Dokument-ID Dokumenttyp Autoren/innen Persönliche Herausgeber/innen Haupttitel Abstract Auflage Verlagsort Verlag Herausgeber (Institution) Erscheinungsjahr Titel des übergeordneten Werkes Jahrgang/Band ISBN Veranstaltung Veranstaltungsort Beginndatum der Veranstaltung Enddatum der Veranstaltung Ausgabe/Heft Erste Seite Letzte Seite URN DOI Lizenz Datum der Freischaltung OPUS4-52809 Beitrag zu einem Tagungsband Simon, Patrick; Schneider, Ronald; Baeßler, Matthias Yokota, H.; Frangopol, D. M. Bayesian system identification of a reinforced concrete beam subject to temperature variations based on static response data Changes in the measured response of structural systems can be an indication of structural damages. However, such changes can also be caused by the effect of varying environmental conditions. To detect, localize and quantify changes or damages in structural systems subject to varying environmental conditions, physics-based models of the structural systems have to be applied which explicitly account for the influence of ambient conditions on the structural behavior. Data obtained from the structural systems should be used to calibrate the models and update predictions. Bayesian system identification is an effective framework for this task. In this paper, we apply this framework to learn the parameters of two competing structural models of a reinforced concrete beam subject to varying temperatures based on static response data. The models describe the behavior of the beam in the uncracked and cracked condition. The data is collected in a series of load tests in a climate chamber. Bayesian model class selection is then applied to infer the most plausible condition of the beam conditional on the available data. CRC Press 2021 Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations Tenth International Conference on Bridge Maintenance, Safety and Management (IABMAS 2020) Online meeting 11.04.2021 15.04.2021 934 941 10.1201/9780429279119-125 2021-06-14 OPUS4-55492 Zeitschriftenartikel Simon, Patrick; Helmrich, M.; Herrmann, Ralf; Schneider, Ronald; Baeßler, Matthias; Lorelli, S.; Morgenthal, G. Maintalbrücke Gemünden: Bauwerksmonitoring und -identifikation aus einem Guss Die Infrastruktursysteme der Industriestaaten erfordern heute und in Zukunft ein effizientes Management bei alternder Bausubstanz, steigenden Lasten und gleichbleibend hohem Sicherheitsniveau. Digitale Technologien bieten ein großes Potenzial zur Bewältigung der aktuellen und künftigen Herausforderungen im Infrastrukturmanagement. Im BMBF-geförderten Projekt Bewertung alternder Infrastrukturbauwerke mit digitalen Technologien (AISTEC) wird untersucht, wie unterschiedliche Technologien und deren Verknüpfung gewinnbringend eingesetzt werden können. Am Beispiel der Maintalbrücke Gemünden werden ein sensorbasiertes Bauwerksmonitoring, bildbasierte Inspektion mit durch Kameras ausgestatteten Drohnen (UAS) und die Verknüpfung digitaler Bauwerksmodelle umgesetzt. Die aufgenommenen Bilder dienen u. a. als Grundlage für spätere visuelle Anomaliedetektionen und eine 3D-Rekonstruktion, welche wiederum für die Kalibrierung und Aktualisierung digitaler Tragwerksmodelle genutzt werden. Kontinuierlich erfasste Sensordaten werden ebenfalls zur Kalibrierung und Aktualisierung der Tragwerksmodelle herangezogen. Diese Modelle werden als Grundlage für Anomaliedetektionen und perspektivisch zur Umsetzung von Konzepten der prädiktiven Instandhaltung verwendet. Belastungsfahrten und historische Daten dienen in diesem Beitrag der Validierung von kalibrierten Tragwerksmodellen. Berlin Ernst & Sohn 2022 Bautechnik 99 3 163 172 urn:nbn:de:kobv:b43-554924 10.1002/bate.202100102 https://creativecommons.org/licenses/by/4.0/deed.de 2022-08-16 OPUS4-48952 Zeitschriftenartikel Straub, D.; Schneider, Ronald; Bismut, E.; Kim, H.-J. Reliability analysis of deteriorating structural systems Reliability analysis of deteriorating structural systems requires the solution of time-variant reliability problems. In the general case, both the capacity of and the loads on the structure vary with time. This analysis can be approached by approximation through a series of time-invariant reliability problems, which is a potentially effective strategy for cases where direct solutions of the time-variant reliability problem are challenging, e.g. for structural systems with many elements or arbitrary load processes. In this contribution, we thoroughly Review the formulation of the equivalent time-invariant reliability problems and extend this approximation to structures for which inspection and monitoring data is available. Thereafter, we present methods for efficiently evaluating the reliability over time. In particular, we propose the combination of sampling-based methods with a FORM (first-order reliability method) approximation of the series system reliability problem that arises in the computation of the lifetime reliability. The framework and algorithms are demonstrated on a set of numerical examples, which include the computation of the reliability conditional on inspection data. Elsevier Ltd. 2020 Structural Safety 82 Paper 101877, 1 10.1016/j.strusafe.2019.101877 2019-09-16 OPUS4-46434 Beitrag zu einem Tagungsband Schneider, Ronald; Rogge, Andreas; Thöns, S.; Bismut, E.; Straub, D. Caspeele, Robby; Taerwe, Luc; Frangopol, Dan M. A sampling-based approach to identifying optimal inspection and repair strategies for offshore jacket structures 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. London Taylor & Francis Group 2019 Proceedings of the sixth international symposium on life-cycle civil engineering (IALCCE 2018) 978-1-138-62633-1 The sixth international symposium on life-cycle civil engineering (IALCCE 2018) Ghent, Belgien 28.10.2018 31.10.2018 1081 1088 2018-11-05 OPUS4-58725 Zeitschriftenartikel Eichner, Lukas; Schneider, Ronald; Baeßler, Matthias Optimal vibration sensor placement for jacket support structures of offshore wind turbines based on value of information analysis 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. Amsterdam Elsevier Ltd. 2023 Ocean Engineering 288 2 10.1016/j.oceaneng.2023.115407 2023-11-02 OPUS4-57244 Beitrag zu einem Tagungsband Gerards-Wünsche, Paul; Ratkovac, Mirjana; Schneider, Ronald; Hille, Falk; Baeßler, Matthias A framework for assessing the reliability of crack luminescence - an automated fatigue crack detection system 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. 2023 SPIE Conference Smart Structures + Nondestructive Evaluation 2023 978-1-5106-6086-1 SPIE Conference Smart Structures + Nondestructive Evaluation 2023 Long Beach, CA, USA 24.03.2023 28.03.2023 1 15 10.1117/12.2658390 2023-03-30