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 T2 - Proc. of the 8th Intl. Symp. on Reliability Engineering and Risk Management (ISRERM 2022) 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 T1 - A risk-based framework for optimizing inspection and maintenance of deteriorating structures monitored by vibration-based monitoring systems N2 - 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. T2 - EERA JP Wind WORKSHOP on Ongoing research in offshore wind structures CY - Online meeting DA - 16.09.2021 KW - Structural Health Monitoring KW - Inspection KW - Maintenance KW - Deterioration KW - Vibration KW - Structural Systems PY - 2021 AN - OPUS4-53749 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Rogge, Andreas A1 - Thöns, S. A1 - Bismut, E. A1 - Straub, D. T1 - A sampling-based approach to identifying optimal inspection and repair strategies for offshore jacket structures N2 - 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. T2 - The Sixth International Symposium on Life-Cycle Civil Engineering (IALCCE 2018) CY - Gent, Belgium DA - 28.10.2018 KW - Steel structures KW - Fatigue KW - Reliability KW - Risk KW - Inspection planning PY - 2018 AN - OPUS4-46432 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 - 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 - 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 - 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? T2 - 18th International Probabilistic Workshop. IPW 2020. Lecture Notes in Civil Engineering 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 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 - Schneider, Ronald T1 - Effect of repair models on risk based optimal inspection strategies for support structures of offshore wind turbines T2 - Proceedings of the 5th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures (SMAR 2019) 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 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, reliability, inspection planning, offshore wind turbines PY - 2019 AN - OPUS4-48830 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -