TY - CONF A1 - Schneider, Ronald T1 - Zuverlässigkeitsbasierte Bauwerksbewertung N2 - Die BAM erforscht mit Partnern an der TUM und DTU Methoden und Modelle für ein optimiertes Tragwerksmanagement von Infrastrukturbauwerken. Im Rahmen des vom BMVI und der BASt aufgelegten Projektclusters „Intelligente Brücke“ wurde ein Software-Prototyps zur zuverlässigkeitsbasierten Bewertung eines konkreten Spannbetonüberbaus unter Berücksichtigung von Inspektionen und Überwachungssystemen entwickelt. Der entwickelte Software-Prototyp ermöglicht Benutzern ohne vertiefte Kenntnisse der Zuverlässigkeitstheorie eine Berechnung des Einflusses von Bauwerksinformationen auf den Systemschädigungszustand und die Tragsicherheit. Auf dieser Grundlage können effiziente Inspektions- und Überwachungsmaßnahmen identifiziert und das Erhaltungsmanagement optimiert werden. T2 - BASt Symposium Intelligente Brücken - Der Weg in die Praxis CY - Bergisch Gladbach, Germany DA - 30.11.2015 KW - Intelligente Brücken KW - Brücken KW - Alterung KW - Bauwerksbewertung PY - 2015 AN - OPUS4-36537 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - RPRT A1 - Schneider, Ronald A1 - Fischer, J. A1 - Straub, D. A1 - Thöns, S. A1 - Bügler, M. A1 - Borrmann, A. T1 - Intelligente Bauwerke - Prototyp zur Ermittlung der Schadens- und Zustandsentwicklung für Elemente des Brückenmodells T2 - Berichte der Bundesanstalt für Straßenwesen N2 - Dieser Bericht beschreibt ein Systemmodell für eine integrale Ermittlung und Prognose der Schadens- und Zustandsentwicklung der Elemente eines Brückensystems unter Berücksichtigung von Ergebnissen aus Inspektionen und Überwachung. Das Systemmodell wurde anhand eines ausgesuchten Spannbetonüberbaus in einzelliger Kastenbauweise entwickelt. Es besteht aus zwei integralen Teilmodellen: ein Modell zur Beschreibung des Systemschädigungszustandes und ein Modell zur Beschreibung der Standsicherheit. Für die Modellierung des stochastischen Systemschädigungszustandes eines Brückensystems werden dynamische Bayes'sche Netze (DBN) vorgeschlagen. Dieser Ansatz ermöglicht es, alle relevanten Schädigungsprozesse und deren stochastische Abhängigkeiten zu berücksichtigen. Ein wesentlicher Vorteil dieses Ansatzes ist es, dass DBN ideal dafür geeignet sind, Bayes'sche Aktualisierungen auf Grundlage von Informationen aus Inspektionen und Überwachungsmaßnahme auf eine effiziente und robuste Art und Weise durchzuführen. Der DBN-Ansatz ist deshalb für die Entwicklung von Software für das Erhaltungsmanagement von alternden Brückenbauwerken, die vom Benutzer keine vertieften Kenntnisse der Zuverlässigkeitstheorie verlangt, ideal geeignet. Für die Modellierung der Standsicherheit eines alternden Kastenträgers wird vereinfachend Biegeversagen des globalen Längssystems betrachtet. Zur Berechnung der maximalen Traglast eines Kastenträgers infolge des Systemschädigungszustandes wird ein plastisch-plastisches Verfahren eingesetzt, wobei die Beanspruchungen mittels der Fließgelenktheorie unter Ausnutzung der plastischen Beanspruchbarkeit der Querschnitte des Kastenträgers ermittelt werden. Ein Kastenträger versagt, wenn sich durch die Ausbildung einer ausreichend großen Anzahl von Fließgelenken eine kinematische Kette ausbildet. Dieser Modellierungsansatz berücksichtigt Redundanzen, die sich aus der plastischen Beanspruchbarkeit der Querschnitte und der statischen Unbestimmtheit eines Kastenträgers ergeben. Zum Nachweis der praktischen Einsetzbarkeit des entwickelten Systemmodells wurde ein Software-Prototyp entwickelt, der eine intuitiv benutzbare graphische Benutzeroberfläche (Front-End) mit einem Berechnungskern (Back-End) koppelt. Die aktuelle Version des Software-Prototyps implementiert ein Modell der chloridinduzierten Bewehrungskorrosion und ein Tragwerksmodell, welches das Verfahrens der stetigen Laststeigerung zur Bestimmung der maximalen Traglast des Kastenträgers auf der Grundlage eines Finite-Elemente-Modells umsetzt. Zur Durchführung von Bayes'schen Aktualisierungen des Systemschädigungszustandes auf der Grundlage des DBN-Modells implementiert der Prototyp den Likelihood-Weighting-Algorithmus. Die entwickelte Architektur des Prototyps ermöglicht eine Erweiterung der Software um weitere Schädigungsprozesse. Der entwickelte Software-Prototyp ermöglicht Benutzern ohne vertiefte Kenntnisse der Zuverlässigkeitstheorie eine Berechnung des Einflusses von Bauwerksinformationen auf den Systemschädigungszustand und die Tragsicherheit eines Kastenträgers. Auf dieser Grundlage können effiziente Inspektions- und Überwachungsmaßnahmen identifiziert und das Erhaltungsmanagement optimiert werden. KW - Bridge KW - Condition survey KW - Damage KW - Deterioration KW - Development KW - Digital model KW - Durability KW - Engineering structure KW - Expert system KW - Forecast KW - Germany KW - Propability KW - Prototype KW - Reinforced concrete KW - Research report KW - Software KW - Stability KW - Stochastic process PY - 2015 UR - http://bast.opus.hbz-nrw.de/volltexte/2015/1615/ SN - 978-3-95606-190-5 SN - 0943-9293 VL - 117 SP - 1 EP - 74 PB - Carl Schünemann Verlag GmbH CY - Bergisch Gladbach AN - OPUS4-35193 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 - Simon, Patrick A1 - Baeßler, Matthias T1 - Integrating vibration monitoring into risk-based inspection and maintenance planning for deteriorating structural systems N2 - 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. T2 - Wind Energy Science Conference (WESC 2021) CY - Online Meeting DA - 25.05.2021 KW - Deterioration KW - Structural systems KW - Inspection KW - Vibration monitoring KW - Maintenance PY - 2021 AN - OPUS4-52766 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick A1 - Schneider, Ronald A1 - Baeßler, Matthias A1 - Recknagel, Christoph ED - Cunha, Á. ED - Caetano, E. 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 T2 - International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-10) 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 SN - 2564-3738 SP - 1537 EP - 1544 AN - OPUS4-54126 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 - GEN A1 - Farhan, Muhammad A1 - Schneider, Ronald A1 - Thöns, Sebastian T1 - Corrigendum to Predictive information and maintenance optimization based on decision theory: a case study considering a welded joint in an offshore wind turbine support structure T2 - Structural health monitoring N2 - This article has been revised and republished due to substantial changes to the text of the original article, as published Online First on January 31, 2021. Most of the change were minor grammatical changes. The following changes are more significant and will be highlighted below. KW - Integrity management KW - Decision theory KW - Value of information KW - Structural reliability KW - Fracture mechanics KW - Fatigue KW - Predictive maintenance KW - Wind turbine support structure PY - 2022 DO - https://doi.org/10.1177/14759217211040385 SN - 1475-9217 VL - 21 IS - 4 SP - 1956 EP - 1956 PB - Sage Publications CY - London AN - OPUS4-55165 LA - eng 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 - Road bridges KW - Fatigue KW - Operational modal analysis KW - System identification PY - 2023 AN - OPUS4-58101 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Thöns, Sebastian A1 - Rogge, Andreas ED - Bucher, Christian ED - Ellingwood, Bruce R. ED - Frangopol, Dan M. T1 - Simulating the service life performance of an inspected group of jacket-type structures T2 - Proceedings of the 12th International Conference on Structural Safety and Reliability N2 - A novel method for risk-based optimization of inspection and repair strategies for deteriorating structural systems has recently been proposed. The method defines heuristics at the system level to reduce the number of possible strategies. For each defined strategy, it computes the updated system failure probability conditional on simulated inspection and repair histories, and evaluates the associated costs and risk. The expected total service life costs and risk for a strategy are finally determined using Monte Carlo simulation. The optimal strategy minimizes the expected total service life costs and risk. We intend to adopt this approach to optimize inspection, monitoring and repair activities for offshore wind park support structures. As a first step, we simulate – in analogy to an offshore wind park – the service life performance of an inspected group of jacket-type frames. The performance is quantified in terms of the group’s system failure probability conditional on simulated inspection and repair histories. The underlying system model accounts for the structural redundancy of the frames and the interdependence among their failure events due to similar loading conditions. The model also captures stochastic dependence among the deterioration states of the frames. As part of the simulation process the a-priori unknown outcome of any planned inspection is generated conditional on the outcome of all previous inspections. T2 - 12th International Conference on Structural Safety and Reliability CY - Vienna, Austria DA - 06.08.2017 KW - Reliability KW - Fatigue KW - Inspection KW - Service life performance KW - Inspection planning PY - 2017 SN - 978-3-903024-28-1 SP - 2738 EP - 2747 PB - TU-MV Media Verlag GmbH CY - Vienna, Austria AN - OPUS4-41344 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Thöns, Sebastian A1 - Rogge, Andreas T1 - Simulating the service life performance of an inspected group of jacket-type structures N2 - A novel method for risk-based optimization of inspection and repair strategies for deteriorating structural systems has recently been proposed. The method defines heuristics at the system level to reduce the number of possible strategies. For each defined strategy, it computes the updated system failure probability conditional on simulated inspection and repair histories, and evaluates the associated costs and risk. The expected total service life costs and risk for a strategy are finally determined using Monte Carlo simulation. The optimal strategy minimizes the expected total service life costs and risk. We intend to adopt this approach to optimize inspection, monitoring and repair activities for offshore wind park support structures. As a first step, we simulate – in analogy to an offshore wind park – the service life performance of an inspected group of jacket-type frames. The performance is quantified in terms of the group’s system failure probability conditional on simulated inspection and repair histories. The underlying system model accounts for the structural redundancy of the frames and the interdependence among their failure events due to similar loading conditions. The model also captures stochastic dependence among the deterioration states of the frames. As part of the simulation process the a-priori unknown outcome of any planned inspection is generated conditional on the outcome of all previous inspections. T2 - 12th International Conference on Structural Safety and Reliability CY - Vienna, Austria DA - 06.08.2017 KW - Structural reliability KW - Inspection KW - Fatigue KW - Inspection planning PY - 2017 AN - OPUS4-41346 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald T1 - Konzept zur Einbindung der Strukturüberwachung in die risikobasierte Inspektionsplanung von Offshore-Strukturen N2 - Das Ermüdungsverhalten einzelner Schweißverbindungen in Offshore-Strukturen ist stark korreliert. Diese Korrelation entsteht zum einen durch die Verwendung gleicher Prozesse und Materialien bei der Herstellung der Verbindungen, zum anderen sind die ermüdungswirksamen Lasten an verschiedene Hospots im Tragwerk ebenfalls von einander abhängig. Hieraus ergeben sich Systemeffekte, die es ermöglichen, durch stichprobenartige Inspektion des Zustandes einzelner Hotspots auf den Zustand der verbleibenden Hotspots im Tragwerk zu schließen. Auf dieser Grundlage können Inspektions- und Reparaturstrategien für ermüdungsbeanspruchte Offshore-Strukturen mit Hilfe von riskobasierten Methoden optimiert werden. In diesem Vortrag wird weiterführend ein Konzept zur Einbindung von globalen Monitoringergebnissen in die risikobasierte Inspektionsplanung vorgestellt. T2 - 29. Sitzung des VDI/VDE-GMA Fachausschuss 2.12 Strukturanalyse und -überwachung in der Bautechnik im Fachbereich Prozessmesstechnik und Strukturanalyse CY - Bremen, Germany DA - 06.09.2017 KW - Ermüdung KW - Offshore-Strukturen KW - Risikobasierte Inspektionsplanung KW - Monitoring PY - 2017 AN - OPUS4-41865 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Cuéllar, Pablo A1 - Baeßler, Matthias T1 - Probabilistic approaches to the design and assessment of offshore foundations considering spatially varying site conditions N2 - 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. T2 - 3rd International Conference on Structural Integrity for Offshore Energy Industry (SI 2021) CY - Online meeting DA - 15.11.2021 KW - Offhore KW - Foundations KW - Probabilistic KW - Design KW - Assessment PY - 2021 AN - OPUS4-53748 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald T1 - Towards predictive maintenance of bridges N2 - Key features of predictive maintenance of structural systems are discussed and demonstrated in two examples. Challenges and needs for further research are discussed. T2 - Workshop Bridge Maintenance CY - Online Meeting DA - 09.04.2021 KW - Predictive maintenance KW - Deterioration KW - Structural systems PY - 2021 AN - OPUS4-52768 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Simon, Patrick A1 - Herrmann, Ralf A1 - Baeßler, Matthias T1 - Kontinuierliches Bauwerksmonitoring – Sensor-basiert (AP4) 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 - 3. Verbundtreffen AISTEC CY - Online meeting DA - 05.05.2020 KW - Zivile Sicherheit KW - Brücken KW - Structural Health Monitoring PY - 2020 AN - OPUS4-50796 LA - deu 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 - TY - CONF A1 - Schneider, Ronald A1 - Thöns, Sebastian A1 - Rücker, Werner A1 - Straub, D. ED - Deodatis, G. ED - Ellingwood, B.R. ED - Frangopol, D.M. T1 - Effect of different inspections strategies on the reliability of Daniels systems subjected to fatigue T2 - ICOSSAR'13 - 11th International conference on structural safety and reliability - Safety, reliability, risk and life-cycle performance of structures and infrastructures (Proceedings) N2 - Inspections are an efficient means of enhancing the reliability of redundant structural Systems subjected to fatigue. To investigate the effect of such inspections, we represent the deterioration state of a Daniels System by means of a probabilistic fatigue crack growth model of all elements, which considers stochastic dependence among element fatigue behavior. We include inspection results in the calculation of the System collapse probability through Bayesian updating of the System deterioration state. Based on this approach, we calculate the collapse probability of a deteriorating Daniels System conditional on different inspection strategies in terms of inspection coverage and inspection times. The acceptability of an inspection strategy is verified by comparing the calculated collapse probabilities with maximum acceptable System failure probabilities. This study is a Step towards identifying optimal inspection strategies for redundant structural Systems subjected to fatigue. T2 - 11th International conference on structural safety and reliability - Safety, reliability, risk and life-cycle performance of structures and infrastructures CY - New York, USA DA - 16.06.2013 PY - 2013 SN - 978-1-138-00086-5 SN - 978-1-315-88488-2 SP - 1 EP - 8 PB - CRC Press CY - Leiden, The Netherlands AN - OPUS4-28984 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - THES A1 - Schneider, Ronald T1 - Time-variant reliability of deteriorating structural systems conditional on inspection and monitoring data T2 - BAM-Dissertationsreihe N2 - 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. T3 - BAM Dissertationsreihe - 168 KW - Reliability KW - Structural systems KW - Deterioration KW - Bayesian analysis KW - Inspection KW - Monitoring KW - Zuverlässigkeit KW - Tragstrukturen KW - Schädigungsprozesse KW - Bayes'sche Analyse KW - Inspektion KW - Monitoring PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-512977 SN - 1613-4249 VL - 168 SP - 1 EP - 188 PB - Bundesanstalt für Materialforschung und -prüfung (BAM) CY - Berlin AN - OPUS4-51297 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Herrmann, Ralf A1 - Schneider, Ronald A1 - Simon, Patrick A1 - Hille, Falk A1 - Said, Samir A1 - Baeßler, Matthias ED - Curbach, M. ED - Marx, S. ED - Scheerer, S. ED - Hampel, T. T1 - Structural Health Monitoring der Maintalbrücke Gemünden zur Unterstützung einer prädiktiven Instandhaltung T2 - Schriftenreihe Konstruktiver Ingenieurbau Dresden N2 - 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. T2 - 11. Symposium Experimentelle Untersuchungen von Baukonstruktionen (SEUB) CY - Online meeting DA - 08.03.2021 KW - Structural Health Monitoring KW - Umwelteinflüsse KW - Prädiktive Instandhaltung PY - 2021 UR - https://tu-dresden.de/bu/bauingenieurwesen/imb/ressourcen/dateien/veranstaltungen/seub/11-seub-2021/2021_SEUB11_06_Herrmann_et_al.pdf?lang=de VL - 55 SP - 66 EP - 76 PB - Technische Universität Dresden CY - Dresden AN - OPUS4-52810 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kinne, Marko A1 - Farhan, Muhammad A1 - Schneider, Ronald A1 - Thöns, Sebastian T1 - Influence of the structural integrity management on the levelized cost of energy of offshore wind: a parametric sensitivity analysis T2 - International Probabilistic Workshop 2022 N2 - The levelized cost of energy (LCoE) is an important measure to quantify the macro-economic efficiency of an offshore wind farm and to enable a quantitative comparison with other types of energy production. The costs of the structural integrity management - which is required to ensure an adequate lifetime reliability of the turbine support structures - are part of the operational expenditures of an offshore wind farm. An optimization of the structural integrity management may reduce the operational expenditures and consequently the LCoE. However, the effect of the structural integrity management on the LCoE is hardly known. To investigate this effect, this paper presents a sensitivity analysis of the LCoE of a generic offshore wind farm. The probabilistic models of the parameters influencing the LCoE are based on a literature study including an explicit model for the structural integrity management. The analysis reveals that LCoE may potentially be reduced if an optimization of the structural integrity management enables a service life extension. T2 - International Probabilistic Workshop 2022 CY - Stellenbosch, South Africa DA - 08.09.2022 KW - Structural integrity management KW - Levelized cost of energy KW - Sensitivity analysis PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-572724 DO - https://doi.org/10.14311/APP.2022.36.0090 VL - 36 SP - 90 EP - 98 PB - Acta Polytechnica CTU Proceedings AN - OPUS4-57272 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kinne, Marko A1 - Schneider, Ronald A1 - Thöns, Sebastian T1 - Reconstructing Stress Resultants in Wind Turbine Towers Based on Strain Measurements N2 - Support structures of offshore wind turbines are subject to cyclic stresses generated by different time-variant random loadings such as wind, waves, and currents in combinationwith the excitation by the rotor. In the design phase, the cyclic demand on wind turbine support structure is calculated and forecasted with semi or fully probabilistic engineering models. In some cases, additional cyclic stresses may be induced by construction deviations, unbalanced rotor masses and structural dynamic phenomena such as, for example, the Sommerfeld effect. Both, the significant uncertainties in the design and a validation of absence of unforeseen adverse dynamic phenomena necessitate the employment of measurement Systems on the support structures. The quality of the measurements of the cyclic demand on the support structures depends on (a) the precision of the measurement System consisting of sensors, amplifier and data normalization and (b) algorithms for analyzing and converting data to structural health information. This paper presents the probabilistic modelling and analysis of uncertainties in strain measurements performed for the purposes of reconstructing stress resultants in wind turbine towers. It is shown how the uncertainties in the strain measurements affect the uncertainty in the individual components of the reconstructed forces and moments. The analysis identifies the components of the vector of stress resultants that can be reconstructed with sufficient precision. T2 - International Conference on Uncertainty in Mechanical Engineering - ICUME CY - Online meeting DA - 07.06.2021 KW - Reconstruction of stress resultants KW - Strain measurements KW - Bayesian updating of measurement uncertainties PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-527987 DO - https://doi.org/10.1007/978-3-030-77256-7_18 SP - 224 EP - 235 PB - Springer AN - OPUS4-52798 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Cuéllar, Pablo A1 - Baeßler, Matthias T1 - Probabilistic approaches to the design and assessment of offshore foundations considering spatially varying site conditions T2 - Proceedings of the 3rd International Conference on Structural Integrity for Offshore Energy Industry (SI 2021) N2 - 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. T2 - 3rd International Conference on Structural Integrity for Offshore Energy Industry (SI 2021) CY - Online meeting DA - 15.11.2021 KW - Probabilistic modelling KW - Spatially varying ground conditions KW - Foundation reliability analysis KW - Monopile installation risks PY - 2022 SN - 978-1-8383226-3-2 SP - 9 EP - 17 AN - OPUS4-54531 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald T1 - Risikoanalyse technischer Systeme: Aktivitäten an der BAM N2 - 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. T2 - 4. Sitzung des Beirates „Infrastruktur“ der Bundesanstalt für Materialforschung und –prüfung (BAM) CY - Berlin, Germany DA - 19.04.2018 KW - Risiko KW - Risikoanalyse PY - 2018 AN - OPUS4-46436 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Fischer, J. A1 - Straub, D. A1 - Thöns, Sebastian A1 - Rücker, Werner T1 - Intelligente Bauwerke - Zuverlässigkeitsbasierte Bewertung von Brückenbauwerken unter Berücksichtigung von Inspektions- und Überwachungsergebnissen T2 - BASt Bundesanstalt für Staßenwesen, Betreuungstreffen "Intelligente Bauwerke" T2 - BASt Bundesanstalt für Staßenwesen, Betreuungstreffen "Intelligente Bauwerke" CY - Bergisch Gladbach, Germany DA - 2012-11-28 PY - 2012 AN - OPUS4-27198 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Simon, Patrick A1 - Herrmann, Ralf A1 - Baeßler, Matthias T1 - Sensorbasiertes Monitoring (AP4 + AP7): Ein Überblick N2 - 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. T2 - AISTEC 5. Verbundtreffen CY - Online meeting DA - 24.06.2021 KW - AISTEC KW - Structural Health Monitoring KW - Brücken PY - 2021 AN - OPUS4-52982 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - 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 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 - 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 - 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 - RPRT A1 - Fischer, J. A1 - Straub, D. A1 - Schneider, Ronald A1 - Thöns, Sebastian A1 - Rücker, Werner T1 - Intelligente Brücke - Zuverlässigkeitsbasierte Bewertung von Brückenbauwerken unter Berücksichtigung von Inspektions- und Überwachungsergebnissen T2 - Berichte der Bundesanstalt für Straßenwesen, Reihe B: Brücken- und Ingenieurbau N2 - Der vorliegende Bericht beschreibt Konzepte für eine intelligente Brücke auf der Grundlage einer zuverlässigkeitsbasierten Zustandsbewertung unter Berücksichtigung von Bauwerksinformationen, welche aus Prüfungen, Inspektionen und Überwachung gewonnen werden. Das Brückensystem wird durch ein Modell beschrieben, welches den zentralen Teil des Konzeptes darstellt. Das Modell wird in Schädigungsmodelle und ein Tragwerkssystem-Modell unterteilt. Dieses Modell wird a-priori durch die Eingangsdaten (welche etwa die Geometrie, die Materialien und die Verwendung der Brücke beschreiben) charakterisiert. Aus diesen ergeben sich dann auch die Ausgangsmodelle. Um die signifikanten Streuungen und Unsicherheiten adäquat abzubilden sind diese Modelle probabilistisch. Das Modell liefert eine sich kontinuierlich ändernde probabilistische Zustandsbewertung. Die Zustandsbewertung gibt eine Aussage über den Zustand und die Zuverlässigkeit des Brückensystems und seiner Bauteile und dient als Grundlage für die Planung und die Optimierung von Maßnahmen. Die Verwendung von Resultaten aus Inspektionen, Prüfungen und Überwachungen erfolgt durch eine Aktualisierung der Modellparameter. Die Aktualisierung beruht auf der Methode der Bayes'schen Aktualisierung und wird auf der Grundlage der entwickelten Klassifizierung der Bauwerksinformationen mit entsprechenden Methoden durchgeführt. Dieses Verfahren erlaubt es, alle Informationen in konsistenter Weise in ein einziges Modell einfließen zu lassen. Dabei wird die Genauigkeit und Aussagekraft der gewonnenen Daten und Beobachtungen explizit berücksichtigt. Durch die Aktualisierung der Modellparameter unter Berücksichtigung von Systemeffekten wird die Zustandsbewertung der Bauteile und des Brückensystems aktualisiert. Das ermöglicht die Planung und die Optimierung von Maßnahmen unter Berücksichtigung der Bauwerksinformationen. Auf diese Weise wird die intelligente Brücke mit Inspektionen und Überwachungen zu einem adaptiven System, welches sich Veränderungen anpassen kann.---------------------------------------------------------------------------------------------------------------------------------------------------------------------------This report describes concepts for an intelligent bridge on the basis of a reliability-based condition assessment utilizing inspection and monitoring data. The central part of the concept is a model describing the bridge system. The overall bridge model is comprised of deterioration models and a mechanical system model of the structure. The model is a-priori characterized by the input data (such as the geometry, the materials, and the utilization of the bridge). Significant uncertainties in the deterioration modeling as well as the load conditions motivate a probabilistic modeling. The model enables a continuously updated probabilistic condition assessment. It provides information about the condition and the reliability of the bridge system and its components and serves as a basis for the planning and the optimization of maintenance actions. Inspection, measurement, and monitoring information are included by updating the model parameters. Bayesian updating is utilized for the updating of the model parameters and is performed on the basis of the developed classification of structural information and the corresponding procedures. These methodologies allow to consistently incorporate all available information into the model and the prediction. Thereby, the precision and the validity of the data and observations are explicitly accounted for. The condition assessment of the bridge system and its components is updated by updating the model parameters, and maintenance actions can be planned and optimized taking into account all available information in a rational and consistent manner. In this way, the intelligent bridge with inspections, measurements, and monitoring information becomes an adaptive system, which has the ability to adjust to changes. KW - Berechnung KW - Brücke KW - Dauerhaftigkeit KW - Deutschland KW - Echtzeit KW - Forschungsbericht KW - Kontinuierlich KW - Kontrolle KW - Messung KW - Prognose KW - Prüfverfahren KW - Rechenmodell KW - Sachschaden KW - Tragfähigkeit KW - Wahrscheinlichkeit KW - Zustandsbewertung PY - 2014 UR - http://bast.opus.hbz-nrw.de/volltexte/2014/768/pdf/BASt_B_99_ELBA_PDF.pdf SN - 978-3-95606-078-6 SN - 0943-9293 IS - B 99 SP - 1 EP - 111 PB - Fachverlag NW in der Carl Schünemann Verlag GmbH CY - Bremen AN - OPUS4-31300 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald T1 - System reliability updating of welded jacket-type structures subjected to fatigue with global monitoring information T2 - 1st workshop of COST Action TU 1402: Quantifying the Value of Structural Health Monitoring T2 - 1st workshop of COST Action TU 1402: Quantifying the Value of Structural Health Monitoring CY - Lyngby, Denmark DA - 2015-05-04 PY - 2015 AN - OPUS4-33198 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Thöns, S. A1 - Fischer, J. A1 - Bügler, M. A1 - Borrmann, A. A1 - Straub, D. T1 - Schädigungs- und Strukturmodelle / Bewertung T2 - Workshop "Intelligente Brücken - Poteniale und Chancen" T2 - Workshop "Intelligente Brücken - Poteniale und Chancen" CY - Bundesanstalt für Straßenwesen (BASt), Bergisch Gladbach, Deutschland DA - 2014-09-15 PY - 2014 AN - OPUS4-32217 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Thöns, S. A1 - Fischer, J. A1 - Bügler, M. A1 - Borrmann, A. A1 - Straub, D. T1 - A software prototype for assessing the reliability of a concrete bridge superstructure subjected to chloride-induced reinforcement corrosion T2 - Fourth International Symposium on Life-Cycle Civil Engineering (IALCCE 2014) T2 - Fourth International Symposium on Life-Cycle Civil Engineering (IALCCE 2014) CY - Tokyo, Japan DA - 2014-11-16 PY - 2014 AN - OPUS4-32218 LA - deu 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 T2 - 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 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 - 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 T2 - Proceedings of EURODYN 2020, XI International Conference on Structural Dynamics 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 T2 - 3rd International Conference on Health Monitoring of Civil & Maritime Structures (HeaMES 2022) - Proceedings 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 - Schneider, Ronald A1 - Thöns, Sebastian A1 - Straub, D. T1 - Reliability-based inspection planning with application to orthotropic bridge deck structures T2 - Third International Symposium on Life-Cycle Civil Engineering (IALCCE'12) T2 - Third International Symposium on Life-Cycle Civil Engineering (IALCCE'12) CY - Vienna, Austria DA - 2012-10-03 PY - 2012 AN - OPUS4-26633 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Thöns, Sebastian A1 - Straub, D. T1 - Probabilistic fatigue crack growth modeling for reliability-based inspection planning T2 - Third International Symposium on Life-Cycle Civil Engineering (IALCCE'12) T2 - Third International Symposium on Life-Cycle Civil Engineering (IALCCE'12) CY - Vienna, Austria DA - 2012-10-03 PY - 2012 AN - OPUS4-26634 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Thöns, Sebastian A1 - Rücker, Werner A1 - Straub, D. T1 - Effect of different inspection strategies on the reliability of Daniels systems subjected to fatigue T2 - ICOSSAR 2013, 11th International Conference on Structural Safety & Reliability T2 - ICOSSAR 2013, 11th International Conference on Structural Safety & Reliability CY - New York, NY, USA DA - 2013-06-16 PY - 2013 AN - OPUS4-28821 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald T1 - Updating of fatigue reliability with inspection data using subset simulation - problems encountered T2 - Seminars in Engineering Risk Analysis & Probabilistic Modelling T2 - Seminars in Engineering Risk Analysis & Probabilistic Modelling CY - Munich, Germany DA - 2013-05-22 PY - 2013 AN - OPUS4-28822 LA - deu 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“ JF - 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 JF - Der Prüfingenieur 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 - 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 A1 - Thöns, S. A1 - Fischer, J. A1 - Bügler, M. A1 - Borrmann, A. A1 - Straub, D. T1 - A software prototype for assessing and updating the reliability of a deteriorating concrete bridge deck T2 - JCSS Workshop on "Risk and reliability based assessment of existing structures in the framework of the Eurocodes" T2 - JCSS Workshop on "Risk and reliability based assessment of existing structures in the framework of the Eurocodes" CY - Ghent, Belgium DA - 2014-10-01 PY - 2014 AN - OPUS4-32219 LA - deu 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 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 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 - 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 -