Now showing 1 - 10 of 21
  • Publication
    On the effectiveness and uncertainty of inspection methods for fatigue crack management
    Non-destructive testing (NDT) methods have been widely used for damage examination and structural maintenance, e.g. detecting and repairing fatigue cracks. In-service inspections help to increase fatigue reliability by providing new information for updating structural failure probability and making decisions on repair. However, these benefits are often compromised by uncertainties associated with inspection methods. Sometimes existing cracks may not be identified, and positive inspection indication may not exist. It is of great interest to consider the influence of inspection uncertainty in maintenance optimization because the benefits and costs of maintenance are affected by inspection decisions (inspection times and methods) which are subjected to inspection uncertainty. However, the influence of inspection uncertainty on maintenance optimization has not been explicitly and adequately covered in the literature. In this paper, the problem has been investigated by probabilistic modelling of the qualities of inspection methods via probability of detection (PoD) functions. A new PoD function has been proposed to characterize the inspection quality when inspection uncertainty is not considered. Optimum inspection decisions are derived with the objective of maximizing lifetime reliability index under two scenarios (considering and not considering inspection uncertainty). The effectiveness of a planned inspection is defined based on the max reliability indexes under the two scenarios. It is shown that the max lifetime reliability index generally decreases when inspection uncertainty is considered. However, inspection uncertainty may have little influence on the lifetime reliability index depending on the planned inspection time. The effectiveness of a planned inspection increases with the decrease of the mean detectable crack size.
      147
  • Publication
    Methodologies for Crack Initiation in Welded Joints Applied to Inspection Planning
    (World Academy of Science, Engineering and Technology, 2016-11-08) ; ;
    Over the past decades, crack propagation has been extensively studied by researchers around the word. The approach based on crack propagation models have been widely used in inspection planning. This approach has the advantage that it gives measurable fatigue damage accumulation in terms of crack propagation with time and thus crack propagation models can be updated with inspection results. However, a prerequisite for using crack propagation models in inspection planning is that parameters such as initial crack size, crack growth rate, geometry function, etc. are known.  Among those parameters, initial crack size, depending on welding quality, material and the environment, is associated with the most uncertainties because of sampling and measuring problems. Another prerequisite for using crack propagation models in inspection planning is that crack initiation period can be assumed to be negligible. Both prerequisites are challenged nowadays as manufacturing and welding techniques have been improved. Some high-quality welded joins have been proven free from detectable size of flaws and the crack initiation period can account for a large part of the whole fatigue life. This gives rise to big difficulty for inspection planning of high-quality welded joins, as there is no generally acceptable approach for modelling the whole fatigue process that includes crack initiation period. Compared to as-welded joints, reliable inspection planning is more crucial for high-quality welded joins, as they are generally designed to withstand a larger stress range. In addition, they may have shorter time for inspection as crack initiation time account for a large part of fatigue life, with a shorter crack propagation period to failure due to higher stress range. To address this problem for high-quality welded joints, a robust model accounting for the whole fatigue process needs to be developed. The core issue is how the crack initiation period can be modelled and added to the crack propagation time. To help identify this issue, this paper reviews treatment methods for crack initiation period and initial crack size in crack propagation models applied to inspection planning. Generally there are four approaches, by: 1) Neglecting the crack initiation period and fitting a probabilistic distribution for initial crack size based on statistical data, e.g. Weibull distribution or lognormal distribution; 2) Extrapolating the crack propagation stage to a very small fictitious initial crack size, so that the whole fatigue process can be modelled by crack propagation models; 3) Assuming a fixed detectable initial crack size and fitting a probabilistic distribution for crack initiation time based on specimen tests; 4) Modelling the crack initiation and propagation stage separately using small crack growth theories and Paris law or similar models. Conclusion is that in view of trade-off between accuracy and computation efforts, calibration of a small fictitious initial crack size to S-N curves is the most efficient approach.
      487
  • Publication
    TRUSS, a European Innovative Training Network Dealing with the Challenges of an Aging Infrastructure Network
    Inspections and maintenance of infrastructure are expensive. In some cases, overdue or insufficient maintenance/monitoring can lead to an unacceptable risk of collapse and to a tragic failure as the Morandi bridge in Genoa, Italy, on 14th August 2018. An accurate assessment of the safety of a structure is a difficult task due to uncertainties associated with the aging and response of the structure, with the operational and environmental loads, and with their interaction. During the period from 2015 to 2019, the project TRUSS (Training in Reducing Uncertainty in Structural Safety) ITN (Innovative Training Network), funded by the EU H2020 Marie Curie-Skłodowska Action (MSCA) programme, has worked towards improving the structural assessment of buildings, energy, marine, and transport infrastructure. Fourteen Early Stage Researchers (ESRs) have been recruited to carry out related research on new materials, testing methods, improved and more efficient modelling methods and management strategies, and sensor and algorithm development for Structural Health Monitoring (SHM) purposes. This research has been enhanced by an advanced program of scientific and professional training delivered via a collaboration between 6 Universities, 1 research institute and 11 companies from 5 European countries. The high proportion of companies participating in TRUSS ITN has ensured significant industry expertise and has introduced a diverse range of perspectives to the consortium on the activities necessary to do business in the structural safety sector.
      115
  • Publication
    Probabilistic decision basis and objectives for inspection planning and optimization
    (Taylor & Francis, 2018-10-31) ; ;
    Marine and offshore engineering has long been challenged with the problem of structural integrity management (SIM) for assets such as ships and offshore platforms due to the harsh marine environments, where cyclic loading and corrosion are persistent threats to structural integrity. SIM for such assets is further complicated by the very large number of welded plates and joints, for which condition surveys by inspections and structural health monitoring become a difficult and expensive task. Structural integrity of such assets is also influenced by uncertainties associated with materials, loading characteristics, fatigue degradation model and inspection method, which have to be accounted for. Therefore, managing these uncertainties and optimizing the inspection and repair activities are relevant to improvements in SIM. This paper addresses probabilistic inspection planning and optimization by comparative analysis for a typical fatigue-prone structural detail based on reliability, life cycle cost (LCC) and value of inspection information (VoI). With the objective of clarifying the differences between the theoretical basis and objectives for probabilistic inspection optimization, three maintenance strategies for the structural detail are proposed and studied. It is found that different optimal inspection times are obtained with the objectives of reliability maximization, LCC minimization and VoI maximization. Also, planned inspection and repair can help to achieve higher reliability with fewer repairs than repair without inspection (i.e. time-based replacement). If the cost of unit inspection and repair is not negligible compared with failure consequence, it is suggested to employ the optimization objective of life cycle cost minimization, which considers the costs of SIM. The paper proposes a simple approach for quantifying the VoI, based on life cycle cost analysis for the three maintenance strategies. It is concluded that the VoI is relevant to both the optimal maintenance decision with and without inspection.
      104
  • Publication
    Probabilistic maintenance optimization for fatigue-critical components with constraint in repair access and logistics
    There is a need to consider repair delay and incurred failure risk in maintenance optimization for some fatigue-critical structural details in marine and offshore structures. For example, in some cases, immediate repair may not be feasible due to weather, geographical location and/or technical restrictions. Also, immediate repair may be much more expensive than well-organized delayed repair. Moreover, detected cracks may sometimes be left unattended until more cracks are found and repaired together. This paper investigates a probabilistic maintenance optimization method allowing for repair delay and the incurred failure risk. The maintenance strategy considering repair delay is optimized based on uncertainty modeling, reliability and life-cycle cost analysis. Special features of the maintenance strategy and its impacts on fatigue reliability and life-cycle costs are discussed on an illustrative example. A method to quantify the risk incurred by repair delay is proposed. It is found that repair delay can result in a significant decrease in fatigue reliability if inspection is scheduled in the late stage of service life. The benefits of the maintenance strategy to fatigue reliability and life-cycle costs are very sensitive to the inspection method. The failure risk incurred by repair delay would be the predominant risk in the life cycle.
      111
  • Publication
    Uncertainty quantification and calibration of a modified fracture mechanics model for reliability-based inspection planning
    Efficient inspection and maintenance are important means to enhance fatigue reliability of engineering structures, but they can only be achieved efficiently with the aid of accurate pre-diction of fatigue crack initiation and growth until fracture. The influence of crack initiation on fatigue life has received a significant amount of attention in the literature, although its im-pact on the inspection plan is not generally addressed. Current practice in the prediction of fatigue life is the use of S-N models at the design stage and Fracture Mechanics (FM) models in service. On the one hand, S-N models are relatively easy to apply given that they directly relate fatigue stress amplitude to number of cycles of failure, however, they are difficult to extrapolate outside the test conditions employed to define the S-N curves. On the other hand, FM models like the Paris propagation law give measurable fatigue damage accumulation in terms of crack growth and have some ability to extrapolate results outside the test conditions, but they can only be a total fatigue life model if the initial crack size was known given that they do not address the crack initiation period. Furthermore, FM models generally introduce large uncertainties in parameters that are often difficult to measure such as initial crack size, crack growth rate, threshold value for stress intensity factor range, etc. This paper proposes a modified FM model that predicts the time to failure allowing for crack initiation period. The main novelty of the modified FM model is the calibration using S-N data (i.e., inclusive of crack initiation period) for an established criterion in fatigue life and reliability level. Sources of uncertainty associated to the model are quantified in probabilistic terms. The modified FM model can then be applied to reliability-based inspection planning. An illustrative example is performed on a typical detail of ship structure, where the optimum inspection plan derived from the proposed model is compared to recommendations by existing FM models. Results demonstrate to what extent is the optimum inspection plan influenced by the crack initiation period. The modified model is shown to be a reliable tool for both fatigue design and fatigue management of inspection and maintenance intervals. 
      302
  • Publication
    Bayesian maintenance decision optimisation based on computing the information value from condition inspections
    A challenge in marine and offshore engineering is structural integrity management (SIM) of assets such as ships, offshore structures, mooring systems, etc. Due to harsh marine environments, fatigue cracking and corrosion present persistent threats to structural integrity. SIM for such assets is complicated because of a very large number of rewelded plates and joints, for which condition inspections and maintenance are difficult and expensive tasks. Marine SIM needs to take into account uncertainty in material properties, loading characteristics, fatigue models, detection capacities of inspection methods, etc. Optimising inspection and maintenance strategies under uncertainty is therefore vital for effective SIM and cost reductions. This paper proposes a value of information (VoI) computation and Bayesian decision optimisation (BDO) approach to optimal maintenance planning of typical fatigue-prone structural systems under uncertainty. It is shown that the approach can yield optimal maintenance strategies reliably in various maintenance decision making problems or contexts, which are characterized by different cost ratios. It is also shown that there are decision making contexts where inspection information doesn’t add value, and condition based maintenance (CBM) is not cost-effective. The CBM strategy is optimal only in the decision making contexts where VoI > 0. The proposed approach overcomes the limitation of CBM strategy and highlights the importance of VoI computation (to confirm VoI > 0) before adopting inspections and CBM.
      175Scopus© Citations 2
  • Publication
    An integrated probabilistic approach for optimum maintenance of fatigue-critical structural components
    Inspection and maintenance are important means to validate or recover reliability of metallic structural systems, which usually degrade over time due to fatigue, corrosion and other mechanisms. These inspection and maintenance actions generally account for a large part of lifetime costs, which necessitate an efficient maintenance strategy to satisfy the requirements on reliability and costs. Most often, an optimum maintenance/repair crack size criterion is derived by probabilistic cost-benefit analysis, e.g. by minimization of expected lifetime costs, which are assessed based on cost models. This paper proposes an integrated approach to derive an optimum range for repair (crack size) criterion using both reliability-based and cost-based optimization. It is found that an optimum repair criterion exists which leads to the maximum lifetime fatigue reliability. A smaller repair criterion than the reliability-optimum do not lead to a higher lifetime fatigue reliability but leads to higher lifetime costs. Hence, a limit for repair criterion is defined by the reliability-optimum criterion, which can be obtained without cost models. The reliability-optimum criterion is found to be smaller than the cost-optimum criterion and thus an optimum range between the reliability-optimum and cost-optimum criterion is established.
      206Scopus© Citations 5
  • Publication
    TRUSS, a European innovative training network dealing with the challenges of an aging infrastructure network
    Inspections and maintenance of infrastructure are expensive. In some cases, overdue or insufficient maintenance/monitoring can lead to an unacceptable risk of collapse and to a tragic failure as the Morandi bridge in Genoa, Italy, on 14th August 2018. An accurate assessment of the safety of a structure is a difficult task due to uncertainties associated with the aging and response of the structure, with the operational and environmental loads, and with their interaction. During the period from 2015 to 2019, the project TRUSS (Training in Reducing Uncertainty in Structural Safety) ITN (Innovative Training Network), funded by the EU H2020 Marie Curie-Skłodowska Action (MSCA) programme, has worked towards improving the structural assessment of buildings, energy, marine, and transport infrastructure. Fourteen Early Stage Researchers (ESRs) have been recruited to carry out related research on new materials, testing methods, improved and more efficient modelling methods and management strategies, and sensor and algorithm development for Structural Health Monitoring (SHM) purposes. This research has been enhanced by an advanced program of scientific and professional training delivered via a collaboration between 6 Universities, 1 research institute and 11 companies from 5 European countries. The high proportion of companies participating in TRUSS ITN has ensured significant industry expertise and has introduced a diverse range of perspectives to the consortium on the activities necessary to do business in the structural safety sector.
      171
  • Publication
    Fatigue inspection and maintenance optimization: A comparison of information value, life cycle cost and reliability based approaches
    Fatigue cracks increase structural failure risk and timely maintenance is very important. Maintenance planning is often formulated as a probabilistic optimization problem, considering uncertainties in structural and load modelling, material properties, damage measurements, etc. A decision rule or strategy, e.g. condition based maintenance (CBM), needs to be set up, and then an optimal maintenance criterion or threshold is derived via solving the optimization problem. This paper develops a probabilistic maintenance optimization approach exploiting value of information (VoI) computation and Bayesian decision optimization. The VoI based approach explicitly quantifies added values from future inspections, and gives an optimal decision (or strategy) by direct modelling decision alternatives and evaluating their expected outcomes, rather than a pre-defined strategy. A comparative study on VoI, life cycle cost (LCC) and reliability based optimization approaches is conducted. It is shown that the VoI based approach takes all available maintenance strategies into account (both with and without involving inspections), and can reliably yield optimal maintenance strategies, whether the VoI is larger than or equal to zero. When the VoI is equal to zero, LCC and reliability based CBM optimization can lead to suboptimal maintenance strategies. The differences in the approaches are illustrated on fatigue-sensitive components in a marine structure.
      163Scopus© Citations 10