TY - CONF A1 - Schneider, Ronald T1 - Towards predictive maintenance of bridges N2 - Key features of predictive maintenance of structural systems are discussed and demonstrated in two examples. Challenges and needs for further research are discussed. T2 - Workshop Bridge Maintenance CY - Online Meeting DA - 09.04.2021 KW - Predictive maintenance KW - Deterioration KW - Structural systems PY - 2021 AN - OPUS4-52768 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald A1 - 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 - JOUR A1 - Straub, D. A1 - Schneider, Ronald A1 - Bismut, E. A1 - Kim, H.-J. T1 - Reliability analysis of deteriorating structural systems N2 - Reliability analysis of deteriorating structural systems requires the solution of time-variant reliability problems. In the general case, both the capacity of and the loads on the structure vary with time. This analysis can be approached by approximation through a series of time-invariant reliability problems, which is a potentially effective strategy for cases where direct solutions of the time-variant reliability problem are challenging, e.g. for structural systems with many elements or arbitrary load processes. In this contribution, we thoroughly Review the formulation of the equivalent time-invariant reliability problems and extend this approximation to structures for which inspection and monitoring data is available. Thereafter, we present methods for efficiently evaluating the reliability over time. In particular, we propose the combination of sampling-based methods with a FORM (first-order reliability method) approximation of the series system reliability problem that arises in the computation of the lifetime reliability. The framework and algorithms are demonstrated on a set of numerical examples, which include the computation of the reliability conditional on inspection data. KW - Monitoring KW - Reliability KW - Deterioration KW - Structural systems KW - Bayesian analysis KW - Inspection PY - 2020 DO - https://doi.org/10.1016/j.strusafe.2019.101877 VL - 82 SP - Paper 101877, 1 PB - Elsevier Ltd. AN - OPUS4-48952 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald T1 - A risk-based framework for optimizing inspection and maintenance of deteriorating structures monitored by vibration-based monitoring systems N2 - In this presentation, a framework for integrating vibration-based structural health monitoring data into the optimization of inspection and maintenance of deteriorating structural systems is presented. The framework is demonstrated in an illustrative example considering a steel frame subject to fatigue. T2 - EERA JP Wind WORKSHOP on Ongoing research in offshore wind structures CY - Online meeting DA - 16.09.2021 KW - Structural Health Monitoring KW - Inspection KW - Maintenance KW - Deterioration KW - Vibration KW - Structural Systems PY - 2021 AN - OPUS4-53749 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald T1 - Structural integrity management research at BAM N2 - This presentation provides an overview on the structural integrity management research at BAM. In addition, a framework for monitoring and risk-informed inspection and maintenance planning for offshore steel structures is presented. T2 - Structural Health Monitoring Using Statistical Pattern Recognition CY - Berlin, Germany DA - 20.03.2023 KW - Structural integrity KW - Monitoring KW - Maintenance KW - Inspeciton KW - Bridges KW - Offshore wind PY - 2023 AN - OPUS4-57864 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schneider, Ronald T1 - Modeling in support of offshore wind farm end-of-life decision making N2 - The EU member states have set out ambitious long-term goals for deploying offshore wind energy. The installed offshore wind capacity is set to increase from 14.6 GW in 2021 to around 320 GW in 2050. This signifies the role of offshore wind energy as a major contributor to reaching the EU’s climate and energy goals. To ensure that the defined targets are met, a significant number of new wind farms has to be installed and existing wind farms reaching the end of their planned life need to be reused efficiently. Some of the relevant reuse alternatives are lifetime extension, repowering based on the existing support structures and repowering with new turbines. As a basis of the decision-making regarding the reuse of existing offshore wind farm, the expected utility of each relevant option should be determined based on the associated expected rewards, costs and risks. The optimal concept maximizes the utility of the decision-maker and fulfills the existing constraints and requirements. To facilitate such a quantitative decision-making, models and methods have to be developed. In particular, models are required that enable predictions of (a) the condition and performance of the turbines and support structures and (b) the renumeration, costs and consequences of adverse events. These predictions have to consider (a) the governing uncertainties, (b) the available information from the planning, construction, installation and operating phase, (b) potential repair, retrofitting and strengthening schemes and (c) possible monitoring, inspection and maintenance regimes for the future operating phase. Over the past years, several models, methods and tools have been developed at the Bundesanstalt für Materialforschung und -prüfung (BAM) to support the structural integrity management of offshore wind turbine substructures. These include: (a) a prototype for reliability-based, system-wide, adaptive planning of inspections of welded steel structures in offshore wind farms, (b) a method for monitoring and risk-informed optimization of inspection and maintenance strategies for jacket structures subject to fatigue, and (c) a probabilistic cost model of inspection and maintenance of welded steel structures in offshore wind farms. This contribution provides an overview on these works and discusses how they can be adapted and extended to support the decision-making regarding lifetime extensions and repowering of offshore wind farms. T2 - 12th International Forum on Engineering Decision Making (12th IFED) CY - Stoos, Switzerland DA - 05.12.2023 KW - Windenergie KW - Offshore Wind KW - Lifetime Extension KW - Repowering PY - 2023 AN - OPUS4-60430 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 - 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 - 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 -