TY - CONF A1 - Schneider, Ronald 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 - Schneider, Ronald 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 - THES A1 - Schneider, Ronald T1 - Time-variant reliability of deteriorating structural systems conditional on inspection and monitoring data 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 - 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 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 A1 - Herrmann, Ralf 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 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 - 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 - 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 - 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 - Schubert, T. A1 - Bracklow, F. A1 - Unger, N. A1 - Hering, Marcus A1 - Beckmann, B. T1 - Impact Tests on Reinforced Concrete Slabs – Variation in Results and Residual Load Bearing Capacity due to Hard Impact N2 - Structures such as concrete slabs and concrete barriers of critical infrastructure facilities must be able to withstand impact events or severe accidents. In particular, the structural safety of the confinements of nuclear power plants against a possible aircraft impact is essential to ensure the safety of inhabitants and environment. This article presents research results of hard impact on reinforced concrete slabs, which have been carried out at the Institute of Concrete Structures (IMB) at TUD Dresden University of Technology Technische Universität (TU Dresden). A specially designed drop tower is available for this purpose on the premises of the Otto Mohr Laboratory of TU Dresden. In the framework of a research project many reinforced concrete slabs of dimension 1.5 x 1.5 x 0.2 m³ were tested by hard impact. The investigation on some already carried out impact tests on reinforced concrete slabs intend to show the range of deviation of impact tests. In particular, the possible standard deviations that should be regarded in impact tests are estimated for the applied test setup. Furthermore, the residual structural capacity of an undamaged and damaged reinforced concrete slab has been investigated. T2 - Conference: 27th International Conference on Structural Mechanics in Reactor Technology (SMiRT) CY - Yokohama, Japan DA - 04.03.2024 KW - Reinforced Concrete KW - Drop Tower KW - Hard Impact PY - 2024 SP - 1 EP - 10 PB - IASMiRT CY - Yokohama, Japan AN - OPUS4-61915 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schubert, Thomas A1 - Máca, Petr A1 - Hering, Marcus A1 - Fiedler, Georg A1 - Beckmann, Birgit T1 - Impact Experiments on Reinforced Concrete Specimens - Investigation of Repeatability and Scaling N2 - Nowadays, the impact resistance of concrete structures has become a prominent concern for critical infrastructure operators, particularly amidst escalating geopolitical tensions. Regulators and design engineers know that reinforced concrete structures can only be developed with high efficiency by considering nonlinear structural and highly nonlinear material behavior. Therefore, specific guidelines on impact design provide instructions for design and analysis of structures required to resist impact loading. These instructions are usually based on published results and evaluated data of impact experiments carried out in laboratories. To widen the knowledge and increase the scientific data the Institute of Concrete Structures (IMB) at TUD Dresden University of Technology (TUD) has carried out many impact experiments on reinforced concrete specimens in recent years. A specially designed drop tower is available for this purpose on the premises of the Otto Mohr Laboratory, TUD. In the framework of the past research at TUD some important issues, such as influence of rebar arrangement, structural thickness, scalability of specimen and repeatability, with regard to experimental impact testing were investigated. This article presents the drop tower facility and research results of impact experiments on reinforced concrete slabs. First, the scalability of impact experiments will be discussed in conjunction with already known theoretical scaling parameters provided by researchers in the past, e.g. Rüdiger et al. [1]. Scalability of experimental data is of huge importance since protective structures made of reinforced concrete differ usually in size in comparison to experimental specimens. The second important research focus is on repeatably of impact experiments. Since impact experiments are usually time consuming and expensive, a certain impact scenario is mostly carried out only once. It is intended to show the range of deviation of impact tests on some already carried out experiments on reinforced concrete slabs. A possible standard deviation is estimated for the applied test setup. T2 - 15th International Conference on Shock & Impact Loads on Structures CY - Gothenburg, Sweden DA - 12.06.2025 KW - Reinforced concrete KW - Drop-weight impact KW - Scaling KW - Repeatability KW - Digital image correlation PY - 2025 SP - 80 EP - 91 AN - OPUS4-63627 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Signorini, C. A1 - Bracklow, F. A1 - Hering, Marcus A1 - Butler, M. A1 - Leicht, L. A1 - Schubert, T. A1 - Beigh, M. A. B. A1 - Beckmann, B. A1 - Curbach, M. A1 - Mechtcherine, V. T1 - Ballistic limit and damage assessment of hybrid fibre-reinforced cementitious thin composite plates under impact loading N2 - Impact resistance of reinforced concrete (RC) structures can be significantly improved by strengthening RC members with thin composite layers featuring high damage tolerance. Indeed, to limit the well-known vulnerability of cement-based materials against impact loading, the synergistic effects of short fibres and continuous textile meshes as hybrid reinforcement has been proved to be highly beneficial. This paper addresses the characterisation of novel cement-based hybrid composites through accelerated drop-weight impact tests conducted on rectangular plates at different impact energies. Two distinct matrices are assessed, with particular interest in a newly developed limestone calcined clay cement (LC3)-based formulation. Important parameters quantifying energy dissipation capability, load bearing capacity and damage are cross-checked to compute the ballistic limit and estimate the safety-relevant characteristics of the different composites at hand. Although textiles alone can improve the damage tolerance of fine concrete to some extent, the crack-bridging attitude of short, well-dispersed fibres in hybrid composites imparts a certain ductility to the cement-based matrices, allowing a greater portion of the textile to be activated and significantly reducing the amount of matrix spalling under impact. KW - Impact loading KW - Cement-based composites KW - SHCC KW - TRC KW - Sustainable binders PY - 2023 DO - https://doi.org/10.1016/j.jobe.2023.108037 VL - 80 SP - 1 EP - 21 PB - Elsevier Ltd. AN - OPUS4-58793 LA - eng 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 - Simon, Patrick T1 - Research Data Management of Structural Health Monitoring Projects and Subsequent Applications of Artificial Intelligence Methods 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 AN - OPUS4-55494 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick T1 - Sensorbasierte Systemidentifikation N2 - Die aktuelle Instandhaltungsstrategien von Ingenieurbauwerken arbeiten zustandsbasiert und stützen sich auf visuelle Inspektionen in kurzen, starren Intervallen. Beim Übergang zu Predicitive-Maintenance-Strategien können Sensordaten eigesetzt werden um Prognosemodelle der Bauwerke zu aktualisieren. Ein erster Schritt hierzu ist die sensorbasierte Systemidentifikation. T2 - Abschlussveranstaltung AISTEC CY - Berlin, Germany DA - 02.05.2022 KW - Systemidentifikation KW - Strukturmonitoring PY - 2022 AN - OPUS4-55495 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick T1 - Temperatureinfluss auf Strukturmonitoring – aktuelle Versuche N2 - Strukturmonitoring kann wertvolle Daten für die Zustandsbewertung und Schadensdetektion von Infrastruk-turbauwerken 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 - Structural Health Monitoring KW - Strukturmonitoring KW - Temperatureinfluss KW - Klimakammer KW - Bayesian Updating PY - 2024 AN - OPUS4-61573 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick T1 - Vibration-based Structural Health Monitoring of a Reinforced Concrete Beam Subjected to Varying Ambient Conditions Using Bayesian Methods 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 - Bayesian methods KW - Environmental effects KW - Structural health monitoring PY - 2020 AN - OPUS4-51732 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -