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 OPUS4-54531 Beitrag zu einem Tagungsband Schneider, Ronald; Cuéllar, Pablo; Baeßler, Matthias Probabilistic approaches to the design and assessment of offshore foundations considering spatially varying site conditions In this contribution, we consider two applications in which probabilistic approaches can potentially complement or enhance the design and assessment of offshore wind turbine foundations. First, we illustrate in a numerical example that probabilistic modelling can be helpful in dealing with chang-es in turbine locations during the planning phase of an offshore wind farm. In this case, spatial probabilistic modelling of the ground conditions enables (a) an inference of the soil properties at the modified turbine location from field data collected at different locations across an offshore wind farm site and (b) an optimisation of further site investigations. Second, we discuss the uncer-tainties and risks associated with the installation of large diameter monopiles in soils with hetero-geneities such as strong layers and/or embedded boulders. Subsequently, we present a concept for modelling, understanding, and managing these risks based on a probabilistic model of the subgrade conditions, monopile, and subgrade-pile-interaction. ASRANet Ltd 2022 Proceedings of the 3rd International Conference on Structural Integrity for Offshore Energy Industry (SI 2021) 978-1-8383226-3-2 3rd International Conference on Structural Integrity for Offshore Energy Industry (SI 2021) Online meeting 15.11.2021 16.11.2021 9 17 2022-03-24 OPUS4-54126 Beitrag zu einem Tagungsband Simon, Patrick; Schneider, Ronald; Baeßler, Matthias; Recknagel, Christoph Cunha, Á.; Caetano, E. Enhancing structural models with material tests and static response data - a case study considering a steel beam with asphalt layer subject to temperature variations 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. International Society for Structural Health Monitoring of Intelligent Infrastructure (ISHMII) 2021 International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-10) International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-10) Online meeting 30.06.2021 02.07.2021 1537 1544 2021-12-22 OPUS4-53748 Vortrag Schneider, Ronald Probabilistic approaches to the design and assessment of offshore foundations considering spatially varying site conditions In this presentation, we discuss the potential of probabilistic approaches to the design and assessment of offshore foundations. The potential is demonstrated in a numerical example considering a laterally loaded monopile. As an outlook, we present a concept for managing the risk associated with installing large monopiles. 2021 3rd International Conference on Structural Integrity for Offshore Energy Industry (SI 2021) Online meeting 15.11.2021 16.11.2021 2021-11-17 OPUS4-53749 Vortrag Schneider, Ronald A risk-based framework for optimizing inspection and maintenance of deteriorating structures monitored by vibration-based monitoring systems 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. 2021 EERA JP Wind WORKSHOP on Ongoing research in offshore wind structures Online meeting 16.09.2021 17.09.2021 2021-11-17 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 OPUS4-52810 Beitrag zu einem Tagungsband Herrmann, Ralf; Schneider, Ronald; Simon, Patrick; Hille, Falk; Said, Samir; Baeßler, Matthias Curbach, M.; Marx, S.; Scheerer, S.; Hampel, T. Structural Health Monitoring der Maintalbrücke Gemünden zur Unterstützung einer prädiktiven Instandhaltung Nach den bisherigen Regeln werden Bauwerksprüfungen von Brücken in starr definierten Intervallen durchgeführt. Diese starre, periodische, zustandsbasierte Instandhaltungsstrategie soll zukünftig durch eine flexible und prädiktive Instandhaltung ersetzt werden. Hierbei sollen Inspektionen und Instandhaltungsmaßnahmen unterstützt durch autonome Systeme auf der Grundlage von Monitoringdaten geplant und zusätzlich bei unvorhergesehenen Ereignissen ausgelöst werden. Im Rahmen des Verbundforschungsvorhabens AISTEC wird ein Vorgehen für Großbauwerke und kleinere Regelbauwerke zur Umsetzung eines kombinierten globalen, schwingungsbasierten und quasistatischen Monitorings entworfen. An der Maintalbrücke Gemünden - einer semiintegralen Rahmenbrücke aus Spannbeton auf der Schnellfahrstrecke Hannover-Würzburg - wurde als Demonstrator ein Dauermonitoring realisiert. Dresden Technische Universität Dresden 2021 Schriftenreihe Konstruktiver Ingenieurbau Dresden 55 11. Symposium Experimentelle Untersuchungen von Baukonstruktionen (SEUB) Online meeting 08.03.2021 66 76 2021-06-14 OPUS4-52982 Vortrag Schneider, Ronald Sensorbasiertes Monitoring (AP4 + AP7): Ein Überblick Im AISTEC Projekt erforscht der FB 7.2 Verfahren zur Bewertung von Verkehrsbrücken auf der Gruandlage von sensorbasierten Bauwerksmessungen. In diesem Vortrag wird ein Überlick über die Forschungsarbeiten des FB 7.2 präsentiert. Des Weiteren wird ein Ausblick zur quantitativen Integration von sensorbasierten Bauwerksmessungen in die risiko-basierte prädiktive Planung von Inspektionen und Reparaturen von Ingenieurbauwerken gegeben. 2021 AISTEC 5. Verbundtreffen Online meeting 24.06.2021 2021-07-21 OPUS4-52766 Vortrag Schneider, Ronald Integrating vibration monitoring into risk-based inspection and maintenance planning for deteriorating structural systems A reliability and risk-based framework for integrating vibration monitoring data in the planning of inspection and maintenance of deteriorating structural systems is discussed and demonstrated in a numerical example. 2021 Wind Energy Science Conference (WESC 2021) Online Meeting 25.05.2021 28.05.2021 2021-06-09 OPUS4-52767 Vortrag Schneider, Ronald SysPark: a software tool for system-wide adaptive planning of inspections of turbine support structures in offshore wind farms 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. 2021 Wind Energy Science Conference (WESC 2021) Online Meeting 25.05.2021 28.05.2021 2021-06-09 OPUS4-52768 Vortrag Schneider, Ronald Towards predictive maintenance of bridges Key features of predictive maintenance of structural systems are discussed and demonstrated in two examples. Challenges and needs for further research are discussed. 2021 Workshop Bridge Maintenance Online Meeting 09.04.2021 2021-06-09 OPUS4-52769 Beitrag zu einem Tagungsband Schneider, Ronald; Straub, D. Matos, J.C.; Lourenço, P.B.; Oliveira, D.V.; Branco, J.; Proske, D.; Silva, R.A.; Sousa, H.S. Cumulative Failure Probability of Deteriorating Structures: Can It Drop? 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. Cham, Switzerland Springer 2021 18th International Probabilistic Workshop. IPW 2020. Lecture Notes in Civil Engineering 153 18th International Probabilistic Workshop (IPW 2020) Online meeting 12.05.2021 14.05.2021 253 264 10.1007/978-3-030-73616-3_18 2021-06-09 OPUS4-52770 Vortrag Schneider, Ronald Cumulative failure probability of deteriorating structures: Can it drop? 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. 2021 18th Internatinoal Probabilistic Workshop (IPW 2020) Online Meeting 12.05.2021 14.05.2021 2021-06-09 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 OPUS4-55493 Beitrag zu einem Tagungsband Simon, Patrick; Herrmann, Ralf; Schneider, Ronald; Hille, Falk; Baeßler, Matthias; El-Athman, Rukeia Research Data Management of Structural Health Monitoring Projects and Subsequent Applications of Artificial Intelligence Methods 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. Boca Raton CRC Press 2022 Bridge safety, maintenance, management, life-cycle, resilience and sustainability - Proceedings of the eleventh International Conference on Bridge Maintenance, Safety and Management (IABMAS 2022), Barcelona, Spain, July 11-15, 2022 978-1-032-35623-5 11th International Conference on Bridge Maintenance, Safety and Management (IABMAS2022) Barcelona, Spain 11.07.2022 15.07.2022 1061 1068 10.1201/9781003322641-127 2022-08-16 OPUS4-55496 Vortrag Schneider, Ronald Belastungsversuch und Methodenvalidierung an der Maintalbrücke Gemünden 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. 2022 Abschlussveranstaltung AISTEC Berlin, Germany 02.05.2022 2022-08-16 OPUS4-55656 Beitrag zu einem Tagungsband Eichner, Lukas; Gerards, Paul; Herrmann, Ralf; Schneider, Ronald; Hille, Falk; Baeßler, Matthias A framework for data and structural integrity management for support structures in offshore wind farms based on building information modelling 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. Singapore Research Publishing ISRERM Organizers 2022 Proc. of the 8th Intl. Symp. on Reliability Engineering and Risk Management (ISRERM 2022) 8th International Symposium on Reliability Engineering and Risk Management Hannover, Germany 04.09.2022 07.09.2022 111 117 10.3850/978-981-18-5184-1_MS-04-161-cd 2022-09-12 OPUS4-55465 Beitrag zu einem Tagungsband Eichner, Lukas; Schneider, Ronald; Simon, Patrick; Baeßler, Matthias 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 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. ASRANet Ltd 2022 3rd International Conference on Health Monitoring of Civil & Maritime Structures (HeaMES 2022) - Proceedings 978-1-8383226-7-0 3rd International Conference on Health Monitoring of Civil & Maritime Structures (HeaMES 2022) Online meeting 08.06.2022 09.06.2022 23 32 2022-08-10 OPUS4-55770 Vortrag Schneider, Ronald Überwachung von Brücken mit digitalen Methoden 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. 2022 BVPI Arbeitstagung 2022 Berlin, Germany 16.09.2022 17.09.2022 2022-09-21 OPUS4-51333 Vortrag Schneider, Ronald; Herrmann, Ralf Sensorbasiertes Monitoring der Maintalbrücke Gemünden 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. 2020 4. Verbundtreffen AISTEC Weimar, Germany 24.09.2020 24.09.2020 2020-09-30 OPUS4-51297 Dissertation Schneider, Ronald Time-variant reliability of deteriorating structural systems conditional on inspection and monitoring data The current practice of operating and maintaining deteriorating structural systems ensures acceptable levels of structural reliability, but it is not clear how efficient it is. Changing the current prescriptive approach to a risk-based approach has great potential to enable a more efficient management of such systems. Risk-based optimization of operation and maintenance strategies identifies the strategy that optimally balances the cost for controlling deterioration in a structural system with the achieved risk reduction. Inspections and monitoring are essential parts of operation and maintenance strategies. They are typically performed to reduce the uncertainty in the structural condition and inform decisions on future operation and maintenance actions. In risk-based optimization of operation and maintenance strategies, Bayesian updating is used to include information contained in inspection and monitoring data in the prediction of the structural reliability. All computations need to be repeated many times for different potential inspection and monitoring outcomes. This motivates the development of robust and efficient approaches to this computationally challenging task. The reliability of deteriorating structural systems is time-variant because the loads on them and their capacities change with time. In most practical applications, the reliability analysis of deteriorating structural systems can be approached by dividing their lifetime into discrete time intervals. The time-variant reliability problem can then be represented by a series of time-invariant reliability problems. Using this methodology as a starting point, this thesis proposes a novel approach to compute the time-variant reliability of deteriorating structural systems for which inspection and monitoring data are available. The problem is formulated in a nested way in which the prediction of the structural condition is separated from the computation of the structural reliability conditional on the structural condition. Information on the structural condition provided by inspections and monitoring is included in the reliability assessment through Bayesian updating of the system deterioration model employed to predict the structural condition. The updated system reliability is obtained by coupling the updated deterioration model with a probabilistic structural model utilized to calculate the failure probability conditional on the structural condition. This approach is the first main outcome of this thesis and termed nested reliability analysis (NRA) approach. It is demonstrated in two numerical examples considering inspected and monitored steel structures subject to high-cycle fatigue. An alternative - recently developed - approach, which also follows the strategy of discretizing time, describes deteriorating structural systems with hierarchical dynamic Bayesian networks (DBN). DBN combined with approximate or exact inference algorithms also enable the computation of the time-variant reliability of deteriorating structural systems conditional on information provided by inspection and monitoring data. In this thesis - as a proof of concept - a software prototype is developed based on the DBN approach, which can be used to assess the reliability of a corroding concrete box girder for which half-cell potential measurements are available. This is the second main outcome of this thesis. Both approaches presented in this thesis enable an integral reliability analysis of inspected and monitored structures that accounts for system effects arising from (a) the correlation among deterioration states of different structural elements, (b) the interaction between element deterioration and system failure, and (c) the indirect information gained on the condition of all unobserved structural elements from inspecting or monitoring the condition of some structural elements. Thus, both approaches enable a systemwide risk-based optimization of operation and maintenance strategies for deteriorating structural systems. The NRA approach can be implemented relatively easily with subset simulation, which is a sequential Monte Carlo method suitable for estimating rare event probabilities. Subset simulation is robust and considerably more efficient than crude Monte Carlo simulation. It is, however, still sampling-based and its efficiency is thus a function of the number of inspection and monitoring outcomes, as well as the value of the simulated event probabilities. The current implementation of the NRA approach performs separate subset simulation runs to estimate the reliability at different points in time. The efficiency of the NRA approach with subset simulation can be significantly improved by exploiting the fact that failure events in different years are nested. The lifetime reliability of deteriorating structural systems can thus be computed in reverse chronological order in a single subset simulation run. The implementation of the DBN approach is much more demanding than the implementation of the NRA approach but it has two main advantages. Firstly, the graphical format of the DBN facilitates the presentation of the model and the underlying assumptions to stakeholders who are not experts in reliability analysis. Secondly, it can be combined with exact inference algorithms. In this case, its efficiency neither depends on the number of inspection and monitoring outcomes, nor on the value of the event probabilities to be calculated. However, in contrast to the NRA approach with subset simulation, the DBN approach with exact inference imposes restrictions on the number of random variables and the dependence structure that can be implemented in the model. Berlin Bundesanstalt für Materialforschung und -prüfung (BAM) 2020 BAM-Dissertationsreihe 168 1 188 urn:nbn:de:kobv:b43-512977 https://creativecommons.org/licenses/by-nc-nd/4.0/deed.de 2020-09-24 OPUS4-50796 Vortrag Schneider, Ronald Kontinuierliches Bauwerksmonitoring - Sensor-basiert (AP4) 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. 2020 3. Verbundtreffen AISTEC Online meeting 05.05.2020 2020-05-20 OPUS4-48829 Beitrag zu einem Tagungsband Schneider, Ronald Effect of repair models on risk based optimal inspection strategies for support structures of offshore wind turbines 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. 2019 Proceedings of the 5th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures (SMAR 2019) 5th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures (SMAR 2019) Potsdam, Germany 27.08.2019 29.08.2019 Paper Th.2.A.4, 1 8 urn:nbn:de:kobv:b43-488297 https://creativecommons.org/licenses/by/4.0/deed.de 2019-09-03 OPUS4-48830 Vortrag Schneider, Ronald Effect of repair models on risk based optimal inspection strategies for support structures of offshore wind turbines 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. 2019 5th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures (SMAR 2019) Potsdam, Germany 27.08.2019 29.08.2019 2019-09-03 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 OPUS4-51590 Beitrag zu einem Tagungsband Simon, Patrick; Schneider, Ronald; Viefhues, Eva; Said, Samir; Herrmann, Ralf; Baeßler, Matthias Papadrakis, M.; Fragiadakis, M.; Papadimitriou, C. Vibration-based Structural Health Monitoring of a Reinforced Concrete Beam Subjected to Varying Ambient Conditions Using Bayesian Methods 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. Athens, Greece Institute of Structural Analysis and Antiseismic Research, School of Civil Engineering, National Technical University of Athens (NTUA) EASD - European Association for Structural Dynamics 2020 Proceedings of EURODYN 2020, XI International Conference on Structural Dynamics 978-618-85072-2-7 EURODYN 2020, XI International Conference on Structural Dynamics Online meeting 23.11.2020 26.11.2020 1254 2020-11-30 OPUS4-46432 Vortrag Schneider, Ronald 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. 2018 The Sixth International Symposium on Life-Cycle Civil Engineering (IALCCE 2018) Gent, Belgium 28.10.2018 31.10.2018 2018-11-05 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 OPUS4-46436 Vortrag Schneider, Ronald Risikoanalyse technischer Systeme: Aktivitäten an der BAM Die Risikoanalyse ist ein formales Verfahren zur Unterstützung von Entscheidungen unter Unsicherheit und Risiko. Es ermöglicht eine Optimierung von Maßnahmen zur Verhinderung unerwünschter Konsequenzen. Der Vortrag stellt die aktuellen Aktivitäten an der BAM in dem Feld Risikoanalyse technischer System vor. 2018 4. Sitzung des Beirates „Infrastruktur“ der Bundesanstalt für Materialforschung und –prüfung (BAM) Berlin, Germany 19.04.2018 19.04.2018 2018-11-05 OPUS4-46437 Vortrag Schneider, Ronald Bayes'sche Analyse von Ingenieurmodellen 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. 2018 Workshop "Digitaler Zwilling" des BAM Koptenzzentrums „Modellierung und Simulation“ Berlin, Germany 04.06.2018 04.06.2018 2018-11-05 OPUS4-46325 Vortrag Baeßler, Matthias; Schneider, Ronald Anwendung von kontinuierlichen sensor-basierten Monitoringverfahren zur Bewertung von Infrastrukturbauwerken 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´. 2018 Kick-Off AIStec Weimar, Germany 17.10.2018 2018-10-19 OPUS4-57811 Zeitschriftenartikel Schneider, Ronald Von der Datenerfassung bis zur Entscheidungsfindung: Jede Brücken-Überwachung bedarf einer Gesamtmethodik 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. Bundesvereinigung der Prüfingenieure für Bautechnik e. V. 2023 Der Prüfingenieur 62 76 83 2023-07-03 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 OPUS4-57863 Vortrag Schneider, Ronald Vibration-based system identification of a large steel box girder bridge 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. 2023 XII International Conference on Structural Dynamics (EURODYN 2023) Delft, Netherlands 02.07.2023 05.07.2023 2023-07-07 OPUS4-57864 Vortrag Schneider, Ronald Structural integrity management research at BAM 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. 2023 Structural Health Monitoring Using Statistical Pattern Recognition Berlin, Germany 20.03.2023 23.03.2023 2023-07-07 OPUS4-58101 Vortrag Schneider, Ronald Vibration-based system identification of a large steel box girder bridge 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. 2023 XII International Conference on Structural Dynamics (EURODYN 2023)) Delft, Netherlands 02.07.2023 05.07.2023 2023-09-04 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 OPUS4-58208 Zeitschriftenartikel Lesny, K.; Arnold, P.; Sorgatz, J.; Schneider, Ronald Wie sicher sind unsere Bauwerke? - Strukturpapier des Arbeitskreises 2.15 der DGGT „Zuverlässigkeitsbasierte Methoden in der Geotechnik" 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 Berlin Ernst & Sohn GmbH 2023 geotechnik 46 3 153 164 10.1002/gete.202300014 2023-09-11