TY - JOUR A1 - Weise, Frank A1 - Stelzner, Ludwig A1 - Recknagel, Christoph A1 - Pittrich, Tim A1 - Neugum, Tim A1 - Hering, Marcus A1 - Fiedler, Georg A1 - Thiele, Marc A1 - Simon, Patrick A1 - Maack, Stefan T1 - 63. DAfStb-Forschungskolloquium in der BAM - Themenblock 5: Bauteile und Bauwerke N2 - Ein weiterer Fokus des 63. DAfStb-Forschungskolloquiums (Tagungsband: DOI 10.26272/opus4-61338) lag auf den Bauteil- und Bauwerksuntersuchungen. Insbesondere wurde hier ein Einblick in die Forschungsaktivitäten in den BAM-Themenfeldern „Infrastruktur“ und „Energie“ gegeben. Thematisch wird dabei der Bogen von der Dauerhaftigkeit von Betonfahrbahndecken über die Extrembeanspruchung von Bauteilen und Bauwerken mittels Brand und Impact bis zum Bauwerksmonitoring und der Zustandsanalyse von Bestandsbauwerken gespannt. T2 - 11. Jahrestagung des DAfStb mit 63. Forschungskolloquium der BAM Green Intelligent Building CY - Berlin, Germany DA - 16.10.2024 KW - Dauerhaftigkeit von Betonfahrbahndecken KW - Alkali-Kieselsäurereaktion KW - Brand Impact KW - Bauwerksmonitoring PY - 2025 SN - 0005-9846 VL - 75 IS - 4 SP - 138 EP - 140 PB - concrete content UG CY - Schermbeck AN - OPUS4-63071 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Schneider, Ronald A1 - Simon, Patrick A1 - Herrmann, Ralf A1 - Hille, Falk A1 - Baeßler, Matthias T1 - Bestandteile Digitaler Zwillinge im Erhaltungsmanagement von Verkehrsbrücken T1 - Components of digital twins in the operation and maintenance management of traffic bridges N2 - Digitale Zwillinge werden zukünftig ein integraler Bestandteil des Erhaltungsmanagements von Verkehrsbrücken sein. In diesem Beitrag wird argumentiert, dass sie nicht nur als digitale Abbilder physikalischer Bauwerke verstanden werden sollten, sondern als eine umfassende digitale Methode, die durch die Integration von Datenerfassung, Erhaltungsmaßnahmen, Datenmanagement, Bauwerksbewertung und Entscheidungsunterstützung die Bauwerksüberwachung und ‐erhaltung verbessert. In diesem Zusammenhang wird betont, dass der Übergang von der reaktiven zur prädiktiven Erhaltung durch den Einsatz von Digitalen Zwillingen nur dann realisierbar ist, wenn neben den erforderlichen diagnostischen und prognostischen Zustandsanalysen auch Methoden zur Optimierung von Entscheidungen über Datenerfassung und Erhaltungsmaßnahmen implementiert werden. Zur Veranschaulichung der Diskussion werden in diesem Beitrag exemplarisch zwei Bestandteile eines Digitalen Zwillings für das Erhaltungsmanagement von Verkehrsbrücken am Beispiel einer Eisenbahnbrücke demonstriert. Dabei wird zum einen gezeigt, wie Monitoringdaten mittels eines Datenmanagementsystems strukturiert verwaltet und für angeknüpfte Analysen bereitgestellt werden. Zum anderen erfolgt im Rahmen einer bauwerksspezifischen Einwirkungsermittlung eine Zugidentifikation anhand von gemessenen Schwellenschwingungen. N2 - Digital twins will become an integral part of the operation and maintenance management of traffic bridges in the future. This paper argues that they should not only be understood as digital representations of physical structures but as a digital methodology that enhances the operation and maintenance of bridges through the integration of data collection, maintenance actions, data management, structural assessment, and decision support. In this context, it is emphasized that the transition from reactive to predictive maintenance using digital twins can only be achieved if, in addition to the necessary diagnostic and prognostic condition analyses, methods for optimizing decisions on data collection and maintenance actions are also implemented. To illustrate this discussion, two key components of a digital twin for the operation and maintenance management of traffic bridges are demonstrated using a railway bridge as an example. First, it is shown how monitoring data can be systematically managed and made available for subsequent analyses through a data management system. Second, train identification based on measured sleeper vibrations is conducted as part of an object-specific load assessment. KW - Digitale Zwillinge KW - Erhaltung KW - Inspektion KW - Monitoring KW - Brücken PY - 2025 DO - https://doi.org/10.1002/bate.202400101 SN - 1437-0999 SP - 1 EP - 11 PB - Ernst & Sohn CY - Berlin AN - OPUS4-62837 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Simon, Patrick A1 - Helmrich, M. A1 - Herrmann, Ralf A1 - Schneider, Ronald A1 - Baeßler, Matthias A1 - Lorelli, S. A1 - Morgenthal, G. T1 - Maintalbrücke Gemünden: Bauwerksmonitoring und -identifikation aus einem Guss T1 - Maintalbrücke Gemünden – Integrated structural health monitoring and UAS diagnostics N2 - 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. N2 - Infrastructure systems of industrialised countries today and in the future require efficient management with an ageing stock, increasing loads while simultaneously maintaining a high level of safety. Digital technologies offer great potential for the current and future challenges in infrastructure management. The BMBF-funded project AISTEC is investigating how the individual technologies and their interconnection can be used beneficially. With the Maintalbrücke in Gemünden as an exemplary application, sensor-based structural monitoring, image-based inspection using unmanned aircraft systems (UAS) equipped with cameras and the integration of digital structural models are being implemented. The recorded images serve, among others, as basis for subsequent anomaly detection and a 3D reconstruction, which in turn are used for updating digital structural models. Continuously recorded sensor data is used to update the parameters of the structural models, which in turn provide the basis for predictive maintenance. Load tests are used to validate the models. KW - Bauwerksüberwachung KW - Strukturmonitoring KW - Structural Health Monitoring KW - Modell-Update KW - UAS KW - Belastungstest KW - Structural system identification KW - Structural health monitoring KW - Model update KW - UAS KW - Load tests PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-554924 DO - https://doi.org/10.1002/bate.202100102 SN - 0932-8351 VL - 99 IS - 3 SP - 163 EP - 172 PB - Ernst & Sohn CY - Berlin AN - OPUS4-55492 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR 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, The Netherlands DA - 02.07.2023 KW - Verkehrsinfrastukturen KW - SHM KW - Model updating KW - System identification KW - Operational modal analysis PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-605041 DO - https://doi.org/10.1088/1742-6596/2647/18/182039 SN - 1742-6596 VL - 2647 IS - 18 SP - 1 EP - 9 PB - IOP Publishing CY - Bristol AN - OPUS4-60504 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Simon, Patrick A1 - Schneider, Ronald A1 - Baeßler, Matthias A1 - Morgenthal, Guido ED - Cha, Young-Jin T1 - A Bayesian Probabilistic Framework for Building Models for Structural Health Monitoring of Structures Subject to Environmental Variability N2 - Managing aging engineering structures requires damage identification, capacity reassessment, and prediction of remaining service life. Data from structural health monitoring (SHM) systems can be utilized to detect and characterize potential damage. However, environmental and operational variations impair the identification of damages from SHM data. Motivated by this, we introduce a Bayesian probabilistic framework for building models and identifying damage in monitored structures subject to environmental variability. The novelty of our work lies (a) in explicitly considering the effect of environmental influences and potential structural damages in the modeling to enable more accurate damage identification and (b) in proposing a methodological workflow for model‐based structural health monitoring that leverages model class selection for model building and damage identification. The framework is applied to a progressively damaged reinforced concrete beam subject to temperature variations in a climate chamber. Based on deflections and inclinations measured during diagnostic load tests of the undamaged structure, the most appropriate modeling approach for describing the temperature‐dependent behavior of the undamaged beam is identified. In the damaged state, damage is characterized based on the identified model parameters. The location and extent of the identified damage are consistent with the cracks observed in the laboratory. A numerical study with synthetic data is used to validate the parameter identification. The known true parameters lie within the 90% highest density intervals of the posterior distributions of the model parameters, suggesting that this approach is reliable for parameter identification. Our results indicate that the proposed framework can answer the question of damage identification under environmental variations. These findings show a way forward in integrating SHM data into the management of infrastructures. KW - Verkehrsinfrastukturen KW - SHM KW - Model Updating KW - Environmental and Operational Variability KW - Damage Identification KW - Model Building PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-605027 DO - https://doi.org/10.1155/2024/4204316 SN - 1545-2255 VL - 2024 IS - 1 SP - 1 EP - 23 PB - Wiley AN - OPUS4-60502 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Baeßler, Matthias A1 - Simon, Patrick T1 - Ballasted track on vibrating bridge decks: physical mechanisms, empirical findings, and a proposal for assessment N2 - This paper summarizes the key findings and physical mechanisms and provides information on open questions and the assessment of railway bridge superstructure vibrations. Bridges are classic disruption points on a railway track. If bridge superstructures are dynamically excited by train traffic, the vertical accelerations of the track must be considered. For a ballasted track, this can lead to the destabilization of the ballast track, as the bridge superstructure acts like a vibrating table. In this respect, the paper explains in more detail what is meant by destabilization, when this destabilization occurs and how various influencing parameters such as acceleration amplitude, the vibration sequence and frequency affect its occurrence. In the InBridge4EU project, gaps in knowledge such as the effect of single impulse loads are being investigated experimentally. A new test facility has been set up for this purpose, the initial results of which are presented here. An essential element in the assessment of this scenario is the stability of the track under high compression forces with simultaneous dynamic excitation of the superstructure. A new approach for the assessment of bridge vibrations with respect to lateral stability is presented. KW - Railway bridge dynamics KW - Bridge deck acceleration KW - Ballast destabilization KW - Lateral track stability KW - Track buckling PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-630972 DO - https://doi.org/10.1142/S0219455425400243 SN - 0219-4554 SN - 1793-6764 IS - 2540024 SP - 1 EP - 27 PB - World Scientific CY - Singapore AN - OPUS4-63097 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick A1 - Baeßler, Matthias ED - Rogge, Andreas ED - Meng, Birgit T1 - Temperatureinfluss auf Strukturmonitoring – Aktuelle Versuche N2 - Strukturmonitoring kann wertvolle Daten für die Zustandsbewertung und Schadensdetektion von Infrastrukturbauwerken liefern. Umgebungsbedingungen wie die Temperatur beeinflussen die Bauwerke und somit die Messdaten jedoch erheblich. Um Methoden für den Umgang mit Temperatureinflüssen zu entwickeln, wurden an der BAM Versuche an Stahlbeton- und Asphaltbalken unter kontrollierten Temperaturen von -40 °C bis 60 °C und definierten Schädigungen durchgeführt. Die Daten ermöglichen die Erforschung und Validierung neuer, auch unter Temperatureinfluss zuverlässiger Methoden des Strukturmonitorings. T2 - 11. Jahrestagung des DAfStb mit 63. Forschungskolloquium der BAM Green Intelligent Building CY - Berlin, Germany DA - 16.10.2024 KW - Strukturmonitoring KW - Temperatureinfluss KW - Infrastrukturbauwerke KW - Stahlbeton- und Asphaltbalken PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-613289 SN - 978-3-9818564-7-7 SP - 294 EP - 302 PB - Bundesanstalt für Materialforschung und -prüfung (BAM) CY - Berlin AN - OPUS4-61328 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick T1 - Experimente in der Klimakammer N2 - Im Rahmen des Verbundtreffens des Vorhabens AISTEC werden akutelle Versuche aus der Großklimakammer des FB 7.2 präsentiert. T2 - 5. Verbundtreffen AISTEC CY - Online meeting DA - 24.06.2021 KW - Klimakammer KW - Stochastic Subspace Damage Detection KW - Model Update KW - Asphalt PY - 2021 AN - OPUS4-52869 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick T1 - Enhancing structural models with material tests and static response data - a case study considering a steel beam with asphalt layer subject to temperature variations N2 - Gradual or sudden changes in the state of structural systems caused, for example, by deterioration or accidental load events can influence their load-bearing capacity. Structural changes can be inferred from static and/or dynamic response data measured by structural health monitoring systems. However, they may be masked by variations in the structural response due to varying environmental conditions. Particularly, the interaction of nominally load-bearing components with nominally non-load bearing components exhibiting characteristics that vary as a function of the environmental conditions can significantly affect the monitored structural response. Ignoring these effects may hamper an inference of structural changes from the monitoring data. To address this issue, we adopt a probabilistic model-based framework as a basis for developing digital twins of structural systems that enable a prediction of the structural behavior under varying ambient condition. Within this framework, different types of data obtained from real the structural system can be applied to update the digital twin of the structural system using Bayesian methods and thus enhance predictions of the structural behavior. In this contribution, we implement the framework to develop a digital twin of a simply supported steel beam with an asphalt layer. It is formulated such that it can predict the static response of the beam in function of its temperature. In a climate chamber, the beam was subject to varying temperatures and its static response wass monitored. In addition, tests are performed to determine the temperature-dependent properties of the asphalt material. Bayesian system identification is applied to enhance the predictive capabilities of the digital twin based on the observed data. T2 - International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-10) CY - Online meeting DA - 30.06.2021 KW - Digital twin KW - Structural health monitoring KW - Material tests KW - Bayesian updating PY - 2021 AN - OPUS4-54130 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick T1 - Zustandsbewertung von Bauwerken unter veränderlichen Umgebungsbedingungen mittels Structural Health Monitoring N2 - Brücken sind Teil der alternden Verkehrsinfrastruktur. Um die Nutzungsdauer zu verlängern und plötzliche Schäden zu detektieren kann Bauwerksmonitoring ("Structural Health Monitoring") eingesetzt werden. Der Einfluss von Umgebungsbedingungen, beispielsweise der Temperatur, auf das Bauwerksverhalten ist meist größer als der Einfluss von Schäden. Diese Einflüsse bestmöglich voneinander zu trennen und Veränderungen im Tragverhalten korrekt Schäden oder Umgebungsbedingungen zuzuordnen ist eine offene Forschungsfrage. Diese Arbeit zeigt eine mögliche Lösung, bei der gekoppelte Modelle von Umwelteinflüssen, Schäden und Tragverhalten des Bauwerks auf Grundlage von Monitoringdaten aktualisiert werden. Das Framework dazu wird vorgestellt und an einem Laborexperiment eines Stahlbetonbalkens in der Klimakammer angewandt. Die Ergebnisse bestätigen die Vorgehensweise. In nächsten Schritten müssen komplexere Tragwerke und die Sensitivität des Ansatzes untersucht werden. T2 - Forschungskolloquium, Institut für Konstruktiven Ingenieurbau, Bauhaus-Universität Weimar CY - Weimar, Germany DA - 28.06.2023 KW - Structural health monitoring KW - Bauwerksmonitoring KW - Umwelteinflüsse KW - Brücken PY - 2023 AN - OPUS4-58005 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick T1 - Bayesian system identification of a reinforced concrete beam subject to temperature variations based on static response data N2 - 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. T2 - Tenth International Conference on Bridge Maintenance, Safety and Management (IABMAS 2020) CY - Online meeting DA - 11.04.2021 KW - Bayesian system identification KW - Reinforced concrete KW - Damage identification KW - Environmental effects KW - Structural health monitoring KW - Structural systems PY - 2021 AN - OPUS4-52812 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Eichner, Lukas A1 - Schneider, Ronald A1 - Simon, Patrick A1 - Baeßler, Matthias T1 - Optimal sensor placement for vibration-based structural health monitoring obtained via value of information analysis as part of a digital structural integrity management of offshore structures N2 - A digital structural integrity management of offshore structures enables an optimized planning of inspections and repairs with risk-based methods. In a risk-based approach, the inspection and repair strategy that minimizes the expected lifetime costs consisting of the expected inspection, repair and failure costs is determined. In addition to inspections, information on the structural condition can be continuously obtained by monitoring the vibration response of the structural system. Changes in the vibration characteristics quantified in terms of modal properties can be an indication of structural damage. In risk-based inspection and repair planning, the effect of monitoring results is determined via Bayesian updating of the structural condition and reliability. This information should be applied to inform decisions on inspections and may result in a reduced inspection effort. The benefit of continuously monitoring the structural health can be quantified in terms of the value of information, which corresponds to the difference between the expected lifetime costs with and without monitoring. In this work, we demonstrate in a numerical example how an optimized sensor placement for a vibration-based structural health monitoring system can be determined by maximizing the value of information. T2 - 3rd International Conference on Health Monitoring of Civil & Maritime Structures (HeaMES 2022) CY - Online meeting DA - 08.06.2022 KW - Structural Health Monitoring KW - Value of Information KW - Offshore Wind Energy KW - Optimal Sensor Placement KW - Bayesian System Identification PY - 2022 UR - https://www.researchgate.net/publication/362569906_Optimal_sensor_placement_for_vibration-based_structural_health_monitoring_obtained_via_value_of_information_analysis_as_part_of_a_digital_structural_integrity_management_of_offshore_structures SN - 978-1-8383226-7-0 SP - 23 EP - 32 AN - OPUS4-55465 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -