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 - 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 U6 - 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 -