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 - TY - JOUR A1 - Hu, Wei-Hua A1 - Thöns, Sebastian A1 - Rohrmann, Rolf A1 - Said, Samir A1 - Rücker, Werner T1 - Vibration-based structural health monitoring of a wind turbine system. Part I: Resonance phenomenon N2 - This paper is focused on a resonance phenomenon of a wind turbine system in 5 MW class, on the basis of dynamic signals acquired continuously from the tubular tower under normal operational conditions during two years. Firstly, technique specifications of the wind turbine system are introduced and a finite element model is developed to characterize the structural dynamic properties. The following part describes the continuous dynamic monitoring system integrated with an automated operational modal analysis procedure using the poly-reference Least Squares Complex Frequency domain (p-LSCF) method. Subsequently, variations and mutual relationships of environmental/operational factors such as vibration amplitude, temperature, wind speed, rotation speed of blades, pitch angle and nacelle direction are also presented. Finally, significant resonance is observed due to the fundamental frequency of the tower matching with the harmonic frequency induced by the rotation of three blades. As the rotation speed of rotor approaches to 8 rpm, the vibration amplitude of the tower increases significantly and the corresponding damping value decreases. With the further rising wind velocity, the rotation speed of blades stops increasing and the input energy just contribute to accumulate the vibration amplitude of tower. Such observation indicates the Sommerfeld effect that aggravates the resonance phenomenon. A vibration control device is necessary to minimize the excessive structural responses. A companion paper will further discuss the environmental/operational effects on dynamic properties of the wind turbine system under the operational conditions. KW - Vibration KW - Structural health monitoring KW - Wind turbine KW - Automated operational modal analysis KW - Resonance KW - Sommerfeld effect PY - 2015 U6 - https://doi.org/10.1016/j.engstruct.2014.12.034 SN - 0141-0296 VL - 89 SP - 260 EP - 272 PB - Elsevier Ltd. CY - Oxford AN - OPUS4-32878 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Hu, Wei-Hua A1 - Thöns, Sebastian A1 - Rohrmann, Rolf A1 - Said, Samir A1 - Rücker, Werner T1 - Vibration-based structural health monitoring of a wind turbine system. Part II: Environmental/operational effects on dynamic properties N2 - The second part of these companion papers mainly researches environmental/operational influences on structural dynamic properties under normal operational conditions during two years, in order to extract a statistical based damage-sensitive indicator for health monitoring of a wind turbine system. The correlation analyses between experimental identified frequencies, damping values as well as mode shapes and environmental/operational factors such as rotation speed of blades, wind speed, pitch angle, temperature and nacelle direction are presented. It is observed that the frequency estimates are influenced by the nacelle position, the activation of rotor, the rotation speed of blades and the wind speed as well as the temperature. Regarding to the damping estimates, they are mainly associated with variation of the aerodynamic damping due to the increasing wind speed. Besides, the resonance phenomenon is also observed in higher modes. The harmonic frequencies due to blades passing by tower are found and the corresponding damping value decreases. Moreover, the mode shapes in some modes are strongly affected by the position of the nacelle. Subsequently, two types of simulated damage including the reduction of stiffness in both the rotor blade and the tubular tower are successfully detected by applying the Principal Component Analysis (PCA) based methods to these temperature-sensitive frequency estimates. Comparison of change of the extracted health features indicates that they are more sensitive with the tower damage. KW - Vibration KW - Structural health monitoring KW - Wind turbine KW - Environmental/operational effects KW - Modal properties KW - Principal Component Analysis KW - Novelty analysis KW - Damage detection KW - Sommerfeld effect KW - Automated operational modal analysis KW - Resonance PY - 2015 U6 - https://doi.org/10.1016/j.engstruct.2014.12.035 SN - 0141-0296 VL - 89 SP - 273 EP - 290 PB - Elsevier Ltd. CY - Oxford AN - OPUS4-32879 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Thöns, Sebastian T1 - On the Value of Monitoring Information for the Structural Integrity and Risk Management N2 - This article introduces an approach and framework for the quantification of the value of structural health monitoring (SHM) in the context of the structural risk and integrity management for systems. The quantification of the value of SHM builds upon the Bayesian decision and utility theory, which facilitates the assessment of the value of information associated with SHM. The principal approach for the quantification of the value of SHM is formulated by modeling the fundamental decision of performing SHM or not in conjunction with their expected utilities. The expected utilities are calculated accounting for the probabilistic performance of a system in conjunction with the associated structural integrity and risk management actions throughout the life cycle, the associated benefits, structural risks, and costs and when performing SHM, the SHM information, their probabilistic outcomes, and costs. The calculation of the expected utilities necessitates a comprehensive and rigorous modeling, which is introduced close to the original formulations and for which analysis characteristics and simplifications are described and derived. The framework provides the basis for the optimization of the structural risk and integrity management based on utility gains including or excluding SHM and inspection information. Studies of fatigue deteriorating structural Systems and their characteristics (1) provide decision Support for the performance of SHM, (2) explicate the influence of the structural component and system characteristics on the value of SHM, and (3) demonstrate how an integral optimization of SHM and inspection strategies for an efficient structural risk and integrity management can be performed. KW - Monitoring KW - Structural Integrity and Risk Management KW - SHM PY - 2018 U6 - https://doi.org/10.1111/mice.12332 VL - 33 IS - 1 SP - 79 EP - 94 PB - John Wiley & Sons, Inc. CY - Hoboken, NJ, USA AN - OPUS4-44537 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Long, Lijia A1 - Döhler, M. A1 - Thöns, Sebastian T1 - Determination of structural and damage detection system influencing parameters on the value of information N2 - A method to determine the influencing parameters of a structural and damage detection system is proposed based on the value of Information analysis. The value of information analysis utilizes the Bayesian pre-posterior decision theory to quantify the value of damage detection system for the structural integrity management during service life. First, the influencing parameters of the structural system, such as deterioration type and rate are introduced for the performance of the prior probabilistic system model. Then the influencing parameters on the damage detection system performance, including number of sensors, sensor locations, measurement noise, and the Type-I error are investigated. The preposterior probabilistic model is computed utilizing the Bayes’ theorem to update the prior system model with the damage indication information. Finally, the value of damage detection system is quantified as the difference between the maximum utility obtained in pre-posterior and prior analysis based on the decision tree analysis, comprising structural probabilistic models, consequences, as well as benefit and costs analysis associated with and without monitoring. With the developed approach, a case study on a statically determinate Pratt truss bridge girder is carried out to validate the method. The analysis shows that the deterioration rate is the most sensitive parameter on the effect of relative value of information over the whole service life. Furthermore, it shows that more sensors do not necessarily lead to a higher relative value of information; only specific sensor locations near the highest utilized components lead to a high relative value of information; measurement noise and the Type-I error should be controlled and be as small as possible. An optimal sensor employment with highest relative value of information is found. Moreover, it is found that the proposed method can be a powerful tool to develop optimal service life maintenance strategies—before implementation—for similar bridges and to optimize the damage detection system settings and sensor configuration for minimum expected Costs and risks. KW - Damage detection systems KW - Value of information KW - Deteriorating structures KW - Probability of damage indication KW - Decision theory PY - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-508083 SN - 1475-9217 SN - 1741-3168 VL - 21 IS - 1 SP - 19 EP - 36 PB - Sage Publications CY - Thousand Oaks, Calif. AN - OPUS4-50808 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Thöns, Sebastian A1 - Stewart, M. G. T1 - On the cost-efficiency, significance and effectiveness of terrorism risk reduction strategies for buildings N2 - We analyse the performance of risk reduction strategies for Terrorist attacks with Improvised Explosive Devices (IEDs) for large governmental building structures in terms of cost-efficiency, significance and effectiveness Accounting for life safety in conjunction with societal preferences and capabilities. The approach builds upon an extended Bayesian pre-posterior decision analysis and the principles of the marginal lifesaving costs based on the Life Quality Index (LQI). The decision scenario is formulated for a decision maker responsible for the safety of governmental or large commercial buildings and consequently the direct risks, the indirect risks due to fatalities and economical importance of the building beside the expected cost for the individual risk reduction strategies are modelled, aggregated and optimised. The considered risk reduction strategies encompass an explicit consideration and distinction of information and actions such as (i) threat surveillance may trigger the temporary evacuation of the building, (ii) the implementation of protection provisions provided by codes and guidelines, (iii) a detailed progressive collapse assessment and specific protection measures and (iv) the combination of protection and surveillance. All considered strategies are found to contribute to risk reduction and can be costefficient, especially for higher threat probabilities. The risk reduction strategies comply with societal macroeconomic and demographical characteristics and societal preferences according to the LQI. The progressive collapse assessment with targeted protection measures is found to be the most cost-efficient, significant and effective counter-terrorism strategy. This finding points to the necessity for a comprehensive utilisation of scientific methods and sophisticated engineering for progressive collapse assessment to determine targeted protection measures. KW - Significance and effectiveness KW - Risk mitigation strategies KW - Terrorist attacks KW - Value of information KW - Bayesian probability KW - Reliability KW - Risk and decision analysis KW - Decision optimality PY - 2020 U6 - https://doi.org/10.1016/j.strusafe.2020.101957 VL - 85 SP - 10195 PB - Elsevier Ltd. AN - OPUS4-50794 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 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-514098 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 - 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 - JOUR A1 - Rastayesh, S. A1 - Long, Lijia A1 - Sørensen, J. D. A1 - Thöns, Sebastian T1 - Risk Assessment and Value of Action Analysis for Icing Conditions of Wind Turbines Close to Highways N2 - The paper presents research results from the Marie Skłodowska-Curie Innovative Training Network INFRASTAR in the field of reliability approaches for decision-making for wind turbines and bridges. This paper addresses the application of Bayesian decision analysis for installation of heating systems in wind turbine blades in cases where an ice detection system is already installed in order to allow wind turbines to be placed close to highways. Generally, application of ice detection and heating systems for wind turbines is very relevant in cases where the wind turbines are planned to be placed close to urban areas and highways, where risks need to be considered due to icing events, which may lead to consequences including human fatality, functional disruptions, and/or economic losses. The risk of people being killed in a car passing on highways near a wind turbine due to blades parts or ice pieces being thrown away in cases of overicing is considered in this paper. The probability of being killed per kilometer and per year is considered for three cases: blade parts thrown away as a result of a partial or total failure of a blade, ice thrown away in two cases, i.e., of stopped wind turbines and of wind turbines in operation. Risks due to blade parts being thrown away cannot be avoided, since low strengths of material, maintenance or manufacturing errors, mechanical or electrical failures may result in failure of a blade or blade part. The blade (parts) thrown away from wind turbines in operation imply possible consequences/fatalities for people near the wind turbines, including in areas close to highways. Similar consequences are relevant for ice being thrown away from wind turbine blades during icing situations. In this paper, we examine the question as to whether it is valuable to put a heating System on the blades in addition to ice detection systems. This is especially interesting in countries with limited space for placing wind turbines; in addition, it is considered if higher power production can be obtained due to less downtime if a heating system is installed. KW - Risk assessment KW - Value of action analysis KW - Icing conditions KW - Wind turbine KW - Blade PY - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-487805 VL - 12 IS - 14 SP - 2653-1 EP - 2653-15 PB - MDPI AN - OPUS4-48780 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Thöns, Sebastian A1 - Döhler, M. A1 - Long, Lijia T1 - On Damage Detection System Information for Structural Systems N2 - Damage detection systems (DDS) provide information of the structural system integrity in contrast to e.g. local information by inspections or non-destructive testing techniques. In this paper, an approach is developed and demonstrated to utilize DDS information to update the structural system reliability and to integrate this information in structural system risk and utility analyses. For this aim, a novel performance modelling of DDS building upon their system characteristics and non-destructive testing reliability is introduced. The DDS performance modelling accounts for a measurement system in combination with a damage detection algorithm attached to a structural system in the reference and damage states and is modelled with the probability of indication accounting for type I and II errors. In this way, the basis for DDS performance comparison and assessment is provided accounting for the dependencies between the damage states in a structure. For updating of the structural system reliability, an approach is developed based on Bayesian updating facilitating the use of DDS information on structural system level and thus for a structural system risk analysis. The structural system risk analysis encompasses the static, dynamic, deterioration, reliability and consequence models, which provide the basis for the system model for calculating the direct risks due to component failure and the indirect risks due to system failure. Two case studies with the developed approach demonstrate a high Value of DDS Information due to risk and expected cost reduction. KW - Damage detection KW - Value of Information KW - Structural systems KW - Damage detection uncertainty PY - 2018 U6 - https://doi.org/10.1080/10168664.2018.1459222 VL - 28 IS - 3 SP - 255 EP - 268 PB - Taylor & Francis AN - OPUS4-46964 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 - 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 -