TY - CONF A1 - Bayane, I. A1 - Long, Lijia A1 - Thöns, Sebastian A1 - Brühwiler, E. T1 - Quantification of the conditional value of SHM data for the fatigue safety evaluation of a road viaduct N2 - Fatigue safety verification of existing bridges that uses ‘‘re-calculation’’ based on codes, usually results in insufficient fatigue safety, triggering invasive interventions. Instead of “re-calculation”, Structural Health Monitoring (SHM) should be used for the assessment of the existing bridges. Monitoring systems provide data that can reduce uncertainties associated with the fatigue loading process and the structural resistance. The objective of this paper is to quantify the value of the SHM system implemented in a 60-years-old road viaduct to investigate its fatigue safety, through modeling of the fundamental decisions of performing monitoring in conjunction with its expected utility. The quantification of the conditional value of information is based on the decision tree analysis that considers the structural reliability, various decision scenarios as well as the cost-benefit assessments. This leads to a quantitative decision basis for the owner about how much time and money can be saved while the viaduct fulfills its function reliably and respects the safety requirements. The originality of this paper stands in the application of the value of information theory to an existing viaduct considering the fatigue failure of the system based on the monitoring data and the cost-benefit of monitoring method. T2 - 13th International Conference on Applications of Statistics and Probability in Civil Engineering CY - Seoul, South Korea DA - 26.05.2019 KW - Fatigue safety KW - Value of information PY - 2019 SP - 275 EP - 288 CY - Seoul, South Korea AN - OPUS4-50809 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Berchtold, Florian A1 - Knaust, Christian A1 - Rogge, Andreas A1 - Arnold, L. A1 - Thöns, Sebastian ED - Lönnermark, Anders ED - Ingason, Haukur T1 - Risk Analysis for Road Tunnels – A Metamodel to Efficiently Integrate Complex Fire Scenarios N2 - Fires in road tunnels constitute complex scenarios with interactions between the fire, tunnel users and safety measures. More and more methodologies for risk analysis quantify the consequences of these scenarios with complex models. Examples for complex models are the computational fluid dynamics model Fire Dynamics Simulator (FDS) and the microscopic evacuation model FDS+Evac. However, the high computational effort of complex models often limits the number of scenarios in practice. To balance this drawback, the scenarios are often simplified. Accordingly, there is a challenge to consider complex scenarios in risk analysis. To face this challenge, we improved the metamodel used in the methodology for risk analysis presented on ISTSS 2016. In general, a metamodel quickly interpolates the consequences of few scenarios simulated with the complex models to a large number of arbitrary scenarios used in risk analysis. Now, our metamodel consists of the projection array-based design, the moving least squares method, and the prediction interval to quantify the metamodel uncertainty. Additionally, we adapted the projection array-based design in two ways: the focus of the sequential refinement on regions with high metamodel uncertainties; and the combination of two experimental designs for FDS and FDS+Evac. To scrutinise the metamodel, we analysed the effects of three sequential refinement steps on the metamodel itself and on the results of risk analysis. We observed convergence in both after the second step (ten scenarios in FDS, 192 scenarios in FDS+Evac). In comparison to ISTSS 2016, we then ran 20 scenarios in FDS and 800 scenarios in FDS+Evac. Thus, we reduced the number of scenarios remarkably with the improved metamodel. In conclusion, we can now efficiently integrate complex scenarios in risk analysis. We further emphasise that the metamodel is broadly applicable on various experimental or modelling issues in fire safety engineering. T2 - International Symposium on Tunnel Safety and Security CY - Boras, Sweden DA - 14.03.2018 KW - Risk KW - Metamodel KW - CFD KW - Evacuation KW - Uncertainty PY - 2018 SN - 978-91-88695-48-2 VL - 8 SP - 349 EP - 360 AN - OPUS4-44535 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Brüske, H. A1 - Thöns, Sebastian T1 - Value of pre‐construction proof loading information for structural design N2 - We introduce a new concept that enables a decision analyst to explore and quantify the benefits of decision alternatives that exceed the scope of a pre‐posterior decision or value of information analysis. This new concept, namely, the expected value of sample information and action analysis, facilitates to examine decision alternatives that become only possible with additional knowledge. The concept is introduced by taking basis in proof load testing as a source of (pre‐)posterior knowledge. Pre‐posterior decision analysis is necessary in order to optimize the structural design through proof loading information. The application of the common value of information Analysis and the new value of information and action analysis are demonstrated in a case study. KW - Value of information and action KW - Pre‐construction proof loading KW - Pre‐posterior decision analysis KW - Structural design optimization PY - 2019 U6 - https://doi.org/10.1002/we.2398 SN - 1095-4244 SP - 1 EP - 17 PB - John Wiley & Sons AN - OPUS4-48804 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Farhan, Muhammad A1 - Schneider, Ronald A1 - Thöns, Sebastian T1 - Corrigendum to Predictive information and maintenance optimization based on decision theory: a case study considering a welded joint in an offshore wind turbine support structure N2 - This article has been revised and republished due to substantial changes to the text of the original article, as published Online First on January 31, 2021. Most of the change were minor grammatical changes. The following changes are more significant and will be highlighted below. KW - Integrity management KW - Decision theory KW - Value of information KW - Structural reliability KW - Fracture mechanics KW - Fatigue KW - Predictive maintenance KW - Wind turbine support structure PY - 2022 U6 - https://doi.org/10.1177/14759217211040385 SN - 1475-9217 VL - 21 IS - 4 SP - 1956 EP - 1956 PB - Sage Publications CY - London AN - OPUS4-55165 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 U6 - 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 - 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 - 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 - 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 - 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 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-527987 SP - 224 EP - 235 PB - Springer AN - OPUS4-52798 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 -