TY - CONF A1 - Long, Lijia A1 - Thöns, Sebastian A1 - Döhler, M. T1 - The effects of SHM system parameters on the value of damage detection information N2 - This paper addresses how the value of damage detection Information depends on key Parameters of the Structural Health Monitoring (SHM) system including number of sensors and sensor locations. The Damage Detection System (DDS) provides the information by comparing ambient vibration measurements of a (healthy) reference state with measurements of the current structural system. The performance of DDS method depends on the physical measurement properties such as the number of sensors, sensor positions, measuring length and sensor type, measurement noise, ambient excitation and sampling frequency, as well as on the data processing algorithm including the chosen type I error for the indication threshold. The quantification of the value of Information (VoI) is an expected utility based Bayesian decision analysis method for quantifying the difference of the expected economic benefits with and without information. The (pre-)posterior probability is computed utilizing the Bayesian updating theorem for all possible indications. If changing any key parameters of DDS, the updated probability of system failure given damage detection information will be varied due to different indication of probability of damage, which will result in changes of value of damage detection information. The DDS system is applied in a statically determinate Pratt truss bridge girder. Through the analysis of the value of information with different SHM system characteristics, the settings of DDS can be optimized for minimum expected costs and risks before implementation. T2 - 9th European Workshop on Structural Health Monitoring CY - Manchester, UK DA - 10.07.2018 KW - SHM KW - Damage detection system KW - Value of information PY - 2018 SP - 375 EP - 384 AN - OPUS4-46190 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 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 U6 - 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 - TY - JOUR A1 - Kinne, Marko A1 - Thöns, Sebastian T1 - Fatigue Reliability Based on Predicted Posterior Stress Ranges Determined from Strain Measurements of Wind Turbine Support Structures N2 - In the present paper, an approach for updating the continuous stress range distribution of a welded connection of a wind turbine support structure with predicted information from strain measurements is presented. Environmental conditions, such as wind or, in offshore fields, waves and currents, in combination with rotor excitations generate cyclic stresses affecting the reliability of welded joints of the support structure over the service life. Using strain measurements, these conditions can be monitored, and the resulting stress ranges, under consideration of measurement, mechanical and material uncertainties, can be reconstructed. These stress ranges can be used as an input for updating the prior probability density function (PDF) of the stress ranges predicted by the overall dynamics and a detailed design analysis. Applying Bayesian probability theory and decision theoretical implications, the predicted posterior probability density of the stress ranges is calculated based on the design information and uncertainties. This approach is exemplified, and it is shown how the predicted stress ranges and the design stress ranges are distributed. The prior and the predicted posterior stress ranges are used for a reliability calculation for potentially entering a pre-posterior decision analysis KW - Strain measurements of wind turbine support structures KW - Bayesian updating of stress ranges KW - Posterior fatigue reliability PY - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-572663 VL - 16 IS - 5 SP - 1 EP - 26 PB - MDPI AN - OPUS4-57266 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kinne, Marko A1 - Farhan, Muhammad A1 - Schneider, Ronald A1 - Thöns, Sebastian T1 - Influence of the structural integrity management on the levelized cost of energy of offshore wind: a parametric sensitivity analysis N2 - The levelized cost of energy (LCoE) is an important measure to quantify the macro-economic efficiency of an offshore wind farm and to enable a quantitative comparison with other types of energy production. The costs of the structural integrity management - which is required to ensure an adequate lifetime reliability of the turbine support structures - are part of the operational expenditures of an offshore wind farm. An optimization of the structural integrity management may reduce the operational expenditures and consequently the LCoE. However, the effect of the structural integrity management on the LCoE is hardly known. To investigate this effect, this paper presents a sensitivity analysis of the LCoE of a generic offshore wind farm. The probabilistic models of the parameters influencing the LCoE are based on a literature study including an explicit model for the structural integrity management. The analysis reveals that LCoE may potentially be reduced if an optimization of the structural integrity management enables a service life extension. T2 - International Probabilistic Workshop 2022 CY - Stellenbosch, South Africa DA - 08.09.2022 KW - Structural integrity management KW - Levelized cost of energy KW - Sensitivity analysis PY - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-572724 VL - 36 SP - 90 EP - 98 PB - Acta Polytechnica CTU Proceedings AN - OPUS4-57272 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - 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 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-596845 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 -