TY - JOUR A1 - Schneider, Ronald A1 - Thöns, Sebastian A1 - Straub, Daniel T1 - Reliability analysis and updating of deteriorating systems with subset simulation N2 - An efficient approach to reliability analysis of deteriorating structural systems is presented, which considers stochastic dependence among element deterioration. Information on a deteriorating structure obtained through inspection or monitoring is included in the reliability assessment through Bayesian updating of the system deterioration model. The updated system reliability is then obtained through coupling the updated deterioration model with a probabilistic structural model. The underlying high-dimensional structural reliability problems are solved using subset simulation, which is an efficient and robust sampling-based algorithm suitable for such analyses. The approach is demonstrated in two case studies considering a steel frame structure and a Daniels system subjected to high-cycle fatigue. KW - Structural reliability KW - Deterioration KW - Bayesian analysis KW - Inspection KW - Monitoring KW - Subset simulation PY - 2017 DO - https://doi.org/10.1016/j.strusafe.2016.09.002 SN - 0167-4730 SN - 1879-3355 VL - 64 SP - 20 EP - 36 PB - Elsevier AN - OPUS4-38218 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 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 - JOUR A1 - Thöns, Sebastian A1 - Schneider, Ronald T1 - The Influence of brittle Daniels system characteristics on the value of load monitoring information N2 - This paper addresses the influence of deteriorating brittle Daniels system characteristics on the value of structural health monitoring (SHM). The value of SHM is quantified as the difference between the life cycle benefits with and without SHM. A value of SHM analysis is performed within the framework of the Bayesian pre-posterior decision theory and requires (1) structural performance modelling and prediction, (2) structural integrity management models, (3) the (pre-posterior) modelling of SHM and (4) the coupling of SHM and the structural performance models. The pre-posterior decision theoretical framework facilitates that the value of SHM can be quantified before the SHM system is quantified and before data are acquired. The results of this study support decisions to select structural systems for which the SHM strategy load monitoring is optimal. T2 - 8th European Workshop on Structural Health Monitoring (EWSHM 2016) CY - Bilbao, Spain DA - 05.07.2016 KW - Value of information KW - Structural performance KW - Deterioration KW - Daniels systems PY - 2016 UR - http://www.ndt.net/?id=20186 SN - 1435-4934 VL - 21 IS - 8 SP - 1 EP - 9 PB - NDT.net CY - Kirchwald AN - OPUS4-38217 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -