Filtern
Erscheinungsjahr
Dokumenttyp
- Vortrag (35)
- Beitrag zu einem Tagungsband (30)
- Zeitschriftenartikel (23)
- Beitrag zu einem Sammelband (3)
- Buchkapitel (1)
- Corrigendum (1)
- Dissertation (1)
- Forschungsbericht (1)
Schlagworte
- Value of information (10)
- Structural reliability (7)
- Fatigue (5)
- Offshore wind turbines (5)
- Structural integrity management (5)
- Condition monitoring (4)
- Damage detection (4)
- Integrated monitoring system (4)
- Monitoring (4)
- Structural health monitoring (4)
- Wind turbine (4)
- Automated operational modal analysis (3)
- Data management (3)
- Integrated Monitoring System (3)
- Measurement uncertainty (3)
- Offshore wind (3)
- Offshore wind turbine (3)
- Resonance (3)
- Risk (3)
- Risk assessment (3)
- SHM (3)
- Structural assessment (3)
- Assessment (2)
- Bayesian updating (2)
- Cost benefit analysis (2)
- Damage Identification (2)
- Damage identification (2)
- Decision theory (2)
- Deterioration (2)
- Ermüdung (2)
- Finite element analysis (2)
- Fire (2)
- Inspection (2)
- Lebenszyklus (2)
- Life cycle (2)
- Limit values (2)
- Load Monitoring (2)
- Load monitoring (2)
- Messunsicherheit (2)
- Reliability (2)
- Rotor blades (2)
- Sommerfeld effect (2)
- Tragwerkszuverlässigkeit (2)
- Tunnel (2)
- Vibration (2)
- Wind power (2)
- Wind turbines (2)
- Bauwerkserhaltung/Sanierung - Maintenance and Repair (1)
- Bauwerksüberwachung (1)
- Bayes'sche Aktualisierung (1)
- Bayesian analysis (1)
- Bayesian probability (1)
- Bayesian updating of measurement uncertainties (1)
- Bayesian updating of stress ranges (1)
- Berechnung (1)
- Berechnungs- und Bemessungsverfahren (1)
- Bestandssicherung und Erhaltung (1)
- Bewertung (1)
- Blade (1)
- Bridge resistance model (1)
- Brücke (1)
- CFD (1)
- Cast steel tube connection (1)
- Comparative study (1)
- Consequence (1)
- Continuous dynamic monitoring (1)
- Cost (1)
- Cost-benefit analysis (1)
- Damage (1)
- Damage detection system (1)
- Damage detection systems (1)
- Damage detection uncertainty (1)
- Damage indicators (1)
- Daniels systems (1)
- Data analysis (1)
- Dauerhaftigkeit (1)
- Decision analysis (1)
- Decision optimality (1)
- Decision tree (1)
- Design verification (1)
- Deteriorating structures (1)
- Deutschland (1)
- Direct (1)
- Direkt (1)
- Dynamic Bayesian Network (1)
- Dynamic analysis (1)
- Dynamic loads (1)
- Echtzeit (1)
- Embedded FBG sensors (1)
- Embedded sensors (1)
- Entwurf und Konstruktion (1)
- Environmental/operational effects (1)
- Evacuation (1)
- FED (1)
- Failure (1)
- Failure analysis (1)
- Fatigue safety (1)
- Forschungsbericht (1)
- Fractional effective dose (1)
- Fracture mechanics (1)
- Gussknoten (1)
- Hängebrücke (1)
- Icing conditions (1)
- Indirect (1)
- Indirekt (1)
- Inspection planning (1)
- Integrity management (1)
- Konsequenz (1)
- Kontinuierlich (1)
- Kontrolle (1)
- Kosten-Nutzen-Analyse (1)
- Lebensdauerverlängerung (1)
- Levelized cost of energy (1)
- Life cycle cost (1)
- Life cycle extension (1)
- Life-cycle (1)
- Load transfer (1)
- Management der Tragwerksintegrität (1)
- Measurement hardware (1)
- Meerestechnik (1)
- Meerestechnik - Offshore engineering (1)
- Messung (1)
- Metamodel (1)
- Modal analysis (1)
- Modal properties (1)
- Model approach (1)
- Model basis (1)
- Modellansatz (1)
- Monitoring strategy (1)
- Monopile support structure (1)
- Neue Verfahren/Versuchstechnik (1)
- New Processes/Experimental Techniques (1)
- Novelty analysis (1)
- Offshore engineering (1)
- Offshore installations (1)
- Offshore-Windenergie (1)
- Operation (1)
- Operation management (1)
- OperationRisk (1)
- Optimierung (1)
- Optimisation (1)
- Orthotropic steel bridge deck (1)
- Orthotropic steel deck (1)
- Posterior fatigue reliability (1)
- Posterior utilities (1)
- Predictive maintenance (1)
- Pre‐construction proof loading (1)
- Pre‐posterior decision analysis (1)
- Principal Component Analysis (1)
- Probabilistic decision analysis (1)
- Probability (1)
- Probability od detection (1)
- Probability of damage indication (1)
- Prognose (1)
- Proof load testing (1)
- Proof loading (1)
- Prüfverfahren (1)
- Quality (1)
- Qualität (1)
- Quantification (1)
- Rechenmodell (1)
- Reconstruction of stress resultants (1)
- Reliability updating (1)
- Risikoanalyse (1)
- Risk analysis (1)
- Risk and decision analysis (1)
- Risk mitigation strategies (1)
- Robustness (1)
- Rotor blade (1)
- Rotors (1)
- Rskbased inspection (1)
- SHM information (1)
- Sachschaden (1)
- Safety (1)
- Schaden (1)
- Schadensindikatoren (1)
- Sensitivity (1)
- Sensitivity analysis (1)
- Service life performance (1)
- Shells (structures) (1)
- Significance and effectiveness (1)
- Smoke (1)
- Stahlbau (1)
- Stahlbau - Steel construction (1)
- Steel bridge deck (1)
- Steel construction (1)
- Stochastic subspace (1)
- Strain measurements (1)
- Strain measurements of wind turbine support structures (1)
- Structural Integrity and Risk Management (1)
- Structural condition assessment (1)
- Structural design optimization (1)
- Structural engineering (1)
- Structural health monitoring information model (1)
- Structural health monitoring systems arrangement strategy (1)
- Structural monitoring (1)
- Structural performance (1)
- Structural reliability and risks (1)
- Structural systems (1)
- Strukturspannungskonzept (1)
- Subset simulation (1)
- Support structure (1)
- Suspension bridge (1)
- System (1)
- Terrorist attacks (1)
- Test blade (1)
- Tower-nacelle system (1)
- Toxicity (1)
- Tragfähigkeit (1)
- Traglast (1)
- Ultimate capacity (1)
- Ultimate limit state (1)
- Uncertainty (1)
- Utility and decision theory (1)
- Value of Information (1)
- Value of action analysis (1)
- Value of information and action (1)
- Versagen (1)
- Wahrscheinlichkeit (1)
- Weld fatigue (1)
- Wind energy converter (1)
- Wind turbine support structure (1)
- Zustandsbewertung (1)
- Zuverlässigkeit (1)
Organisationseinheit der BAM
Paper des Monats
- ja (1)
Eingeladener Vortrag
- nein (35)
Fatigue and serviceability limit state model basis for assessment of offshore wind energy converters
(2012)
This paper develops the models for the structural performance of the loading and probabilistic characterization for the fatigue and the serviceability limit states for the support structure of offshore wind energy converters. These models and a sensitivity study are part of a risk based assessment and monitoring framework and will be applied for establishing the 'as designed and constructed' reliability as prior information for the assessment and the design of monitoring systems. The constitutive physical equations are introduced in combination with the fatigue and serviceability limit state requirements as the starting point for the development of the structural performance and loading models. With these models introduced in detail, several modeling aspects for both limit states are analyzed. This includes analyses of the influence on the hot spot stresses by applying a contact formulation for the pile guide brace connection and the application of a finite element formulation using solid elements. Further, the comparison of the natural frequencies of a discrete rotor model with a continuous rotor model is documented. To account for uncertainties associated with the structural and loading models, a probabilistic model is derived on the basis of literature review and measurement data from a prototype Multibrid M5000 support structure. The sensitivity study is based on the calculation of a nonlinear coefficient of correlation in conjunction with predetermined designs of experiments. This is conducted by a systematic analysis of the influence of the random variables on limit state responses and hence on the structural reliability. Integrating the analyses and sensitivity studies of the fatigue and serviceability limit state models developed in this paper as well as the ultimate limit state models in Thöns et al. ('Ultimate Limit State Model Basis for Assessment of Offshore Wind Energy Converters,' ASME J. Offshore Mech. Arct. Eng.), the model basis for the assessment is completed. The process of establishing and analyzing such a model basis contributes to a detailed understanding of the deterministic and probabilistic characteristics of the structure and provides valuable insights in regard to the significance of available data.
Dieser Artikel enthält aktuelle Forschungsergebnisse im Bereich des überwachungsgestützten Managements der Tragwerksintegrität. Das Management der Tragwerksintegrität hat zum Ziel, die Funktionalität eines Tragwerks während des gesamten Lebenszyklus durch Einhaltung der Zielzuverlässigkeiten sicherzustellen. Ausgehend von Forschungsergebnissen über die Charakteristik von Überwachungsverfahren und -daten im Rahmen von Zuverlässigkeitsanalysen, wird ein Ansatz vorgestellt, wie die erwarteten Kosten für das Management der Tragwerksintegrität durch Überwachungsverfahren optimiert werden können. Dazu wird eine Kosten-Nutzen-Analyse für den Lebenszyklus einer Gründungstruktur von Offshore-Windenergieanlagen durchgeführt. Im Rahmen der Bayes'schen Entscheidungstheorie werden durch eine Prä-posteriori-Entscheidungsanalyse die optimalen Entscheidungsparameter für den Entwurf eines Überwachungssystems bestimmt. Als Fallstudie wird ein Überwachungssystem für die Gründungsstruktur eines Multibrid-M5000-Prototyps konzipiert und die mögliche Reduktion der Risiken und erwarteten Betriebskosten quantifiziert. --------------------------------------------------------------------------------------------------------------------------------------------------------------------
This paper contains recent research results in the field of monitoring supported structural integrity management. The structural integrity management aims at ensuring the functioning of a structure throughout the life cycle by compliance with the target reliabilities. Building upon research results concerning the characteristics of monitoring techniques and data within the framework of reliability analyses, an approach is introduced for the optimisation of the expected structural integrity management costs by monitoring information. For this aim, a life cycle cost benefit analysis for offshore wind turbine support structures is formulated. The optimal monitoring decision parameters are then assessed utilizing the Bayesian pre-posterior decision theory. As a case study a monitoring system for a Multibrid M5000 offshore wind turbine prototype support structure is designed and possible reductions of the risks and expected costs are quantified.
This paper establishes the model basis regarding the ultimate limit state consisting of structural, loading, and probabilistic models of the support structure of offshore wind energy converters together with a sensitivity study. The model basis is part of a risk based assessment and monitoring framework and will be applied for establishing the 'as designed and constructed' reliability as prior information for the assessment and as a basis for designing a monitoring system. The model basis is derived considering the constitutive physical equations and the methodology of solving these which then in combination with the ultimate limit state requirements leads to the specific constitutive relations. As a result finite element models based on shell elements incorporating a structural and a loading model are introduced and described in detail. Applying these models the ultimate capacity of the support structure and the tripod structure are determined with a geometrically and materially nonlinear finite element analysis. The observed failure mechanisms are the basis for the definition of the ultimate limit state responses. A probabilistic model accounting for the uncertainties involved is derived on the basis of literature review and measurement data from a prototype Multibrid M5000 support structure. In combination with the developed structural and loading models, sensitivity analyses in regard to the responses are performed to enhance the understanding and to refine the developed models. To this end, as the developed models necessitate substantial numerical efforts for the probabilistic response analysis predetermined designs of numerical experiments are applied for the calculation of the sensitivities using the Spearman rank correlation coefficient. With this quantification of the sensitivity of the random variables on the responses including nonlinearity the refinement of the model is performed on a quantitative basis.
Prototypes of wind turbines of the megawatt dass are to be built and tested until 2008 within a German offshore wind energy test field in the North Sea (ALPHA VENTUS). To ensure a high operational reliability of offshore wind turbines with economically acceptable repair and maintenance efforts, comprehensive diagnosis and supervision concepts are required. Automatic monitoring Systems will be an essential part of such concepts. Because of the fact, that during Operation there will be static and dynamic interaction between the components ‘structure’, ‘machinery’ and ‘blades’ it is necessary to develop the monitoring techniques in an overall concept. These monitoring Systems are supposed to be applied for the design and testing as well as for the Operation and maintenance phases. In the paper the developed approaches for the measurement of actions and the condition monitoring of all components of an offshore wind energy plant will be shown.
Structural health monitoring of wind turbine blades by strain measurement and vibration analysis
(2011)
Wind turbine blades have to withstand a high number of load cycles in mostly hard weather conditions over 20 years. In a research project BAM and several partners have designed, evaluated and tested a condition monitoring system for all parts of a wind turbine. At a rotorblade with a length of 58 m fibre bragg grating sensors were applied for in-service strain measurement. Additionally a complex test rig was designed to enable real biaxial loading conditions at a representative test rotor blade to simulate the mechanical loading conditions in the lab. In this test blade with a length of 8 m also fibre bragg grating sensors were implemented to determine their influences for the structure and the condition monitoring system. Vibration measurements were carried out at different test phases. The results were compared with finite element strain and modal analysis.
Structural Health Monitoring (SHM) systems are designed for assisting owners and operators with information and forecasts concerning the fitness for purpose of structures and building systems. The benefit associated with the implementation of SHM may in some cases be intuitively anticipated or proven by past experiences but in general there appears to be no rational or systematic approach for assessing the value of SHM systems a-priory to their implementation. The present paper addresses the assessment of the value of SHM with basis in structural risk assessments and the Bayesian pre-posterior decision analysis. The quantification of the value of SHM builds upon the quantification of the value of information (VoI) or rather the benefit of monitoring. The suggested approach involves a probabilistic representation of the loads and environmental conditions acting on structures as well as their responses and performances over their life-cycle. In addition, the quality of monitoring and the performance of possible remedial actions triggered by monitoring results are modeled probabilistically.The consequences accounted for, in principle include all consequences associated with the performance of the structure over its life-cycle as well as the costs associated with monitoring and possible remedial actions. The suggested approach is illustrated through two case studies concerning the monitoring of welded details in steel structures subjected to fatigue loading. The case studies address the effect of the uncertainty associated with the performance of SHM on the value of SHM. Moreover, in order to illustrate the potential of the application of approach for monitoring of structural systems an optimal strategy for SHM is determined for a system comprised of three welded details.
The Influence of brittle Daniels system characteristics on the value of load monitoring information
(2016)
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.
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.
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.
Risk Assessment and Value of Action Analysis for Icing Conditions of Wind Turbines Close to Highways
(2019)
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.
Quantification of the posterior utilities of SHM campaigns on an orthotropic steel bridge deck
(2019)
This paper contains a quantification and decision theoretical optimization of the posterior utilities for several options for monitoring campaigns on the particular case of fatigue life predictions of an orthotropic steel deck. The monitoring campaigns are defined by varying monitoring durations and phases. The decision analysis is performed with real data from the Structural Health Monitoring (SHM) of the Great Belt Bridge (Denmark) which, among others, consist of measured strains, pavement temperatures and traffic intensities. The fatigue loading prediction model is based on regression models linking daily averaged pavement temperatures, daily aggregated heavy-traffic Counts and derived S-N fatigue damages, all of them derived from the outcomes of different monitoring campaigns. A probabilistic methodology is utilized to calculate the fatigue reliability profiles of selected instrumented welded joints. The posterior utilities of SHM campaigns are then quantified by considering the structural fatigue reliability, various monitoring campaigns and the corresponding cost-benefit models. The decisions of identifying the optimal monitoring campaign and of extending the service life or not in conjunction with monitoring results are modelled. The optimal monitoring campaign is identified - retrospectively - by maximizing the expected benefits and minimize risks in dependency of the monitoring duration and the monitoring associated costs. The results, despite relying on a number of simplistic assumptions, pave the way towards the use of pre-posterior decision support to optimise the design of monitoring campaigns for similar bridges, with an overall goal to proof the cost efficiency of SHM approaches to civil infrastructure management.
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.
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.
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.
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.
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.
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.
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.
Structural health monitoring systems have been widely implemented to provide real-time continuous data support and to ensure structural safety in the context of structural integrity management. However, the quantification of the potential benefits of structural health monitoring systems has not yet attracted widespread attention. At the same time, there is an urgent need to develop strategies, such as optimizing the monitoring period, monitoring variables, and other factors, to maximize the potential benefits of structural health monitoring systems. Considering the continuity of structural health monitoring information, a framework is developed in this article to support decision-making for structural Health monitoring systems arrangement in the context of structural integrity management, which integrates the concepts of value of information and risk-based inspection planning based on an approach which utilizes a conjugate prior probability distribution for updating of the probabilistic models of structural performances based on structural health Monitoring information. An example considering fatigue degradation of steel structures is investigated to illustrate the application of the proposed framework. The considered example shows that the choice of monitoring variables, the Monitoring period, and the monitoring quality may be consistently optimized by the application of the proposed framework and approach. Finally, discussions and conclusions are provided to clarify the potential benefits of the proposed Framework with a special view to practical applications of structural health monitoring systems.
Quantification of the posterior utilities of SHM campaigns on an orthotropic steel bridge deck
(2019)
This paper contains a quantification and decision theoretical optimization of the posterior utilities for several options for monitoring campaigns on the particular case of fatigue life predictions of an orthotropic steel deck. The monitoring campaigns are defined by varying monitoring durations and phases. The decision analysis is performed with real data from the Structural Health Monitoring (SHM) of the Great Belt Bridge (Denmark) which, among others, consist of measured strains, pavement temperatures and traffic intensities. The fatigue loading prediction model is based on regression models linking daily averaged pavement temperatures, daily aggregated heavy-traffic Counts and derived S-N fatigue damages, all of them derived from the outcomes of different monitoring campaigns. A probabilistic methodology is utilized to calculate the fatigue reliability profiles of selected instrumented welded joints. The posterior utilities of SHM campaigns are then quantified by considering the structural fatigue reliability, various monitoring campaigns and the corresponding cost-benefit models. The decisions of identifying the optimal monitoring campaign and of extending the service life or not in conjunction with monitoring results are modelled. The optimal monitoring campaign is identified - retrospectively - by maximizing the expected benefits and minimize risks in dependency of the monitoring duration and the monitoring associated costs. The results, despite relying on a number of simplistic assumptions, pave the way towards the use of pre-posterior decision support to optimise the design of monitoring campaigns for similar bridges, with an overall goal to proof the cost efficiency of SHM approaches to civil infrastructure management.
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
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.
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.
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.