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 DO - 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 - THES A1 - Thöns, Sebastian T1 - Monitoring based condition assessment of offshore wind turbine support structures N2 - A central societal need in developed countries is the energy production with a low environmental impact. Thus ambitious energy programs have been initiated aiming at the establishment of renewable energies as a main contributor to the energy mix in the next decade. Like no other renewable energy, the offshore wind energy possesses a high potential and constitutes the main contributor to this aim. The development of large scale wind parks is one of the major challenges in the offshore industry today while the first wind parks of significant size and in considerable water depths are being built. In preparation for the next step, this thesis aims to contribute to the efficient and cost effective operation of wind parks. It specifically addresses the support of the inspection and maintenance activities of offshore wind turbines by the development of methods for the assessment and monitoring of support structures. The essential finding of this thesis is that the operation efficiency of wind turbine structures can be significantly enlarged by monitoring based assessment procedures. It is found that a substantial expected life-cycle benefit for the operation can be achieved by the conceptual integration of structural monitoring techniques in the structural reliability theory. The integration should be bidirectional in the sense that the generic design decisions for structural monitoring systems are based on a structural reliability assessment and that simultaneously a possible reduction of the uncertainty associated with the condition is utilized for the structural reliability assessment and thus for the inspection and maintenance planning. The thesis covers the issues of (I) the integration of monitoring data in the framework for structural reliability assessment of the Joint Committee on Structural Safety (JCSS), (II) the issue of the consistent determination of the measurement uncertainties utilizing all available information of the measurement process, (III) the issue of the application of monitoring techniques for structural integrity management and (IV) the establishment of a full probabilistic performance model basis for the support structure of an offshore wind turbine. To cover these issues the thesis comprises (1) the development of probabilistic structural, loading and limit state models, (2) a response surface algorithm for a multiple component reliability analysis, (3) a reliability analysis of an offshore wind turbine support structure applying the model basis, (4) a framework for the determination of measurement uncertainties utilizing process and observation data and (5) concepts for utilizing monitoring data in a structural reliability analysis as well as for the risk based inspection planning. The starting point of this thesis is the development of the model basis containing the models for the structural performance of a reference case, namely a support structure of an offshore wind turbine. The model basis comprises the structural, loading and probabilistic characterization of the ultimate, fatigue and the serviceability limit states and is derived considering the constitutive physical equations. The introduced models for the structural performance and loads account for design, production and execution information. A sensitivity study is performed on the basis of a non-linear coefficient of correlation. The process of establishing and analyzing these models contributes to an enhanced understanding of the performance of the structure and is documented in detail. The reliability analysis of an offshore wind turbine support structure builds upon the developed model basis. In order to facilitate the reliability analysis with such complex multiple component models, an adaptive response surface algorithm is developed. This algorithm utilizes clustered experimental designs in combination with an efficient augmentation scheme for these designs. The results of the reliability analyses comprise the system reliabilities and the probabilities of failure for the components in the individual limit states. With these results critical components are identified. A comparison with the target reliabilities specified in DIN EN 1990 (2002) shows that the target reliabilities are met. A novel contribution, as mentioned above, constitutes a new approach for the determination of measurement uncertainties in the context of the structural reliability theory. This approach builds upon two types of measurement uncertainties (as defined in the ISO/IEC Guide 98-3 (2008a)), namely the uncertainty based on a statistical analysis of observations and the uncertainty derived from a process equation describing physically the measurement process. Both types of measurement uncertainties are utilized for the derivation of a posterior measurement uncertainty by Bayesian updating. This facilitates the quantification of a measurement uncertainty using all available data of the measurement process. The measurement uncertainty models derived are analyzed through a sensitivity study and are discussed in detail resulting in an identification of the most relevant sources of measurement uncertainties. For the utilization of monitoring data in a structural reliability analysis the approach for the determination of measurement uncertainties data is applied. Monitoring data can be interpreted in two ways, namely as probabilistic loading model information and as probabilistic resistance model information, i.e. proof loading. For both ways the influence of the measurement uncertainties on the structural reliability is shown and how the specific modeling of monitoring data in a reliability analysis can result in a reduction of uncertainties and as a consequence in an increase of the reliability. The proof loading concept is developed further to account for probabilistic proof loading information, i.e. information subjected to measurement uncertainties. In conjunction with an alternative proof loading concept utilizing Bayesian updating techniques, a criterion to facilitate a consistent choice of the appropriate proof loading method is developed. The developed approaches and the findings are applied in a life-cycle cost-benefit analysis comprising the expected costs of failure, of inspection, of repair and of the monitoring system as well as its operation. Here, concepts for the design decision support of monitoring systems are introduced by formulating the life-cycle cost-benefit analysis as an optimization problem. On this basis, it can be determined which components should be monitored to achieve a life cycle benefit. Furthermore, an approach for the reduction of monitoring period is introduced. The most significant result of the cost-benefit analysis is that a substantial expected life-cycle benefit is achievable by the application of the developed concepts. KW - Structural condition assessment KW - Monitoring KW - Offshore wind turbine KW - Measurement uncertainty KW - Cost benefit analysis KW - Structural integrity management PY - 2012 DO - https://doi.org/10.3929/ethz-a-009753058 SN - 0257-6821 IS - 345 SP - 1 EP - 149 PB - vdf Hochschulverlag AG CY - Zollikon AN - OPUS4-28280 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 DO - 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 - GEN A1 - Thöns, Sebastian A1 - Faber, M.H. A1 - Rücker, Werner A1 - Rohrmann, Rolf ED - Martorell, S. ED - et al., T1 - Assessment and monitoring of reliability and robustness of offshore wind energy converters T2 - ESREL 2008 CY - Valencia, Spain DA - 2008-09-22 KW - Structural reliability KW - Robustness KW - Monitoring KW - Risk KW - Wind energy converter PY - 2008 SN - 978-0-415-48513-5 SP - 1567 EP - 1572 PB - Taylor & Francis CY - London, UK AN - OPUS4-18565 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -