterdam AN - OPUS4-58725 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Gerards-Wünsche, Paul A1 - Ratkovac, Mirjana A1 - Schneider, Ronald A1 - Hille, Falk A1 - Baeßler, Matthias T1 - A framework for assessing the reliability of crack luminescence – an automated fatigue crack detection system N2 - 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. T2 - SPIE Conference Smart Structures + Nondestructive Evaluation 2023 CY - Long Beach, CA, USA DA - 24.03.2023 KW - Structural Health Monitoring KW - Non-Destructive Evaluation KW - Probability of Detection KW - Reliability KW - Artificial Intelligence KW - Computer Vision KW - Crack Luminescence KW - Wind PY - 2023 SN - 978-1-5106-6086-1 DO - https://doi.org/10.1117/12.2658390 SP - 1 EP - 15 AN - OPUS4-57244 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Thöns, S. A1 - Rogge, Andreas T1 - SysPark: a software tool for system-wide adaptive planning of inspections of turbine support structures in offshore wind farms N2 - Fatigue is one of the main deterioration processes affecting the performance of welded steel support structures of wind turbines in offshore wind farms. In this contribution, we present a probabilistic physics-based fatigue deterioration model of a wind farm that accounts for the stochastic dependence among the fatigue behavior of different hotspots at turbine and wind farm level. The dependence exists because of uncertain common influencing factors such as similar material properties, fabrication qualities and load conditions. These system effects signify that an inspection of one hotspot provides indirect information of the condition of the remaining hotspots and thus enable an optimization of the inspection effort for a wind farm. The wind farm model consists of two levels: A turbine support structure (level 1 system model) is represented by its fatigue hotspots and their stochastic dependence. The fatigue performance of a hotspot is described by a probabilistic fracture mechanics (FM) fatigue model. The probabilistic model of the parameters of the FM fatigue model is calibrated based on design data and is thus directly linked to the design of the turbine support structures. Dependence among the fatigue performances of different hotspots in a turbine support structure is modeled by introducing correlations between the stochastic parameters of the FM fatigue models. A wind farm (level 2 system model) consists of different turbine support structures (level 1 system models). Additional correlations are introduced at wind farm level to account for the dependence among the fatigue behavior of hotspots belonging to different turbine support structures. The wind farm model enables the computation of (marginal) hotspot fatigue reliabilities, system fatigue reliabilities of individual turbine support structures and the system fatigue reliability of an entire wind farm. The probabilistic model of the parameters of the two-level system model can be consistently updated with inspection outcomes using Bayesian methods. The updated probabilistic model of the model parameters then forms the basis for updating the estimates of the fatigue reliabilities. We implement the wind farm model in a software tool named SysPark. The tool provides the means for planning inspections at wind farm level using an adaptive reliability-based threshold approach. In this approach, the first inspection campaign is planned in the year before the fatigue failure rates of the hotspots with the lowest fatigue reliabilities exceed a threshold failure rate. Once inspection results become available, the probabilistic model of the parameters of the wind farm model is updated. If repairs are performed, the wind farm model is additionally modified to describe the behavior of the repaired hotspots. The updated and modified model then enables the planning of the next inspection campaign and so on. The software tool is demonstrated in a case study considering a generic wind farm consisting of turbines with jacket support structures. T2 - Wind Energy Science Conference (WESC 2021) CY - Online Meeting DA - 25.05.2021 KW - Fatigue deterioration KW - Offshore wind farm KW - Inspection planning PY - 2021 AN - OPUS4-52767 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick A1 - Herrmann, Ralf A1 - Schneider, Ronald A1 - Hille, Falk A1 - Baeßler, Matthias A1 - El-Athman, Rukeia T1 - Research Data Management of Structural Health Monitoring Projects and Subsequent Applications of Artificial Intelligence Methods N2 - 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. T2 - 11th International Conference on Bridge Maintenance, Safety and Management (IABMAS2022) CY - Barcelona, Spain DA - 11.07.2022 KW - Research data management KW - Structural health monitoring KW - Artificial intelligence PY - 2022 SN - 978-1-032-35623-5 SN - 978-1-003-32264-1 DO - https://doi.org/10.1201/9781003322641-127 SP - 1061 EP - 1068 PB - CRC Press CY - Boca Raton AN - OPUS4-55493 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick A1 - Schneider, Ronald A1 - Baeßler, Matthias T1 - Untersuchungsmethoden klimatisch belasteter Bauteile - Projektupdate BAM N2 - Kontinuierliche Sensorbasierte Bauwerksmessungen leisten einen wichtigen Beitrag zur Sicherheit von Verkehrsbauwerken. Hierzu werden im Vorhaben AISTEC Referenzbauwerke und Referenzverfahren untersucht mit Schwerpunkt auf den Einfluss klimatischer Bedingungen. Der Vortrag stellt den aktuellen Projektstand des FB 7.2 vor. T2 - Erstes Verbundtreffen AISTEC CY - Weimar, Germany DA - 21.03.2019 KW - Structural Health Monitoring KW - Environmental Effects KW - Climate Chamber KW - Brücken KW - SHM KW - Klimakammer PY - 2019 AN - OPUS4-47702 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick A1 - Schneider, Ronald A1 - Viefhues, Eva A1 - Said, Samir A1 - Herrmann, Ralf A1 - Baeßler, Matthias ED - Papadrakis, M. ED - Fragiadakis, M. ED - Papadimitriou, C. T1 - Vibration-based Structural Health Monitoring of a Reinforced Concrete Beam Subjected to Varying Ambient Conditions Using Bayesian Methods N2 - Inspection and maintenance contribute significantly to the lifetime cost of bridges. There is significant potential in using information obtained through structural health monitoring to update predictive models of the condition and performance of such structures, and thus ena-ble an improved decision-making regarding inspection and maintenance activities. Within the AISTEC project funded by the German Federal Ministry of Education and Research, we develop vibration-based structural health monitoring systems aimed at continuously provid-ing information on the structural condition of bridges. Environmental variations such as changing ambient temperatures can significantly influence the dynamic characteristics of bridges and thus mask the effect of structural changes and damages. It remains a challenge to account for such influences in structural health monitoring. To study the effect of ambient temperatures on the dynamic characteristics of beam structures, we monitor the vibration response of a reinforced concrete beam in the uncracked and cracked state at varying tem-peratures in a climate chamber. We postulate a set of competing parameterized probabilistic structural models, which explicitly account for the effect of varying ambient temperatures on the mechanical properties of the system. We then combine the information provided by the structural models with the information contained in the recorded vibration data to learn the parameters of the temperature-dependent structural models and infer the plausible state of the beam using Bayesian system identification and model class selection. T2 - EURODYN 2020, XI International Conference on Structural Dynamics CY - Online meeting DA - 23.11.2020 KW - Structural health monitoring KW - Bayesian methods KW - Environmental effects PY - 2020 SN - 978-618-85072-2-7 SN - 978-618-85072-0-3 SP - 1254 PB - Institute of Structural Analysis and Antiseismic Research, School of Civil Engineering, National Technical University of Athens (NTUA) CY - Athens, Greece AN - OPUS4-51590 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Eichner, Lukas A1 - Schneider, Ronald A1 - Simon, Patrick A1 - Baeßler, Matthias 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 - Structural Health Monitoring KW - Value of Information KW - Offshore Wind Energy KW - Optimal Sensor Placement KW - Bayesian System Identification PY - 2022 UR - https://www.researchgate.net/publication/362569906_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 SN - 978-1-8383226-7-0 SP - 23 EP - 32 AN - OPUS4-55465 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick A1 - Herrmann, Ralf A1 - Schneider, Ronald A1 - Hille, Falk A1 - Baeßler, Matthias A1 - El-Athman, Rukeia T1 - Research Data Management of Structural Health Monitoring Projects and Subsequent Applications of Artificial Intelligence Methods N2 - 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. T2 - 11th International Conference on Bridge Maintenance, Safety and Management (IABMAS2022) CY - Barcelona, Spain DA - 11.07.2022 KW - Research data management KW - Structural health monitoring KW - Artificial intelligence PY - 2022 AN - OPUS4-55494 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Lesny, K. A1 - Arnold, P. A1 - Sorgatz, J. A1 - Schneider, Ronald T1 - Wie sicher sind unsere Bauwerke? - Strukturpapier des Arbeitskreises 2.15 der DGGT „Zuverlässigkeitsbasierte Methoden in der Geotechnik“ N2 - Der zukünftige Eurocode 7 wird ausdrücklich die Nutzung zuverlässigkeitsbasierter Methoden in der geotechnischen Planung und Bemessung erlauben. In Deutschland gibt es bisher kaum Erfahrung in der praktischen Anwendung derartiger Verfahren und entsprechend sind die Vorbehalte gegenüber diesen Methoden oft groß. Der neue DGGT-Arbeitskreis (AK) 2.15 „Zuverlässigkeitsbasierte Methoden in der Geotechnik“ hat sich zum Ziel gesetzt, durch praxisorientierte Anleitungen und Empfehlungen sowie begleitende Aus- und Weiterbildungsangebote den praktischen Zugang zu diesen Verfahren zu unterstützen. Ziel ist es, Möglichkeiten und Grenzen zu verdeutlichen sowie vor allem ihre Potenziale zu erschließen. In dem vorliegenden Beitrag werden allgemeine Grundlagen und die zukünftigen Arbeitsfelder des AK 2.15 vorgestellt. Ausgehend von der Einführung relevanter Fachbegriffe wird zunächst die Einbettung zuverlässigkeitsbasierter Verfahren in den aktuellen Normungs- und Regelungskontext aufgezeigt. Anschließend werden anhand des Lebenszyklus eines geotechnischen Bauwerks die Unsicherheiten in den geotechnischen Prognosen und Bewertungen beschrieben. Daran anknüpfend wird aufgezeigt, an welchen Stellen zuverlässigkeitsbasierte Methoden als mögliches Werkzeug sinnvoll genutzt werden können, um Ingenieur:innen, Bauherr:innen und Prüfer:innen in Nachweis- und Entscheidungsprozessen zu unterstützen. Zu den sich daraus ableitenden Arbeitsthemen werden durch den AK 2.15 zukünftig Empfehlungen erarbeitet und sukzessive veröffentlicht KW - Brückensicherheit KW - Sicherheit KW - Wahrscheinlichkeit KW - Zuverlässigkeit KW - Bemessung KW - Bewertung KW - Offshore Wind PY - 2023 DO - https://doi.org/10.1002/gete.202300014 VL - 46 IS - 3 SP - 153 EP - 164 PB - Ernst & Sohn GmbH CY - Berlin AN - OPUS4-58208 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Schneider, Ronald T1 - Von der Datenerfassung bis zur Entscheidungsfindung: Jede Brücken-Überwachung bedarf einer Gesamtmethodik N2 - Brücken müssen laufend überwacht werden, damit die Unsicherheiten hinsichtlich ihres Zustands, ihrer Beanspruchung und ihrer Leistungsfähigkeit verringert werden können. Diese Aufgabe soll künftig mit digitalen Methoden erleichtert werden. Im folgenden Beitrag werden deshalb die digitale Bauwerksmodellierung und die Entscheidungsfindung beleuchtet. Dazu wird gezeigt, wie Zustandsdiagnosen und -prognosen digital ermöglicht werden und wie durch diagnostische und prognostische Modelle eine wissenschaftliche Basis für risikobasierte Entscheidungen über Erhaltungsmaßnahmen und für den Übergang vom reaktiven zum vorausschauenden Brückenmanagement gebildet werden kann. Dabei wird klar: Jede Brücken-Überwachung bedarf einer Gesamtmethodik, ihre wichtigsten Elemente sind: Datenerfassung, Datenmanagement, Datenanalyse, Bauwerksmodellierung, Bauwerksbewertung und die letztendlichen Entscheidungen über notwendige Erhaltungsmaßnahmen. KW - Prädiktive Instandhaltung KW - Brücken KW - Erhaltungsmanagement KW - Digitale Zwillinge PY - 2023 IS - 62 SP - 76 EP - 83 AN - OPUS4-57811 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Herrmann, Ralf A1 - Simon, Patrick A1 - Schneider, Ronald A1 - Hille, Falk A1 - Baeßler, Matthias T1 - SHM system integration and experiments at a high speed railway bridge N2 - The long-term preservation of our infrastructure requires not only intelligent sensor technology and highly developed monitoring procedures, but also innovative digital tools for analyzing, evaluating and utilizing the results. This includes mathematical and, in particular, probabilistic methods for damage detection and tracking as well as for calculating service life and maintenance cycles and data management. The example project Maintal Bridge Gemuenden as part of the AISTEC project shows the workflow for the implementation of structural health monitoring and experimental tests with a train of Deutsche Bahn. The influence lines, as one possible way for damage detection, were measured with a highly accurate GNSS System to locate the trains position when crossing the bridge. The results were compared to measurements from 1987 just before the bridge went in operation. T2 - Structural Health Monitoring Using Statistical Pattern Recognition CY - Berlin, Germany DA - 20.03.2023 KW - SHM KW - Maintal Bridge Gemuenden KW - Load Test KW - Damage Detection KW - Railway PY - 2023 AN - OPUS4-57242 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Straub, D. T1 - Cumulative failure probability of deteriorating structures: Can it drop? N2 - The reliability of deteriorating structures at time t is quantified by the probability that failure occurs within the period leading up to time t. This probability is often referred to as cumulative failure probability and is equal to the cumulative distribution function of the time to failure. In structural reliability, an estimate of the cumulative failure probability is obtained based on probabilistic engineering models of the deterioration processes and structural performance. Information on the condition and the loading contained in inspection and monitoring data can be included in the probability estimate through Bayesian updating. Conditioning the probability of failure on the inspection or monitoring outcomes available at time t (e.g. detections or no detection of damages) can lead to a reduction in that probability. Such a drop in the cumulative failure probability might seem counterintuitive since the cumulative failure probability is a non-decreasing function of time. In this paper, we illustrate—with the help of a numerical example—that such a drop is possible because the cumulative probability before and after the updating is not based on the same information, hence not on the same probabilistic model. T2 - 18th Internatinoal Probabilistic Workshop (IPW 2020) CY - Online Meeting DA - 12.05.2021 KW - Deterioration KW - Structural systems KW - Time-variant reliability KW - Bayesian updating KW - Inspection KW - Monitoring PY - 2021 AN - OPUS4-52770 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Artinov, Antoni T1 - Modeling the Relationship between Weld Pool Dynamics and Centerline Solidification Cracking in High Power Laser Beam Welding N2 - The present work deals with the recently confirmed widening of the weld pool interface, known as a bulging effect, and its relevance in high power laser beam welding. A combined experimental and numerical approach is utilized to study the influence of the bulge on the hot cracking formation and the transport of alloying elements in the molten pool. A technique using a quartz glass, a direct-diode laser illumination, a high-speed camera, and two thermal imaging cameras is applied to visualize the weld pool geometry in the longitudinal section. The study examines the relevance of the bulging effect on both, partial and complete penetration, as well as for different sheet thicknesses ranging from 8 mm to 25 mm. The numerical analysis shows that the formation of a bulge region is highly dependent on the penetration depth and occurs above 10 mm penetration depth. The location of the bulge correlates strongly with the cracking location. The obtained experimental and numerical results reveal that the bulging effect increases the hot cracking susceptibility and limits the transfer of alloying elements from the top of the weld pool to the weld root. T2 - Gastvortrag an der Universität Innsbruck, Institut für Konstruktion und Materialwissenschaften CY - Innsbruck, Austria DA - 18.06.2023 KW - Laser beam welding KW - Centerline solidification cracking KW - Bulging KW - Numerical simulation PY - 2024 AN - OPUS4-60333 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald T1 - Effect of repair models on risk based optimal inspection strategies for support structures of offshore wind turbines N2 - Owners or operators of offshore wind farms perform inspections to collect information on the condition of the wind turbine support structures and perform repairs if required. These activities are costly and should be optimized. Risk-based methods can be applied to identify inspection and repair strategies that ensure an optimal balance between the expected total service life cost of inspection and repair, and the achieved risk reduction. Such an optimization requires explicit modeling of repairs. In this paper, the impact of different repair models on the results of a risk-based optimization of inspection and repair strategies is quantified in a numerical example considering a jacket-type steel frame subject to high-cycle fatigue. The example showed that, in this specific application, there is no need for detailed modeling of the behavior of repaired welded connections. T2 - 5th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures (SMAR 2019) CY - Potsdam, Germany DA - 27.08.2019 KW - Risk KW - Reliability KW - Inspection planning KW - Offshore wind turbines PY - 2019 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-488297 UR - https://www.smar2019.org/Portals/smar2019/bb/Th.2.A.4.pdf SP - Paper Th.2.A.4, 1 EP - 8 AN - OPUS4-48829 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Straub, D. ED - Matos, J.C. ED - Lourenço, P.B. ED - Oliveira, D.V. ED - Branco, J. ED - Proske, D. ED - Silva, R.A. ED - Sousa, H.S. T1 - Cumulative Failure Probability of Deteriorating Structures: Can It Drop? N2 - The reliability of deteriorating structures at time t is quantified by the probability that failure occurs within the period leading up to time t. This probability is often referred to as cumulative failure probability and is equal to the cumulative distribution function of the time to failure. In structural reliability, an estimate of the cumulative failure probability is obtained based on probabilistic Engineering models of the deterioration processes and structural performance. Information on the condition and the loading contained in inspection and monitoring data can be included in the probability estimate through Bayesian updating. Conditioning the probability of failure on the inspection or monitoring outcomes available at time t (e.g. detections or no detection of damages) can lead to a reduction in that probability. Such a drop in the cumulative failure probability might seem counterintuitive since the cumulative failure probability is a non-decreasing function of time. In this paper, we illustrate—with the help of a numerical example—that such a drop is possible because the cumulative probability before and after the updating is not based on the same information, hence not on the same probabilistic model. T2 - 18th International Probabilistic Workshop (IPW 2020) CY - Online meeting DA - 12.05.2021 KW - Deterioration KW - Structural systems KW - Time-variant reliability KW - Bayesian updating KW - Inspection KW - Monitoring PY - 2021 DO - https://doi.org/10.1007/978-3-030-73616-3_18 VL - 153 SP - 253 EP - 264 PB - Springer CY - Cham, Switzerland AN - OPUS4-52769 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald T1 - Bayes‘sche Analyse von Ingenieurmodellen N2 - Der Vortrag zeigt, dass Unsicherheiten in Ingenieurmodellen quantitativ mit Methoden der Wahrscheinlichkeitstheorie modelliert werden können. Zusätzlich können durch eine Bayes‘sche Analyse probabilistische Ingenieurmodelle konsistent anhand von Daten „gelernt“ werden. T2 - Workshop "Digitaler Zwilling" des BAM Koptenzzentrums „Modellierung und Simulation“ CY - Berlin, Germany DA - 04.06.2018 KW - Probabilitische Ingenieurmodelle KW - Bayes'sche Analyse PY - 2018 AN - OPUS4-46437 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Simon, Patrick A1 - Hille, Falk A1 - Herrmann, Ralf A1 - Baeßler, Matthias T1 - Vibration-based system identification of a large steel box girder bridge N2 - The Bundesanstalt für Materialforschung und -prüfung (BAM) collaborates with TNO to develop a software framework for automated calibration of structural models based on monitoring data. The ultimate goal is to include such models in the asset management process of engineering structures. As a basis for developing the framework, a multi-span road bridge consisting of ten simply supported steel box girders was selected as a test case. Our group measured output-only vibration data from one box girder under ambient conditions. From the data, we determined eigenfrequencies and mode shapes. In parallel, we developed a preliminary structural model of the box girder for the purpose of predicting its modal properties. In this contribution, we provide an overview of the measurement campaign, the operational modal analysis, the structural modeling and qualitatively compare the identified with the predicted modes. As an outlook, we discuss the further steps in the calibration process and future applications of the calibrated model. T2 - XII International Conference on Structural Dynamics (EURODYN 2023) CY - Delft, Netherlands DA - 02.07.2023 KW - Bridge KW - Safety KW - Fatigue KW - Modal system identification KW - Model updating PY - 2023 AN - OPUS4-57863 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Baeßler, Matthias A1 - Schneider, Ronald A1 - Hille, Falk A1 - Herrmann, Ralf A1 - Said, Samir T1 - Anwendung von kontinuierlichen sensor-basierten Monitoringverfahren zur Bewertung von Infrastrukturbauwerken N2 - Kontinuierliche Sensorbasierte Bauwerksmessungen leisten einen wichtigen Beitrag zur Sicherheit von Verkehrsbauwerken. Hierzu werden im Vorhaben AISTec Referenzbauwerke und Referenzverfahren untersucht. Der Vortrag stellt die Expertise des FB 7.2, Herangehensweisen und Projektziele vor´. T2 - Kick-Off AIStec CY - Weimar, Germany DA - 17.10.2018 KW - Zivile Sicherheit KW - Brücken KW - SHM PY - 2018 AN - OPUS4-46325 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick A1 - Schneider, Ronald A1 - Baeßler, Matthias A1 - Recknagel, Christoph T1 - Enhancing structural models with material tests and static response data - a case study considering a steel beam with asphalt layer subject to temperature variations N2 - Gradual or sudden changes in the state of structural systems caused, for example, by deterioration or accidental load events can influence their load-bearing capacity. Structural changes can be inferred from static and/or dynamic response data measured by structural health monitoring systems. However, they may be masked by variations in the structural response due to varying environmental conditions. Particularly, the interaction of nominally load-bearing components with nominally non-load bearing components exhibiting characteristics that vary as a function of the environmental conditions can significantly affect the monitored structural response. Ignoring these effects may hamper an inference of structural changes from the monitoring data. To address this issue, we adopt a probabilistic model-based framework as a basis for developing digital twins of structural systems that enable a prediction of the structural behavior under varying ambient condition. Within this framework, different types of data obtained from real the structural system can be applied to update the digital twin of the structural system using Bayesian methods and thus enhance predictions of the structural behavior. In this contribution, we implement the framework to develop a digital twin of a simply supported steel beam with an asphalt layer. It is formulated such that it can predict the static response of the beam in function of its temperature. In a climate chamber, the beam was subject to varying temperatures and its static response wass monitored. In addition, tests are performed to determine the temperature-dependent properties of the asphalt material. Bayesian system identification is applied to enhance the predictive capabilities of the digital twin based on the observed data. T2 - International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-10) CY - Online meeting DA - 30.06.2021 KW - Digital twin KW - Structural health monitoring KW - Material tests KW - Bayesian updating PY - 2021 AN - OPUS4-54130 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Zinas, Orestis A1 - Schneider, Ronald A1 - Cuéllar, Pablo A1 - Schepers, Winfried A1 - Baeßler, Matthias A1 - Papaioannou, I. T1 - Potentials of probabilistic approaches in offshore foundation installation N2 - This presentation discusses the potentials of probabilistic methods in offshore foundation installation, from the perspective of probabilistic ground models and data-driven site characterization. We discuss about methodologies for utilizing site-specific geotechnical (CPT) and geological data, aiming to construct an integrated ground model that can predict stratigraphic profiles and useful for geotechnical design parameters at any location within a 3D domain. The predicted parameters and stratigraphy are then used to predict the probability of potential pile tip damage, upon collision with a boulder. T2 - Colloquium Buckling of Offshore Wind Energy Structures CY - Berlin, Germany DA - 14.02.2024 KW - Wind KW - Offshore KW - Buckling KW - Probabilistic KW - Ground PY - 2024 AN - OPUS4-59538 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald T1 - Überwachung von Brücken mit digitalen Methoden N2 - Brücken werden durch Inspektionen und teilweise durch Monitoring überwacht, um Daten und Informationen über den Zustand und die Einwirkungen zu sammeln. Auf deren Grundlage werden Entscheidungen hinsichtlich Maßnahmen zur Gewährleistung der Sicherheit und Verfügbarkeit getroffen. In diesem Vortrag werden die Potentiale der Digitalisierung zur Unterstützung und Verbesserung der Brückenüberwachung diskutiert. Insbesondere werden die Bereiche Datenmanagement, Brückenmodellierung und Entscheidungsfindung betrachtet. T2 - BVPI Arbeitstagung 2022 CY - Berlin, Germany DA - 16.09.2022 KW - Entscheidungsfindung KW - Brücken KW - Überwachung KW - Digitalisierung KW - Datenmanagement KW - Modellierung PY - 2022 AN - OPUS4-55770 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Simon, Patrick A1 - Herrmann, Ralf A1 - Hille, Falk A1 - Baeßler, Matthias T1 - Belastungsversuch und Methodenvalidierung an der Maintalbrücke Gemünden N2 - Im Projekt AISTEC wurden Methoden entwickelt, die der prädiktiven Instandhaltung von Ingenieurbauwerken dienen. Zur Validierung dieser Methoden wurden an einem Referenzbauwerk - der Maintalbrücke Gemünden - Belastungstests durchgeführt. T2 - Abschlussveranstaltung AISTEC CY - Berlin, Germany DA - 02.05.2022 KW - Belastungsfahrt KW - GNSS KW - Einflusslinien PY - 2022 AN - OPUS4-55496 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Pittner, Andreas A1 - Winterkorn, René A1 - Fabry, Çağtay A1 - Rethmeier, Michael A1 - Thiele, Marc A1 - Baeßler, Matthias A1 - Brauser, S. T1 - SmartWeld - Leichtbautechnik für Tragstrukturen von Offshore Windenergieanlagen N2 - 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. T2 - 11. Zukunftskonferenz Wind & Maritim CY - Rostock, Germany DA - 01.09.2022 KW - Offshore Windenergieanlagen KW - Gründungsstrukturen KW - Leichtbauprinzipien KW - Automatisierte Fertigung PY - 2022 AN - OPUS4-56654 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Pittner, Andreas A1 - Winterkorn, René A1 - Fabry, Çağtay A1 - Rethmeier, Michael A1 - Ratkovac, Mirjana A1 - Thiele, Marc A1 - Baeßler, Matthias T1 - Innovative Design- und Fertigungsstrategien zur Steigerung der Leichtbaupotenziale im Stahlbau N2 - Ziel des Verbundvorhabens „SmartWeld“ ist es, für die schweißtechnische Fertigung von Stahlbaustrukturen exemplarisch am Beispiel von Hohlprofilknoten, welche als designrelevante Elemente von Gründungsstrukturen für Offshore-Windenergieanlagen (OWEA) einsetzbar sind, die Möglichkeiten des Leichtbaus unter konsequenter Digitalisierung der Fertigungskette aufzuzeigen, um einerseits die Ressourceneffizienz zu forcieren und gleichzeitig wettbewerbsfähige Fertigungsstrategien aufzuzeigen. Innerhalb von „SmartWeld“ werden daher die Möglichkeiten einer wirtschaftlichen Fertigung von Leichtbau-Gründungsstrukturen am Beispiel aufgelöster Tragstrukturen (Jackets) aufgezeigt. Eine lastgerechte Auslegung der Schweißverbindungen nach bionischen Prinzipien ermöglicht, weitere Einsparpotenziale an Ressourcen bei gleichzeitiger Erhöhung der Lebensdauer zu erschließen. Die Ausnutzung konstruktiver Prinzipien des Leichtbaus zur Erzeugung innovativer und ressourcenschonender Produkte erfordert den Einsatz digitaler Werkzeuge in der Designphase, der virtuellen Absicherung, der Fertigung und Qualitätsüberwachung sowie nachgelagerten Bauteilprüfung zur Abbildung der Nutzungsphase. Im Rahmen der Arbeiten wird daher der gesamte Produktentstehungs- und Prüfprozess betrachtet. Dies beinhaltet das Design im Kontext des konstruktiven Leichtbaus, den schweißtechnischen Fertigungsprozess, die Bauteilprüfung sowie den Transfer der Ergebnisse in die Industrie durch serientaugliche Demonstratoren. Der Fokus der Arbeiten ist, die Fertigung auch im Umfeld eines für großskalige Stahlstrukturen üblichen hohen Individualisierungsgrades schweißtechnisch zu automatisieren und das Leichtbaupotenzial gezielt umzusetzen. Die Vorgaben aus der Designphase hinsichtlich einer lastgerechten Gestaltung bzw. Implementierung bionischer Ansätze können so gezielt durch einen adaptiven, automatisierten Schweißprozess eingestellt werden. Dies führt zu einer Erhöhung der Ermüdungs¬festigkeit und damit Produktlebensdauer, wodurch die Strukturen dünnwandiger ausgeführt und Ressourcen sowie CO2 eingespart werden können. T2 - Sitzung des DVS Fachausschuss FA03 - Lichtbogenschweißen CY - Rostock, Germany DA - 11.10.2022 KW - Offshore Windenergieanlagen KW - Gründungsstrukturen KW - Leichtbau KW - Automatisierte schweißtechnische Fertigung PY - 2022 AN - OPUS4-56656 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Pittner, Andreas A1 - Winterkorn, René A1 - Fabry, Çağtay A1 - Rethmeier, Michael A1 - Ratkovac, Mirjana A1 - Thiele, Marc A1 - Baeßler, Matthias T1 - Innovative Design- und Fertigungsstrategien zur Steigerung der Leichtbaupotenziale im Stahlbau N2 - Offshore wind energy plays an important role for the desired transition towards a carbon dioxide free industry within the next decades. However, the grounding of the offshore wind plants governs the overall installation process besides bureaucratic bottlenecks. The application of lightweight principles in steel construction, e.g. the usage dissolved load-bearing structures, so called Jackets foundations, offer great potential in reducing the resource consumption, especially with respect to the needed amount of steel. In this context this presentation focuses on a fully digitalization of the welding manufacturing and as well as testing chain to enable a fully automated manufacturing as well as quality assessment of tubular nodes as key element of Jackets foundation structures. Furthermore, the relationship between the seam shape geometry and resulting fatigue strength is evaluated by numerical methods incorporating bionic principles. It is shown that tubular nodes can be welded fully automatically taking geometry tolerances into account. Moreover, the seam shape could be manufactured as requested by the numerical models which offers great potential for an extended lifetime. Subsequently, the improvements in resource efficiency and reduction of carbon dioxide emissions are evaluated by a life-cycle-assessment. T2 - Leichtbau in der Hauptstadtregion - Rohstoffe - Recycling - Rohstoffe: Kreislaufwirtschaft im Leichtbau CY - Berlin, Germany DA - 28.11.2022 KW - Offshore Windenergie KW - Gründungsstrukturen KW - Leichtbau KW - Automatisierte schweißtechnische Fertigung PY - 2022 AN - OPUS4-56657 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Pittner, Andreas A1 - Winterkorn, René A1 - Fabry, Çağtay A1 - Rethmeier, Michael A1 - Ratkovac, Mirjana A1 - Thiele, Marc A1 - Baeßler, Matthias T1 - Innovative Design- und Fertigungsstrategien zur Steigerung der Leichtbaupotenziale im Stahlbau N2 - Ziel des Verbundvorhabens „SmartWeld“ ist es, für die schweißtechnische Fertigung von Stahlbaustrukturen exemplarisch am Beispiel von Hohlprofilknoten, welche als designrelevante Elemente von Gründungsstrukturen für Offshore-Windenergieanlagen (OWEA) einsetzbar sind, die Möglichkeiten des Leichtbaus unter konsequenter Digitalisierung der Fertigungskette aufzuzeigen, um einerseits die Ressourceneffizienz zu forcieren und gleichzeitig wettbewerbsfähige Fertigungsstrategien aufzuzeigen. Innerhalb von „SmartWeld“ werden daher die Möglichkeiten einer wirtschaftlichen Fertigung von Leichtbau-Gründungsstrukturen am Beispiel aufgelöster Tragstrukturen (Jackets) aufgezeigt. Eine lastgerechte Auslegung der Schweißverbindungen nach bionischen Prinzipien ermöglicht, weitere Einsparpotenziale an Ressourcen bei gleichzeitiger Erhöhung der Lebensdauer zu erschließen. Die Ausnutzung konstruktiver Prinzipien des Leichtbaus zur Erzeugung innovativer und ressourcenschonender Produkte erfordert den Einsatz digitaler Werkzeuge in der Designphase, der virtuellen Absicherung, der Fertigung und Qualitätsüberwachung sowie nachgelagerten Bauteilprüfung zur Abbildung der Nutzungsphase. Im Rahmen der Arbeiten wird daher der gesamte Produktentstehungs- und Prüfprozess betrachtet. Dies beinhaltet das Design im Kontext des konstruktiven Leichtbaus, den schweißtechnischen Fertigungsprozess, die Bauteilprüfung sowie den Transfer der Ergebnisse in die Industrie durch serientaugliche Demonstratoren. Der Fokus der Arbeiten ist, die Fertigung auch im Umfeld eines für großskalige Stahlstrukturen üblichen hohen Individualisierungsgrades schweißtechnisch zu automatisieren und das Leichtbaupotenzial gezielt umzusetzen. Die Vorgaben aus der Designphase hinsichtlich einer lastgerechten Gestaltung bzw. Implementierung bionischer Ansätze können so gezielt durch einen adaptiven, automatisierten Schweißprozess eingestellt werden. Dies führt zu einer Erhöhung der Ermüdungs¬festigkeit und damit Produktlebensdauer, wodurch die Strukturen dünnwandiger ausgeführt und Ressourcen sowie CO2 eingespart werden können. T2 - 9. Forum Leichtbau - Fortschrittliche Fertigungstechnologien und Werkstoffe für den Klimaschutz CY - Berlin, Germany DA - 29.09.2022 KW - Offshore Windenergieanlagen KW - Gründungsstrukturen KW - Leichtbau KW - Bionik KW - Automatisierte schweißtechniche Fertigung PY - 2022 AN - OPUS4-56655 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Baeßler, Matthias A1 - Balscheit, Hagen A1 - Schepers, Winfried A1 - Victor, Albrecht A1 - Daryaei, Reza A1 - Bianco, Marcelo A1 - Starost, Christina T1 - Close-out Webinar OWA VERBATIM N2 - The risk of pile base buckling is a major reason for high pile wall thicknesses in monopiles. The VERBATIM project - Verification of the buckling detection and behaviour of large monopiles - aimed to investigate buckling phenomena related to both the plastic deformation of the pile tip during installation and the buckling of the embedded pile near the seabed. Numerical models were developed and validated on the basis of extensive tests. This enables a better understanding of the buckling behaviour in order to reduce the wall thickness, which allows cost savings in the amount of steel and the development of safer and optimised structures. The previous design procedures were able to ensure the successful installation of the monopiles. However, as the size of monopiles continues to increase, the development of improved design methods for safe and cost-effective foundations is becoming increasingly important. The presentation provides an overview of the investigations carried out and the results. T2 - Webinar Carbon Trust Offshore Wind Accelerator CY - Online meeting DA - 22.05.2024 KW - Offshore Windenergy Pile Buckling PY - 2024 AN - OPUS4-60348 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Baeßler, Matthias A1 - Aubram, Daniel T1 - Vorstellung OWA VERBATIM N2 - Das Risiko von Pfahlfussbeulen ist ein wesentlicher Grund für hohe Pfahlwandstärken bei Monopiles. Das Projekt VERBATIM - Verifikation des Beulnachweises und –verhaltens großer Monopiles zielte darauf ab, Beulphänomene zu untersuchen, die sich sowohl auf die plastischen Verformungen der Pfahlspitze während der Installation als auch auf das Beulen des eingebetteten Pfahls in der Nähe des Seebodens beziehen. Auf der Basis aufwändiger Versuche wurden numerische Modelle entwickelt und validiert. Dies ermöglicht ein besseres Verständnis des Beulverhaltens, um die Wanddicke zu reduzieren, was Kosteneinsparungen bei der Stahlmenge sowie die Entwicklung sicherer und optimierter Strukturen erlaubt. Die bisherigen Designverfahren konnten die erfolgreiche Installation der Monopiles gewährleisten. Da die Größe von Monopiles jedoch stetig zunimmt, wird die Entwicklung verbesserter Designverfahren für sichere und kostengünstige Fundamente immer wichtiger. Der Rückenwind-Vortrag gibt eine Übersicht zu den durchgeführten Untersuchungen und Ergebnissen T2 - Rückenwind Aktuelles aus der Windenergieforschung (PTJ) CY - Online meeting DA - 21.06.2024 KW - Offshore Windenergy Pile Buckling PY - 2024 AN - OPUS4-60349 LA - deu 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 - TY - CONF A1 - Baeßler, Matthias A1 - Weise, Sigurd T1 - Digitalization of Maintenance Processes N2 - Main aspects of Digitalization of Maintenance Processes are summarized and discussed. Introduction to the Windforce2024 session organised by BAM. T2 - Windforce 2024 CY - Bremerhaven, Germany DA - 11.06.2024 KW - Maintenance Digital Twin Offshore Wind Energy PY - 2024 AN - OPUS4-60350 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald T1 - Modeling in support of decisions regarding lifetime extensions and repowering of offshore wind farms N2 - The EU member states have set out ambitious long-term goals for deploying offshore wind energy. The installed offshore wind capacity is set to increase from 14.6 GW in 2021 to around 320 GW in 2050. This signifies the role of offshore wind energy as a major contributor to reaching the EU’s climate and energy goals. To ensure that the defined targets are met, a significant number of new wind farms has to be installed and existing wind farms reaching the end of their planned life need to be reused efficiently. Some of the relevant reuse alternatives are lifetime extension, repowering based on the existing support structures and repowering with new turbines. As a basis of the decision-making regarding the reuse of existing offshore wind farm, the expected utility of each relevant option should be determined based on the associated expected rewards, costs and risks. The optimal concept maximizes the utility of the decision-maker and fulfills the existing constraints and requirements. To facilitate such a quantitative decision-making, models and methods have to be developed. In particular, models are required that enable predictions of (a) the condition and performance of the turbines and support structures and (b) the renumeration, costs and consequences of adverse events. These predictions have to consider (a) the governing uncertainties, (b) the available information from the planning, construction, installation and operating phase, (b) potential repair, retrofitting and strengthening schemes and (c) possible monitoring, inspection and maintenance regimes for the future operating phase. Over the past years, several models, methods and tools have been developed at the Bundesanstalt für Materialforschung und -prüfung (BAM) to support the structural integrity management of offshore wind turbine substructures. These include: (a) a prototype for reliability-based, system-wide, adaptive planning of inspections of welded steel structures in offshore wind farms, (b) a method for monitoring and risk-informed optimization of inspection and maintenance strategies for jacket structures subject to fatigue, and (c) a probabilistic cost model of inspection and maintenance of welded steel structures in offshore wind farms. This contribution provides an overview on these works and discusses how they can be adapted and extended to support the decision-making regarding lifetime extensions and repowering of offshore wind farms. T2 - 12th International Forum on Engineering Decision Making (12th IFED) CY - Stoos, Switzerland DA - 05.12.2023 KW - Windenergie KW - Offshore Wind KW - Lifetime Extension KW - Repowering PY - 2023 AN - OPUS4-60430 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Schepers, Winfried A1 - Brinkgreve, RBJ A1 - Appel, S. T1 - Recommendations on finite element modelling of non-seismic excitation in soil-structure interaction problems N2 - Nowadays geotechnical engineering firms have powerful software tools to extent their consult-ing business also into dynamic soil-structure interaction, which before has been restricted to a rather small community of specialized experts in this field, and they certainly do. This is par-ticularly true with respect to non-seismic sources, that is all kinds of human induced vibrations. Hence, there is a demand from clients as well as from contractors to have guidance on the re-quirements as well as the limits of numerical modelling of soil-structure interaction. From the literature as well as from relevant standards, recommendations for the numerical modelling of soil-structure interaction problems involving seismic actions are well known, e. g. ASCE/SEI 4-16. There are, however, some particularities when dealing with human-induced vibrations, which are absent in seismic analyses. For human-induced excitations very little specific guid-ance has been published in the past. A machine foundation on a homogeneous half space ex-cited by harmonic loads with excitation frequency between 4 Hz and 64 Hz has been ana-lysed by means of several commercially available software packages. Parametric studies have been performed to verify if recommendations for seismic soil-structure analyses are valid for non-seismic analyses as well. This paper provides details on the benchmark example and the most important conclusions from the undertaken parametric studies. T2 - XII International Conference on Structural Dynamics CY - Delft, Netherlands DA - 02.07.2023 KW - Numerische Analysen KW - Referenzbeispiel KW - Maschinenfundament KW - Wellenausbreitung PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-604931 DO - https://doi.org/10.1088/1742-6596/2647/8/082014 SN - 1742-6596 VL - 2647 IS - 25 SP - 1 EP - 13 PB - IOP Publishing AN - OPUS4-60493 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Schepers, Winfried A1 - Kulke, D. T1 - Cone penetration tests and dynamic soil properties N2 - ISO 14837-32:2015 and DIN EN 1998-1/NA:2021 as well as prEN 1997-2:2022 allow for us-ing correlations between the results of in-situ soil penetration tests and shear wave velocity (or shear modulus) to determine soil properties to be used in dynamic analyses. While the ISO and prEN standards even provide some recommendations on specific correlations to be used, the DIN standard does not. Due to the statistical nature of such correlations their general applica-bility has to be verified. We collected data sets from test sites from Germany as well as New Zealand at which cone penetration tests (CPT) as well as seismic site investigation methods were conducted. These sites comprise sandy soils as well as clayey soils, mixed soils as well as glacial soils. We compare the results of several correlations between CPT results and shear wave velocity. The accuracy of such correlations is assessed with respect to the accuracy of seismic in-situ tests. It turns out that for clean sands such correlations between CPT and Vs have a similar order of variability as seismic in-situ tests conducted at the same site. The higher the fines portion of the soil, the higher the variability of the statistical correlations, and conse-quently the less the general applicability. For glacial soils and other special soil types usage of statistical correlations to determine dynamic soil properties is not recommended. T2 - XII International Conference on Structural Dynamics CY - Delft, Netherlands DA - 02.07.2023 KW - Wave propagation KW - Soil properties KW - Dynamic excitation PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-604887 DO - https://doi.org/10.1088/1742-6596/2647/25/252005 VL - 2647 SP - 1 EP - 11 PB - IOP Publishing CY - Bristol AN - OPUS4-60488 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -