TY - CONF A1 - Zinas, Orestis A1 - Papaioannou, Iason A1 - Schneider, Ronald A1 - Cuéllar, Pablo A1 - Baeßler, Matthias T1 - 3D spatial modelling of CPT data for probabilistic preliminary assessment of potential pile tip damage upon collision with boulders N2 - Tip damage of monopiles from boulder collisions during installation has emerged as a critical design issue, primarily due to the combination of the widespread use of large-diameter piles and the complexity of the ground conditions at the available sites. Recently, a framework relating potential pile tip damage to cone tip resistance from Cone Penetration Tests (CPTs) has been proposed in the literature. Gaussian processes are powerful stochastic models that enable probabilistic spatial interpolation of soil data at any location within a site. On this basis, this study utilizes sparse CPT data from a site in the North Sea, to first develop an efficient Gaussian process regression model, which is used to derive a three-dimensional (3D) probabilistic predictive map of the cone tip resistance. Assuming deterministic loading conditions and a factual collision with a boulder of pre-defined properties, the cone tip resistance predictive model is subsequently used for a probabilistic preliminary assessment of potential pile tip damage. Results of the analysis are realistic 3D probability maps of potential damage that aim to support engineering judgment and contribute towards cost-effective site investigation planning and offshore wind farm design. T2 - 5th International Symposium on Frontiers in Offshore Geotechnics (ISFOG 2025) CY - Nantes, France DA - 09.06.2025 KW - CPT data KW - Gaussian process regression KW - Boulder impact KW - Preliminary pile tip damage assessment PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-634417 SN - 978-2-85782-758-0 DO - https://doi.org/10.53243/ISFOG2025-323 SP - 505 EP - 510 PB - International Society for Soil Mechanics and Geotechnical Engineering CY - London AN - OPUS4-63441 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 - CONF A1 - Gerards-Wünsche, Paul A1 - Ratkovac, Mirjana A1 - Schneider, Ronald A1 - Hille, Falk A1 - Baeßler, Matthias T1 - A framework for assessing the reliability of crack luminescence – an automated fatigue crack detection system N2 - The new crack luminescence method offers the possibility of making fatigue surface cracks in metallic materials more visible during inspections through a special coating system. This coating system consists of two layers, whereby the first layer has fluorescent properties and emits visible light as soon as it is irradiated by UV light. The top layer is black and is designed to prevent the fluorescent layer from emitting if no crack develops in the underlying material. The technique proved particularly useful in a wide variety of fatigue tests of steel components under laboratory conditions. Moreover, it has the potential to be used in various industrial applications. To enable industrial deployment and integration into maintenance strategies, a concept study is developed in this contribution, resulting in a qualification framework that can serve as a foundation for determining the reliability of the crack luminescence system in terms of a probability of detection curve. Within this study, factors causing measurement variability and uncertainty are being determined and their influences assessed. Due to the extension of the system by a moving computer vision system for automated crack detection using artificial intelligence, additional long-term effects associated with structural health monitoring systems need to be incorporated into an extended probability of detection study as part of the technical justification. Finally, important aspects and findings related to design of experiments are discussed, and a framework for reliability assessment of a new optical crack monitoring method is presented, emphasizing the influence of various uncertainty parameters, including long-term effects such as system ageing. T2 - SPIE Conference Smart Structures + Nondestructive Evaluation 2023 CY - Long Beach, CA, USA DA - 24.03.2023 KW - Structural Health Monitoring KW - Non-Destructive Evaluation KW - Probability of Detection KW - Reliability KW - Artificial Intelligence KW - Computer Vision KW - Crack Luminescence KW - Wind PY - 2023 SN - 978-1-5106-6086-1 DO - https://doi.org/10.1117/12.2658390 SP - 1 EP - 15 AN - OPUS4-57244 LA - eng 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 N2 - Support structures of wind turbines in German offshore wind farms are regularly inspected. Currently, inspection outcomes are generally not systematically recorded. This prevents their consistent handling and processing, which is a key requirement to enable an efficient structural integrity management. As part of the DiMoWind-Inspect project, a data model and reference designation system for such inspection results is developed to facilitate their identification, localization, quantification, tracing and linking throughout the lifetime of a wind farm and beyond. The inspection results together with structural health monitoring results and information on repairs form the basis for assessing and predicting the structural condition, estimating the remaining lifetime, and planning of future inspections, structural health monitoring, and repairs. As a basis for developing a digital structural integrity management, a generic framework is proposed in this paper, which describes the stakeholders, data, models, processes and workflows of the integrity management of support structures in offshore wind farms and their interrelations. The framework adopts a building information modelling approach to describe the information relevant to the structural integrity management. The central digital space of the framework is a common data environment. An implementation of the framework will enable a digital structural integrity management in which inspection, structural health monitoring, repair, assessment and planning outcomes generated throughout the life cycle of a wind farm can be consistently collected, managed, shared and processed by the relevant shareholders. T2 - 8th International Symposium on Reliability Engineering and Risk Management CY - Hannover, Germany DA - 04.09.2022 KW - Offshore wind energy KW - support structures KW - structural health monitoring KW - building information modelling KW - structural integrity management PY - 2022 DO - https://doi.org/10.3850/978-981-18-5184-1_MS-04-161-cd SP - 111 EP - 117 PB - Research Publishing CY - Singapore AN - OPUS4-55656 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald T1 - A risk-based framework for optimizing inspection and maintenance of deteriorating structures monitored by vibration-based monitoring systems N2 - In this presentation, a framework for integrating vibration-based structural health monitoring data into the optimization of inspection and maintenance of deteriorating structural systems is presented. The framework is demonstrated in an illustrative example considering a steel frame subject to fatigue. T2 - EERA JP Wind WORKSHOP on Ongoing research in offshore wind structures CY - Online meeting DA - 16.09.2021 KW - Structural Health Monitoring KW - Inspection KW - Maintenance KW - Deterioration KW - Vibration KW - Structural Systems PY - 2021 AN - OPUS4-53749 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick A1 - Schneider, Ronald A1 - Baeßler, Matthias ED - Yokota, H. ED - Frangopol, D. M. 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 - Structural systems KW - Bayesian system identification KW - Damage identification KW - Environmental effects KW - Structural health monitoring PY - 2021 DO - https://doi.org/10.1201/9780429279119-125 SP - 934 EP - 941 PB - CRC Press AN - OPUS4-52809 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald T1 - Belastungsversuch und Methodenvalidierung an der Maintalbrücke Gemünden N2 - Im Projekt AISTEC wurden Methoden entwickelt, die der prädiktiven Instandhaltung von Ingenieurbauwerken dienen. Zur Validierung dieser Methoden wurden an einem Referenzbauwerk - der Maintalbrücke Gemünden - Belastungstests durchgeführt. T2 - Abschlussveranstaltung AISTEC CY - Berlin, Germany DA - 02.05.2022 KW - Belastungsfahrt KW - GNSS KW - Einflusslinien PY - 2022 AN - OPUS4-55496 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - 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 - CONF A1 - Schneider, Ronald A1 - Schwiersch, Niklas T1 - Betrieb und Planung - Ausgewählte Vorteile von Risikoanalysen im Ingenieur- und Wasserbau N2 - Am 19. und 20.11.2024 veranstaltete die BAM und der DGGT AK 2.15 „Zuverlässigkeitsbasierte Methoden in der Geotechnik“ in Zusammenarbeit mit der DGGT-Akademie einen zweitägigen Workshop zur Einführung in die zuverlässigkeitsbasierte Bemessung. Im Rahmen der Vortragsveranstaltung am zweiten Tag wurden zum einen die unterschiedlichen Sicherheits- und Bemessungsphilosophien nach dem bewährten Teilsicherheitskonzept sowie nach dem zuverlässigkeitsbasierten Konzept vorgestellt. Zum anderen werden verschiedene Anwendungen zuverlässigkeitsbasierter Verfahren aus der Ingenieurpraxis und Wissenschaft präsentiert. In diesem Vortrag wurden aus Sicht des Ingenieur- und Wasserbaus Vorteile von Risikoanalysen u. a. für die Planung von Inspektionszyklen, die Ursachenforschung im Versagensfall und die Konzeption von Hochwasserrisikomanagement-Maßnahmen präsentiert. T2 - 2. Workshop des DGGT AK 2.15 „Zuverlässigkeitsbasierte Methoden in der Geotechnik“ CY - Berlin, Germany DA - 19.11.2024 KW - Risikoanalyse KW - Offshore-Strukturen KW - Hochwasserschutz PY - 2024 AN - OPUS4-61906 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - Straub, D. ED - Matos, J.C. ED - Lourenço, P.B. ED - Oliveira, D.V. ED - Branco, J. ED - Proske, D. ED - Silva, R.A. ED - Sousa, H.S. T1 - Cumulative Failure Probability of Deteriorating Structures: Can It Drop? 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 - 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 - Hille, Falk A1 - Herrmann, Ralf A1 - Schneider, Ronald A1 - Pitters, S. A1 - Wedel, F. A1 - Hindersmann, I. T1 - Developing a guideline for structural health monitoring of road bridges in Germany N2 - In recent years, Structural Health Monitoring (SHM) has become a useful and increasingly widely used tool for supporting lifetime extensions of existing bridges with known structural deficiencies or indications of potentially critical damages or damage processes. At the same time, methods and tools are emerging, which enable monitoring-informed predictive maintenance of new and existing bridges based on digital twins. The monitoring process – starting from the definition of monitoring actions and ending with decisions based on monitoring outcomes – is complex and requires expertise in structural engineering, operation and maintenance of bridges, metrology, and data analytics. To support German road authorities, engineering consultancies, building contractors and other stakeholders of the bridge management, the Federal Highway Research Institute (BASt) has initiated the development of a new guideline for applying SHM as part of the management of road bridges. The guideline will present various use cases and for each identified use case, it will propose a proven monitoring scheme. In addition, the guideline will provide guidance on assessing the benefits of SHM as well as a common approach to managing monitoring data as a systematic basis for integrating monitoring data in the bridge management. This contribution discusses the motivation, objectives, and scope of the guideline, describes its use case centric structure and outlines the proposed data management. T2 - IABMAS 2024 CY - Kopenhagen, Danmark DA - 24.06.2024 KW - Guideline KW - Structural health monitoring KW - Road bridges KW - Infrastructure PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-613947 SN - 978-1-032-77040-6 DO - https://doi.org/10.1201/9781003483755-236 SP - 2009 EP - 2017 PB - CRC Press AN - OPUS4-61394 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald T1 - Digitaler Zwilling im Erhaltungsmanagement von Straßenbrücken N2 - Digitale Zwillinge werden zukünftig ein integraler Bestandteil des Erhaltungsmanagements von Straßenbrücken 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 T2 - Workshop „Digitaler Zwilling im Lebenszyklusmanagement" der AG BIM in der Bauwerkserhaltung des Koordinierungsausschusses Erhaltung (KoA-Erhaltung) der B/L-DB Konstruktiver Ingenieurbau CY - Potsdam, Germany DA - 09.04.2025 KW - Digitale Zwillinge KW - Erhaltung KW - Inspektion KW - Monitoring KW - Brücken PY - 2025 AN - OPUS4-62951 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Eichner, Lukas A1 - Gerards-Wünsche, Paul A1 - Happel, Karina A1 - Weise, Sigurd A1 - Haake, Gerrit A1 - Sieber, Lars A1 - Flederer, Holger A1 - Schneider, Ronald A1 - Herrmann, Ralf A1 - Hille, Falk A1 - Baeßler, Matthias A1 - Huhn, Holger A1 - Küchler, Andreas T1 - Digitales Datenmanagement für die Instandhaltung von Offshore-Windparks T1 - Digital data management for maintenance in offshore wind farms N2 - Im Forschungsprojekt DiMoWind-Inspect wurde untersucht, welche Grundvoraussetzungen geschaffen werden müssen, um digitale Methoden für die Instandhaltung von Offshore-Windenergieanlagen einsetzen zu können. Daten aus allen Lebensphasen der Anlagen werden derzeit nur selten effizient dafür genutzt, um die sinnvollsten Instandhaltungsmaßnahmen am richtigen Ort, zum richtigen Zeitpunkt und mit den geringsten Kosten durchzuführen. Eine im Vorhaben entwickelte einheitliche Strukturierung der bisher häufig unstrukturierten Bau- und Instandhaltungsdaten ermöglicht ihre übergreifende, anwenderspezifische Verfügbarkeit. Hierfür werden Prinzipien des Referenzkennzeichnungssystems RDS-PP adaptiert. Es wird aufgezeigt, wie neben Bauteilen auch zusätzliche Informationen wie Instandhaltungsmaßnahmen oder Mängel strukturiert werden können. Dem Ansatz des Building Information Modeling folgend werden die Bauwerkskomponenten direkt mit den Informationen aus Inspektionen und weiteren Instandhaltungsmaßnahmen verknüpft. So können Informationen aus dem Betrieb über den Zustand der Struktur verarbeitet und für die maßgebenden Berechnungen und Nachweise zur Verfügung gestellt werden. Als Anwendungsfall wird ein zweistufiges Konzept vorgestellt, das zur Bewertung der Ermüdungslebensdauer eines korrosionsgeschädigten Konstruktionsdetails der Gründungsstruktur einer Offshore-Windenergieanlage mit Informationen aus der Instandhaltung eingesetzt wird. N2 - The DiMoWind-Inspect research project explored the essential requirements for implementing digital methods in the maintenance of offshore wind turbines. Currently, data from all stages of the turbines' lifecycles are underutilized, leading to suboptimal maintenance actions being taken in terms of location, timing, and cost. A consistent structuring of previously often unstructured construction and maintenance data developed in the project enables their cross-disciplinary, user-specific availability. To accomplish this, the principles of the Reference Designation System for Power Plants RDS-PP are applied. In this way, additional information, such as maintenance measures or defects, can be structured alongside components. The components of the structures are directly linked with information from inspections and other maintenance activities, following the Building Information Modeling approach. This allows for processing operational information about the condition of the structure and providing it for relevant calculations and assessments. As a use case, a two-stage concept is presented, utilizing maintenance information to assess the fatigue life of a corrosion-damaged structural detail in the support structure of an offshore wind turbine. KW - Building Information Modeling KW - Datenmanagement KW - Instandhaltung KW - Offshore-Windenergie KW - Referenzkennzeichnungssystem PY - 2024 DO - https://doi.org/10.1002/bate.202400026 VL - 101 IS - 10 SP - 558 EP - 567 PB - Ernst & Sohn CY - Berlin AN - OPUS4-60765 LA - deu 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 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 - Herrmann, Ralf A1 - Hille, Falk A1 - Pitters, S. A1 - Ramasetti, Eshwar Kumar A1 - Schneider, Ronald A1 - Wedel, F. A1 - Hindersmann, I. ED - Rogge, Andreas ED - Meng, Birgit T1 - Föderiertes Datenmanagement von Monitoringdaten aus Structural Health Monitoring Anwendungen und daraus gewonnenen Trainingsdaten bei Spannbetonbrücken N2 - Beim Structural Health Monitoring entstehen eine Vielzahl von Daten, Metadaten und Modellen mit hohem Wert für die Beurteilung des Bauwerkszustands und der Prognose von Veränderungen. Kontinuierlich anwachsende Datenbestände müssen nachhaltig geteilt, genutzt und über die Bauwerkslebensdauer archiviert werden. Dabei stellen die Vielfalt der Messaufgaben, die Heterogenität der Daten, die dezentrale Erfassung und z. T. der Umfang eine Herausforderung für die beteiligten Akteure dar. Für den Datentransfer der Monitoringdaten zwischen der Straßenbauverwaltung und den Monitoringausführenden wird ein flexibles Abstimmungsverfahren vorgeschlagen und ein Lösungskonzept für ein föderiertes Datenmanagement skizziert. Eine weitere Herausforderung stellt die bauwerksübergreifende Zusammenstellung von Trainingsdaten für konkrete KI-Anwendungen dar. T2 - 11. Jahrestagung des DAfStb mit 63. Forschungskolloquium der BAM Green Intelligent Building CY - Berlin, Germany DA - 16.10.2024 KW - Structural Health Monitoring PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-612902 SN - 978-3-9818564-7-7 SP - 178 EP - 185 PB - Bundesanstalt für Materialforschung und -prüfung (BAM) CY - Berlin AN - OPUS4-61290 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Wedel, F. A1 - Pitters, S. A1 - Herrmann, Ralf A1 - Schneider, Ronald A1 - Hille, Falk A1 - Hindersmann, I. T1 - Guideline for the strategic application of monitoring of road bridges in Germany N2 - Engineering structures are an important part of our transport infrastructure. Their failure is associated with high safety risks and economic damage. Ensuring the availability of these constructions and guaranteeing their operational safety are thus important tasks. Currently, maintenance of engineering structures is a reactive process and therefore not yet a predictive process. Every 3 to 6 years, the structures are visually inspected, all damages are documented and a condition grade is assigned to the structure based on the detected damages. Continuous data-providing methods such as monitoring are used only very occasionally. With the help of monitoring, condition data about the structures are continuously collected, which can be used for a better assessment of the structures. On the one hand, this would increase safety of engineering structures, and on the other hand, it makes the shift towards predictive maintenance management based on real-time data and predictions, where the onset of damage is detected before it occurs, possible in the first place. Monitoring plays therefore an important role in the management of the infrastructure. It is a crucial a step towards the digitalisation of our infrastructure and existing processes. Although there are many use cases for monitoring that have already been successfully implemented, monitoring is not yet widely used by German road authorities due to several challenges that were also identified within the scope of the project. Therefore, a guide has been developed in which the current obstacles related to monitoring are identified and possibilities for integrating monitoring into existing processes are offered. To ensure optimal alignment with the needs of road authorities, both an online survey and a workshop have been conducted. The results are summarised in a brochure that is made available to authorities to improve the use of monitoring in Germany. This paper presents the guideline and the brochure. T2 - 10th European Workshop on Structural Health Monitoring (EWSHM 2024) CY - Potsdam, Germany DA - 10.06.2024 KW - Verkehrsinfrastrukturen KW - Engineering Structures KW - Bridges KW - Structural Health Monitoring KW - Guideline PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-612821 UR - https://www.ndt.net/search/docs.php3?id=29582 DO - https://doi.org/10.58286/29582 SN - 1435-4934 VL - 29 IS - 7 SP - 1 EP - 8 PB - NDT.net GmbH & Co. KG CY - Mayen AN - OPUS4-61282 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald T1 - Impulsvortrag: Ermüdungslebensdauerbewertung mittels Informationen aus Monitoring und Inspektionen N2 - Kontext: Ermüdungsbeanspruchte Tragstrukturen von Windenergieanlagen, Bestimmung der Ermüdungsbeanspruchungen und -zuverlässigkeit auf der Grundlage von Simulationen aus dem Design unter Berücksichtigung von Modellunsicherheiten, Aktualisierung der Ermüdungsbeanspruchungen und -zuverlässigkeit auf der Grundlage von globalen Monitoring- und lokalen Inspektionsinformationen aus dem Betrieb unter Berücksichtigung von Modell- und Messunsicherheiten T2 - 3. Verbundtreffen ReNEW CY - Berlin, Germany DA - 05.09.2024 KW - Modellunsicherheiten KW - Windenergie KW - Ermüdungslebensdauer KW - Tragstrukturen KW - Monitoring KW - Inspektionen PY - 2024 AN - OPUS4-61427 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald 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 - Schneider, Ronald T1 - Kontinuierliche sensordaten- und modellgestützte Bewertung von Infrastrukturbauwerken in der Praxis N2 - Ein Einsatz von kontinuierlichen sensorbasierten Verfahren komplementär zu den zeitlich diskreten bildbasierten Verfahren haben ein enormes Potenzial, die bisher hauptsächlich visuellen Prüfprozesse zu transformieren. Zur Ermöglichung eines strategischen Einsatzes des sensorbasierten Monitorings im Erhaltungsmanagement von Ingenieurbauwerken ist das übergeordnete Ziel des Projektes AISTEC-Pro die Demonstration des praktischen Mehrwerts des sensorbasierten Monitorings. Dies wird durch praktische Anwendungen an der Maintalbrücke Gemünden und einem neu ausgewählten Referenzbauwerk unter Berücksichtigung von typischen Einsatzszenarien im Bereich der Bauwerkserhaltung erreicht werden. Die Einsatzszenarien werden in enger Abstimmung mit den Endanwendern entwickelt und fortgeschrieben. Hierbei wird insbesondere Bezug auf die aktuelle Neufassung der DIN 1076 genommen, in der erstmals die Anwendung von sensor- und bildbasierten Monitoringverfahren in der Bauwerksprüfung geregelt wird. T2 - AISTEC-Pro Auftakttreffen CY - Weimar, Germany DA - 02.12.2024 KW - Sensorbasiertes Monitoring KW - Erhaltung KW - Verkehrsbrücken PY - 2024 AN - OPUS4-61919 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -