TY - JOUR A1 - Long, Lijia A1 - Alcover, I. F. A1 - Thöns, Sebastian T1 - Utility analysis for SHM durations and service life extension of welds on steel bridge deck N2 - Optimization of the duration of Structural Health Monitoring (SHM) campaigns is rarely performed. This article provides a utility-based solution to posteriorly determine: i) optimal monitoring Durations and ii) the extension of the service life of the welds on a steel bridge deck. The approach is Illustrated with a case study focusing on remaining fatigue life estimation of the welds on the orthotropic steel deck of the Great Belt Bridge, in Denmark. The identification of the optimal monitoring duration and the decision about extending the service life of the welds are modelled by maximizing the expected benefits and minimizing the structural risks. The results are a parametric analysis, mainly on the effect of the target probability, benefit, cost of failure, cost of rehabilitation, cost of monitoring and Discount rate on the posterior utilities of monitoring strategies and the choice of service life considering the risk variability and the costs and benefits models. The results show that the decision on short-term monitoring, i.e., 1 week every six months, is overall the most valued SHM strategy. In addition, it is found that the target probability is the most sensitive parameter affecting the optimal SHM Durations and service life extension of the welds. KW - Fatigue KW - Monitoring strategy KW - Orthotropic steel deck KW - Structural health monitoring KW - Utility and decision theory PY - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-521719 SN - 1573-2479 VL - 18 IS - 4 SP - 492 EP - 504 PB - Taylor Francis Online AN - OPUS4-52171 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 - 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 - 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 -