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 - 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 - 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 - JOUR A1 - Thibaux, Philippe A1 - Thiele, Marc A1 - Van Wittenberghe, Jeroen A1 - Baeßler, Matthias T1 - Comparison of resonance and hydraulic testing on large scale fatigue tests of welded tubular joints for offshore wind turbine foundations N2 - Jackets structures as foundations for offshore wind energy converters are efficient solutions. But these structures require the welding of a large number of joints. The design of the Jacket structures is typically driven by fatigue. Therefore, consequently the fatigue strength of the joints is a primary parameter for an optimized design. The present paper investigates if tubular joints produced by manual welding using the current techniques have an improved performance compared to the relevant standards that are applied for the design of the foundations. To investigate this, 4 full-scale tests in geometry representative of a structure were performed, 2 using a resonance method and 2 using a three-point bending method with hydraulic actuators. The results are similar, with cracks initiated early and extending extensively before failure. The results are very close to the current T-curve from DNV RP-C203 applied for tubular joints. KW - Fatigue KW - Tubular joints KW - Resonance testing KW - Steel welds PY - 2025 DO - https://doi.org/10.1016/j.ijfatigue.2024.108797 SN - 0142-1123 VL - 193 SP - 1 EP - 16 PB - Elsevier Ltd. AN - OPUS4-62373 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Balscheit, Hagen A1 - Geißler, Peter A1 - Cuéllar, Pablo A1 - Basedau, Frank A1 - Baeßler, Matthias T1 - Large-scale field tests on plastic pile tip failure upon monopile installation N2 - Large-diameter monopiles are the most common foundation structures for offshore wind turbines. One relevant failure mode during installation is plastic failure of the pile tip which may increase progressively during further driving (pile tip buckling; extrusion buckling). This paper presents the details and results of a large-scale field-test campaign with dynamic pile installation for the validation and calibration of different numerical approaches concerning pile-tip buckling phenomena. The phenomenology of observed pile-tip failures is here described in detail and a first quantitative approach is evaluated based on the field-test data. As the number of new projects continues to grow and the necessity to construct wind farms in challenging terrain increases, such field data-sets will become increasingly relevant. KW - Monopile KW - Offshore Windenergy KW - Pfahlfußbeulen KW - Pile Tip Buckling KW - Reference Tests PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-611651 DO - https://doi.org/10.1016/j.oceaneng.2024.119322 VL - 313 SP - 1 EP - 14 PB - Elsevier B.V. AN - OPUS4-61165 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick A1 - Baeßler, Matthias ED - Cunha, Álvaro ED - Caetano, Elsa T1 - On the reassessment of bridge superstructure vibrations for high-speed traffic N2 - The acceleration thresholds of bridge superstructures remain critical for designing and reassessing railway bridges on high-speed lines, with ballasted track systems historically limited to 3.5 m/s2 vertical accelerations due to destabilization risks. As part of the European InBridge4EU project, this study addresses methodological uncertainties in linking vertical bridge vibrations to lateral track creep—a key focus area for modernizing assessment protocols. A comparative analysis of two acceleration postprocessing methods (peak identification vs. fatigue-derived rainflow counting) as part of a recently proposed framework was conducted using an example bridge and train combination. Results demonstrate that rainflow counting yields more conservative creep estimates with the bulk of cumulative vibration-induced creep attributable to accelerations exceeding 3 m/s2. However, discretizing acceleration ranges into 1 m/s2 bins introduced significant errors compared to continuous cycle data, highlighting sensitivity to analysis parameters. These findings underscore the complexity of reconciling laboratory-derived harmonic vibration models with real-world bridge dynamics, where non-uniform acceleration patterns dominate. The research directly informs ongoing efforts to refine standardized criteria for ballasted track stability, particularly through the InBridge4EU project’s systematic re-evaluation of vibration limits and their engineering implications. By quantifying discrepancies between computational approaches, this work advances the development of robust protocols for predicting track degradation under high-speed operational loads. T2 - 11th International Conference on Experimental Vibration Analysis for Civil Enginering Structures (EVACES 2025) CY - Porto, Portugal DA - 02.07.2025 KW - Infrastructure KW - Railway bridges KW - Ballast destabilization KW - Acceleration limit KW - Ballasted track KW - Rainflow counting PY - 2025 SN - 978-3-031-96105-2 DO - https://doi.org/10.1007/978-3-031-96106-9_53 VL - 675 SP - 506 EP - 515 PB - Springer CY - Cham AN - OPUS4-64267 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Eichner, Lukas A1 - Schneider, Ronald A1 - Baeßler, Matthias T1 - Optimal vibration sensor placement for jacket support structures of offshore wind turbines based on value of information analysis N2 - Information on the condition and reliability of an offshore jacket structure provided by a vibration-based structural health monitoring system can guide decisions on inspection and maintenance. When selecting the sensor setup, the designer of the monitoring system must assess its overall benefit compared to its costs before installation. The potential benefit of continuously monitoring the dynamic response of a jacket structure can be formally quantified through a value of information analysis from Bayesian decision theory. In this contribution, we present a framework for optimizing the placement of vibration sensors on offshore jacket structures by maximizing the value of information of the monitoring system. To solve the resulting discrete optimization problem, we adapt a genetic algorithm. The framework is demonstrated in a numerical example considering a redundant jacket-type steel frame. The numerical study shows that monitoring the vibration response of the frame is beneficial. Good sensor setups consist of relatively few sensors located towards the upper part of the frame. The adapted genetic algorithm performs similarly well as established sequential sensor placement algorithms and holds substantial promise for application to real jacket structures. KW - Optimal sensor placement KW - Value of information KW - Jacket support structure KW - Offshore wind turbine KW - Monitoring-informed inspection and maintenance planning PY - 2023 DO - https://doi.org/10.1016/j.oceaneng.2023.115407 SN - 0029-8018 VL - 288 IS - 2 PB - Elsevier Ltd. CY - Amsterdam AN - OPUS4-58725 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 T1 - Parallelized adaptive Bayesian updating with structural reliability methods for inference of large engineering models N2 - The reassessment of engineering structures, such as bridges, now increasingly involve the integration of models with realworld data. This integration aims to achieve accurate ‘as-is’ analysis within a digital twin framework. Bayesian model updating combines prior knowledge and data with models to enhance the modelling accuracy while consistently handling uncertainties. When updating large engineering models, numerical methods for Bayesian analysis present significant computational challenges due to the need for a substantial number of likelihood evaluations. The novelty of this contribution is to parallelize adaptive Bayesian Updating with Structural reliability methods combined with subset simulation (aBUS) to improve its computational efficiency. To demonstrate the efficiency and practical applicability of the proposed approach, we present a case study on the Maintalbrücke Gemünden, a large railway bridge. We leverage modal property data to update a linear-elastic dynamic structural model of the bridge. The parallelized aBUS approach significantly reduces computational time, making Bayesian updating of large engineering models feasible within reasonable timeframes. The improved efficiency allows for a wider implementation of Bayesian model updating in structural health monitoring and maintenance decision support systems. KW - Bayesian model updating KW - Bayesian updating with structural reliability methods KW - Structural health monitoring KW - Parallelization KW - Modal analysis KW - Railway bridge PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-633686 DO - https://doi.org/10.1177/13694332251346848 SN - 1369-4332 SN - 2048-4011 SP - 1 EP - 26 PB - Sage AN - OPUS4-63368 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Hüsken, Götz A1 - Shamsuddoha, Md A1 - Pirskawetz, Stephan A1 - Hofmann, Detlef A1 - Baeßler, Matthias A1 - Kühne, Hans-Carsten T1 - Potential of a Repair System for Grouted Connections in Offshore Structures: Development and Experimental Verification N2 - Grouted connections are intensively used in offshore rigs, platforms as well as jacket and monopile offshore wind turbine structures. Being located in remote offshore conditions, these connections can experience considerable adverse loading during their lifetimes. Degradation was reported inside similar connections, which were installed in the last three decades. Grouting in the offshore sites may often be proven difficult, which eventually leads to reduced load-bearing capacity of connections in the long run. Thus, repair and rehabilitation of such connections should be planned ahead to minimize operational delays and costs. In this study, scaled grouted connections were manufactured using a novel mould, whose integrity were monitored using digital image correlation (DIC). The connections were loaded under static load to visualize the main failure pattern using distributed fibre optic sensors and acoustic emission (AE) analysis. Grouted connections were then repaired using a cementitious injectable grout. The effectiveness of the grout injection was monitored using dye penetration technique. Finally, specimens are reloaded to identify the potential of such repair for grouted connections. KW - Offshore KW - Grouted connection KW - Fibre optic sensors KW - Acoustic emission analysis KW - Cracks KW - Repair KW - Rehabilitation KW - Static loading PY - 2021 DO - https://doi.org/10.1016/j.marstruc.2021.102934 VL - 77 SP - 102934 PB - Elsevier Ltd. AN - OPUS4-52059 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -