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Zou, Guang
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Zou, Guang
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Zou, Guang
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Now showing 1 - 10 of 21
- PublicationTRUSS, a European innovative training network dealing with the challenges of an aging infrastructure network(2018-11-12)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; 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.253 - PublicationMethodologies for Crack Initiation in Welded Joints Applied to Inspection Planning(World Academy of Science, Engineering and Technology, 2016-11)
; ; Crack initiation and propagation threatens structural integrity of welded joints and normally inspections are assigned based on crack propagation models. However, the approach based on crack propagation models may not be applicable for some high-quality welded joints, because the initial flaws in them may be so small that it may take long time for the flaws to develop into a detectable size. This raises a concern regarding the inspection planning of high-quality welded joins, as there is no generally acceptable approach for modeling the whole fatigue process that includes the crack initiation period. In order to address the 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; 2) Extrapolating the crack propagation stage to a very small fictitious initial crack size, so that the whole fatigue process can be modeled 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; and, 4) Modeling the crack initiation and propagation stage separately using small crack growth theories and Paris law or similar models. The 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.360 - PublicationDevelopment of probabilistic fracture mechanics method for fatigue life prediction based on EIFS conceptA problem with fracture mechanics (FM) based fatigue analysis is that reliable information on initial crack/flaw size is often unavailable. Also, FM method cannot be applied directly to welded joints with relatively small initial flaws and long crack initiation life. This paper proposes a novel probabilistic FM method based on the equivalent initial flaw size (EIFS) concept. The initial crack size is substituted with EIFS to take both the crack initiation and propagation life into account. Three methods are tested to obtain mean value of EIFS: calibrating to S-N curve, Kitagawa-Takahashi (KT) diagram and fitting to test data. The obtained EIFSs are evaluated by comparing the predicted fatigue lives and crack evolutions with S-N curve and test crack evolution data. The suggested procedure is to derive the mean value of EIFS from S-N curve and the coefficient of variation from KT diagram.
138 - PublicationOn the effectiveness and uncertainty of inspection methods for fatigue crack managementNon-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.
240 - PublicationUncertainty quantification and calibration of a modified fracture mechanics model for reliability-based inspection planningEfficient 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.
373 - PublicationProbabilistic maintenance optimization with respect to inspection quality(2018-09-12)
; ; Maintenance scheduling and optimization against fatigue failures is of great interest for marine and offshore engineering in terms of safety assurance, integrity management and cost control. The main challenge is to make risk-informed and optimal maintenance decisions taking into account uncertainties associated with material properties, fatigue loads, modelling, inspection and maintenance methods. While optimization of inspection times has been the objectives of many studies, the influence and optimization of inspection qualities is not very clear. This paper has applied probabilistic fracture mechanics and reliability/risk methods to optimization of inspection quality as well as inspection time and revealed the effect of inspection quality on lifetime fatigue reliability. It is found that there is a reliability-based optimum inspection quality for maintenance scheduling, which is different from the cost-based optimum one. Better inspection quality than the optimum one can lead to excessive maintenance, which occurs when the effect of maintenance is not good, and the inspection quality applied is very good. Excessive maintenance can lead to increase of both expected failure costs and maintenance costs, and thus should be avoided.159 - PublicationProbabilistic decision basis and objectives for inspection planning and optimizationMarine 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.
145 - PublicationTRUSS, a European Innovative Training Network Dealing with the Challenges of an Aging Infrastructure Network(NDT.net, 2019-04-01)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; 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.222 - PublicationBayesian maintenance decision optimisation based on computing the information value from condition inspectionsA 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.
272Scopus© Citations 3 - PublicationA probabilistic approach for joint optimization of fatigue design, inspection and maintenance(International Society of Offshore and Polar Engineers, 2018-06-10)
; ; ; This paper addresses challenges in fatigue management of marine structural assets with a holistically approach, by jointly considering fatigue design, inspection and maintenance decisions, whilst taking into account sources of uncertainties affecting life cycle performance. A risk-informed and holistic approach is proposed for jointly optimizing fatigue design, inspection and maintenance based on the same fatigue deterioration model. The optimization parameters are fatigue design factor (FDF) and inspection intervals, while the objective is to minimize expected life cycle costs (LCC). The framework is to guide design process as well as to formulate optimal maintenance strategies. The proposed approach is exemplified for the marine industry through a fatigue-prone detail in a ship structure to obtain the life cycle optimal management solution that achieves a best compromise between structural safety and life cycle costs.196
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