TY - JOUR A1 - Kapoor, M. A1 - Overgaard Christensen, Ch. A1 - Wittrup Schmidt, J. A1 - Dalsgaard Sørensen, J. A1 - Thöns, Sebastian T1 - Decision analytic approach for the reclassification of concrete bridges by using elastic limit information from proof loading N2 - Reclassification of bridges, i.e., a change in load rating, using reliability-based methods and a direct update with proof load information has been presented by many authors. However, bridge reclassification has hardly been studied from a decision analytic perspective, i.e., with quantification of the risks and benefits of different classification choices, and the expected benefit gain from proof loading. We derive, explain and exemplify a decision analytic approach for bridge reclassification along with models for (1) elastic and ultimate capacity and their adaptation with proof load information, (2) proof load information with classification outcomes accounting for target reliabilities and, (3) utilities including socio-economic benefits from reclassification. The approach and models are exemplified with a case study based on reclassification of bridges with a low existing classification. Decision rules, for practical use by a highway authority to find the optimal classification, are identified and documented based on: (1) the measurement of the capacity at elastic limit by proof loading, (2) the bridge reclassification benefits, and, (3) the required annual reliability level. From a Value of Information analysis, it is concluded that the proof load information is highly valuable for reclassification in cases of high socio-economic benefits and high reliability requirements. KW - Proof loading KW - Structural reliability KW - Value of information KW - Decision analysis PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-596845 DO - https://doi.org/10.1016/j.ress.2022.109049 SN - 0951-8320/ VL - 232 SP - 1 EP - 16 PB - Elsevier Ltd. AN - OPUS4-59684 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Long, Lijia A1 - Anh Mai, Q. A1 - Morato, P. G. A1 - Dalsgaard Sorensen, J. A1 - Thöns, Sebastian T1 - Information value-based optimization of structural and environmental monitoring for offshore wind turbines support structures N2 - The use of load and structural performance measurement information is vital for efficient structural integrity management and for the cost of energy production with Offshore Wind Turbines (OWTs). OWTs are dynamically sensitive structures subject to an interaction with a control unit exposed to repeated cyclic wind and wave loads causing deterioration and fatigue. This study focuses on the quantification of the value of structural and environmental information on the integrity management of OWT structures, with the focus on fatigue of welded joints. By utilizing decision analysis, structural reliability methods, measurement data, as well as the cost-benefit models, a Value of Information (VoI) analysis can be performed to quantify the most beneficial measurement strategy. The VoI assessment is demonstrated for the integrity management of a butt welded joint of a monopile support structure for a 3 MW OWT with a hub height of approximately 71m. The conditional value of three-year measured oceanographic information and one-year strain monitoring information is quantified posteriori in conjunction with an inspection and repair planning. This paper provides insights on how much benefits can be achieved through structural and environmental information, with practical relevance on reliability-based maintenance of OWT structures. KW - Structural health monitoring KW - Offshore wind turbine KW - Monopile support structure KW - Value of information KW - Weld fatigue KW - Decision tree KW - Dynamic Bayesian Network PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-514098 DO - https://doi.org/10.1016/j.renene.2020.06.038 VL - 10 IS - 159 SP - 1036 EP - 1046 PB - Elsevier Ltd. AN - OPUS4-51409 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -