TY - JOUR A1 - Long, Lijia A1 - Alcover, I. F. A1 - Thöns, Sebastian T1 - Utility analysis for SHM durations and service life extension of welds on steel bridge deck JF - Structure and Infrastructure Engineering Maintenance, Management, Life-Cycle Design and Performance Latest Articles N2 - Optimization of the duration of Structural Health Monitoring (SHM) campaigns is rarely performed. This article provides a utility-based solution to posteriorly determine: i) optimal monitoring Durations and ii) the extension of the service life of the welds on a steel bridge deck. The approach is Illustrated with a case study focusing on remaining fatigue life estimation of the welds on the orthotropic steel deck of the Great Belt Bridge, in Denmark. The identification of the optimal monitoring duration and the decision about extending the service life of the welds are modelled by maximizing the expected benefits and minimizing the structural risks. The results are a parametric analysis, mainly on the effect of the target probability, benefit, cost of failure, cost of rehabilitation, cost of monitoring and Discount rate on the posterior utilities of monitoring strategies and the choice of service life considering the risk variability and the costs and benefits models. The results show that the decision on short-term monitoring, i.e., 1 week every six months, is overall the most valued SHM strategy. In addition, it is found that the target probability is the most sensitive parameter affecting the optimal SHM Durations and service life extension of the welds. KW - Fatigue KW - Monitoring strategy KW - Orthotropic steel deck KW - Structural health monitoring KW - Utility and decision theory PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-521719 DO - https://doi.org/10.1080/15732479.2020.1866026 SN - 1573-2479 VL - 18 IS - 4 SP - 492 EP - 504 PB - Taylor Francis Online AN - OPUS4-52171 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kinne, Marko A1 - Schneider, Ronald A1 - Thöns, Sebastian T1 - Reconstructing Stress Resultants in Wind Turbine Towers Based on Strain Measurements N2 - Support structures of offshore wind turbines are subject to cyclic stresses generated by different time-variant random loadings such as wind, waves, and currents in combinationwith the excitation by the rotor. In the design phase, the cyclic demand on wind turbine support structure is calculated and forecasted with semi or fully probabilistic engineering models. In some cases, additional cyclic stresses may be induced by construction deviations, unbalanced rotor masses and structural dynamic phenomena such as, for example, the Sommerfeld effect. Both, the significant uncertainties in the design and a validation of absence of unforeseen adverse dynamic phenomena necessitate the employment of measurement Systems on the support structures. The quality of the measurements of the cyclic demand on the support structures depends on (a) the precision of the measurement System consisting of sensors, amplifier and data normalization and (b) algorithms for analyzing and converting data to structural health information. This paper presents the probabilistic modelling and analysis of uncertainties in strain measurements performed for the purposes of reconstructing stress resultants in wind turbine towers. It is shown how the uncertainties in the strain measurements affect the uncertainty in the individual components of the reconstructed forces and moments. The analysis identifies the components of the vector of stress resultants that can be reconstructed with sufficient precision. T2 - International Conference on Uncertainty in Mechanical Engineering - ICUME CY - Online meeting DA - 07.06.2021 KW - Reconstruction of stress resultants KW - Strain measurements KW - Bayesian updating of measurement uncertainties PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-527987 DO - https://doi.org/10.1007/978-3-030-77256-7_18 SP - 224 EP - 235 PB - Springer AN - OPUS4-52798 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Farhan, Muhammad A1 - Schneider, Ronald A1 - Thöns, Sebastian T1 - Predictive information and maintenance optimization based on decision theory: a case study considering a welded joint in an offshore wind turbine support structure JF - Structural health monitoring N2 - Predictive information and maintenance optimization for deteriorating structures is concerned with scheduling (a) the collection of information by inspection and monitoring and (b) maintenance actions such as repair, replacement, and retrofitting based on updated predictions of the future condition of the structural system. In this article, we consider the problem of jointly identifying—at the beginning of the service life—the optimal inspection time and repair strategy for a generic welded joint in a generic offshore wind turbine structure subject to fatigue. The optimization is performed based on different types of decision analyses including value of information analyses to quantify the expected service life cost encompassing inspection, repair, and fatigue damage for all relevant combinations of inspection time, repair method, and repair time. Based on the analysis of the expected service life cost, the optimal inspection time, repair method, and repair time are identified. Possible repair methods for a welded joint in an offshore environment include welding and grinding, for which detailed models are formulated and utilized to update the joint’s fatigue performance. The decision analyses reveal that an inspection should be scheduled approximately at mid-service life of the welded joint. A repair should be performed in the same year after an indication and measurement of a fatigue crack given an optimal inspection scheduling. This article concludes with a discussion on the results obtained from the decision and value of information analyses. KW - Integrity management KW - Value of information KW - Decision theory KW - Structural reliability KW - Fracture mechanics KW - Fatigue KW - Predictive maintenance KW - Wind turbine support structure PY - 2021 DO - https://doi.org/10.1177/1475921720981833 SN - 1475-9217 SN - 1741-3168 PB - Sage Publications CY - London AN - OPUS4-52771 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kapoor, M. A1 - Sørensen, J. D. A1 - Ghosh, S. A1 - Thöns, Sebastian T1 - Decision theoretic approach for identification of optimal proof load with sparse resistance information T2 - Proceedings of the 10th international conference on bridge maintenance, safety and management (IABMAS) N2 - Proof load testing may be performed to confirm the reliability of the bridge for an existing classification or to prove the reliability for a higher classification. In this paper, a probabilistic decision analysis approach is applied to the scenario for the evaluation of target proof load in the situation where information on the bridge resistance model is lacking. In this case, the resistance model is established by proof loading and taking very basic prior knowledge into account. The decision scenario is modelled in the context of the proof load test planner who shall choose the required load level for assessment of a bridge. The choice of the load level depends on the risks due to the testing and the expected benefit gain from the test. Information acquired about the loading response from monitoring during the proof load testing is modelled by taking basis in the model uncertainty formulation. The optimal proof load level for classification of a single lane, simply supported bridge of 8m span subjected to live load from very heavy (gross weight > 80 tons) transport vehicles was calculated. The optimal proof load level was identified as leading to a positive expected benefit gain to the decision maker while also satisfying target reliability criteria for remaining service life. The analysis was performed for the evaluation of bridge performance with respect to five classifications of very heavy transport vehicles with different vehicle weights and configurations. T2 - 10th International Conference on Bridge Maintenance, Safety and Management (IABMAS) CY - Sapporo, Japan DA - 11.04.2021 KW - Proof load testing KW - Probabilistic decision analysis KW - Bridge resistance model PY - 2021 SN - 978-0-429-27911-9 DO - https://doi.org/10.1201/9780429279119-104 SP - 789 EP - 797 PB - CRC Press CY - Boca Raton, Florida AN - OPUS4-57879 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -