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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.
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.
This paper addresses the quantification of the value of damage detection system and algorithm information on the basis of Value of Information (VoI) analysis to enhance the benefit of damage detection information by providing the basis for its optimization before it is performed and implemented. The approach of the quantification the value of damage detection information builds upon the Bayesian decision theory facilitating the utilization of damage detection performance models, which describe the information and its precision on structural system level, facilitating actions to ensure the structural integrity and facilitating to describe the structural system performance and its functionality throughout the service life. The structural system performance is described with its functionality, its deterioration and its behavior under extreme loading. The structural system reliability given the damage detection information is determined utilizing Bayesian updating. The damage detection performance is described with the probability of indication for different component and system damage states taking into account type 1 and type 2 errors. The value of damage detection information is then calculated as the difference between the expected benefits and risks utilizing the damage detection information or not. With an application example of the developed approach based on a deteriorating Pratt truss system, the value of damage detection information is determined,demonstrating the potential of risk reduction and expected cost reduction.
As more offshore wind parks are commissioned, the focus will inevitably shift from a planning, construction, and warranty focus to an operation, maintenance, and investment payback focus. In this latter case, both short-term risks associated with wind turbine component assemblies, and long-term risks related to integrity of the support structure, are highly important. This research focuses on the role of condition monitoring to lower costs and risks associated with short-term reliability and long-term asset integrity. This enables comparative estimates of the life cycle costs and reduction in uncertainty, both of which are of value to investors.
Das Bauwerk einer Windenergieanlage dient der Sicherstellung der Energieproduktion. Eine entsprechende Zuverlässigkeit der Struktur und deren permanente Bewertung und Unterhaltung ist dazu notwendig. In diesem Beitrag werden Möglichkeiten der Bewertung des für die Struktur wichtigen Schädigungsmechanismus Ermüdung sowie dessen Überwachung in Zusammenhang mit Schädigungsindikatoren aufgezeigt. Dabei wird auf strukturmechanische, werkstoffmechanische und probabilistische Modelle sowie auf Messdaten eines Prototyps einer OWEA zurückgegriffen. Ausgehend von der gesamtdynamischen Berechnung wird die Zuverlässigkeit gemäß der Auslegung für den Schädigungsmechanismus Ermüdung durch ein Wöhlerlinienmodell berechnet. Damit werden ermüdungssensible Komponenten der Struktur identifiziert. Schädigungsindikatoren zur Überwachung der Ermüdungsfestigkeit werden auf Grundlage schädigungs-äquivalenter Dehnungen vorgestellt.
Fatigue assessment of support structures for offshore wind energy converters.
The structure of wind energy converters secures a reliable energy production. Hence an adequate reliability of the structure and additionally permanent assessment and maintenance is required. Within this paper methods for the assessment of the important damage mechanism fatigue in combination with monitoring of the fatigue reliability utilizing damage indicators are proposed. These methods comprise structural system, material degradation and probabilistic models as well as monitoring data of an offshore wind energy converter prototype. The structural reliability of the structure as designed is calculated based on an overall dynamic analysis using a SN-approach. Herewith fatigue sensitive components are identified. Damage indicators for monitoring the fatigue reliability based on damage equivalent strains are presented.