Volume 3: Structures, Safety, and Reliability最新文献

{"title":"3D Printing Miniature Marine Structures Models for Structural Analysis Purpose: Is it Possible?","authors":"M. Gonzales, P. Kujala","doi":"10.1115/omae2019-95772","DOIUrl":"https://doi.org/10.1115/omae2019-95772","url":null,"abstract":"\u0000 In the last few years, additive manufacture techniques — also known as 3d printing — are gaining more applications in the maritime sector including the production of functional large ship components in compliance with demanded operational and quality standards. By contrast, 3d printing miniature models of marine structures with the aim to reproduce structural responses brings along a higher degree of complexity. On the one hand, miniature thin-walled structures entails different manufacturing challenges when compared with large-size ship components. On the other hand, modeling structural events that comprise extreme reduction scales (around 1:100), material deformation and fracture at high loading rates, among other aspects, require purpose-designed scaling laws to handle all these effects adequately. The aim of this work is to present a wide panorama in the development of miniature 3d printed marine structures aiming to model experimentally ship collision and grounding events in reduced scale. Some preliminary experimental tests in miniature marine structures are also presented.","PeriodicalId":314553,"journal":{"name":"Volume 3: Structures, Safety, and Reliability","volume":"355 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125638249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Review and Comparison of Collated Offshore Mooring Chain Fatigue Test Data","authors":"Gary H. Farrow, A. Potts, Eric N Jal, Nicholas D’Arcy Evans, A. Kilner","doi":"10.1115/omae2019-95875","DOIUrl":"https://doi.org/10.1115/omae2019-95875","url":null,"abstract":"\u0000 The first phase of the Chain FEARS (Finite Element Analysis of Residual Strength) Joint Industry Project (JIP) aimed to develop guidance for the determination of a rational discard criteria for mooring chains subject to severe pitting corrosion which, based on current code requirements, would otherwise require immediate removal and replacement. Critical to the ability to evaluate the residual fatigue life of a degraded chain, is to have an accurate estimate of the chain in its as-new condition, thereby providing a benchmark for any loss in fatigue life associated with severe corrosion or wear.\u0000 A large collection of fatigue test data was collated for comparison and to establish underlying trends in as-new mooring chain fatigue response, and a non-linear multi-axial Finite Element Analysis (FEA) fatigue assessment method was developed to correlate against available as-new chain link fatigue test data and underlying failure trends [1,2] as part of the JIP achieving this critical requirement.\u0000 This study sought through collation and review of available fatigue test data to:\u0000 • Identify relationships between chain fatigue performance and the key input parameters of chain type, grade and environmental conditions.\u0000 • Compare and validate the fatigue test data against the current Code formulations for chain fatigue endurance.\u0000 • Determine chain nominal stress S-N fatigue endurance curves against which to validate a numerical model developed as part of the Chain FEARS JIP for the assessment of as-new chain link fatigue endurance.\u0000 The collated fatigue data was separated into groups associated with offshore mooring chain type (i.e. stud and studless), grade (i.e. ORQ, R3, R4 and R5) and environmental conditions (i.e. free corrosion in seawater and in-air) for review.\u0000 Good correlation occurred between the two standard deviation lower bound of the mean curves and current Code formulation design curves. The mean curves of the collated fatigue test data were considered representative of the overall fatigue performance of chain links and as such formed a good basis for subsequent development and the validation of an FEA model for the assessment of chain fatigue endurance [1,2].","PeriodicalId":314553,"journal":{"name":"Volume 3: Structures, Safety, and Reliability","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121735728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A New Approach for Environmental Contour and Multivariate De-Clustering","authors":"Q. Derbanne, G. D. Hauteclocque","doi":"10.1115/omae2019-95993","DOIUrl":"https://doi.org/10.1115/omae2019-95993","url":null,"abstract":"\u0000 When the long term behaviour of a floating unit is assessed, the environmental contour concept is often applied together with IFORM (Inverse First Order Reliability Method). This approach avoids direct computation on all sea-states, which is computationally very demanding, and most often simply not feasible. Instead, only a few conditions (the contour) are assessed and results in an accurate estimate of the long term extreme. However, most of available methods to derive the contour require the knowledge of the joint distribution of the different random variables (waves, wind, current...), which is often difficult to derive accurately. In fact, some complex dependences exist and are attempted to be simplified in too few coefficients. Another limitation of current environmental contour is its difficulty to deal with the dependence issue. Indeed, extreme sea-states arise by groups (storms, hurricanes...) and are not independent. While de-clustering techniques exist and are quite straightforward in univariate problems, this becomes difficult when the number of dimension increases.\u0000 In an attempt to tackle those challenges, this paper presents a novel approach to derive IFORM contours. The method does not require any joint distribution and makes use of much more degrees of freedom to capture the dependence between variables. It also allows for an easy de-clustering. The approach is illustrated on two locations, using actual hindcast data of significant wave height and period; the resulting contours are compared to the ones obtained with more traditional methods.","PeriodicalId":314553,"journal":{"name":"Volume 3: Structures, Safety, and Reliability","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131475697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensitivity Analysis of a Bottom Fixed Offshore Wind Turbine Using the Environmental Contour Method","authors":"D. Barreto, A. Moghtadaei, M. Karimirad, A. Ortega","doi":"10.1115/OMAE2019-95390","DOIUrl":"https://doi.org/10.1115/OMAE2019-95390","url":null,"abstract":"\u0000 In the field of stochastic dynamics of marine structures, environmental conditions play a vital role. Considering wind and waves as random processes, determining the environmental parameters which correspond to an annual exceedance probability for a certain structural concept is of vital importance for the respective assessment of the loads and their effects. The accuracy in predicting the conditions, especially those corresponding to the sea, is of a great relevance when a probabilistic design is performed in order to ensure the structural integrity of an offshore wind turbine. In particular, models are not always completely perfect and accurate data is not always available. The Environmental Contour Method (ECM), which is based on the IFORM methodology, is one of the most popular methods in the offshore industry when determining the environmental conditions, for a given annual exceedance probability, is required. The ECM allows analysing proper sea states for operational and extreme conditions with lower computational efforts than the most accurate method (Full Long-Term Analysis). In the present study, effects of progressive variations (uncertainties) of the sea states parameters (i.e. significant wave height, spectral peak period) on the dynamic response of a Monopile Wind Turbine (NREL 5MW) are analysed. Two operative conditions are considered: rated wind and cut-out wind speed. In each case, the 50-year environmental contour (EC) is plotted for a site located in the North Sea. Some sea states are selected from the EC (base cases) and then derived cases with percentage variations are generated. All the cases are simulated in FAST (NREL) and the standard deviations of the time series are compared with its respective values of base cases. The results for the dynamic responses at mudline (e.g. overturning moments and shear forces) are presented as the most important parameters governing the design of the monopile. In this analysis, the wave height shows more influence on the response variation percentage than the peak period. This work shows the importance of accurately setting up the input parameters and their impact on the calculation of the dynamic responses.","PeriodicalId":314553,"journal":{"name":"Volume 3: Structures, Safety, and Reliability","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130500620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational Fatigue Assessment of Chains Working in Twisted Conditions","authors":"I. Pérez, Ø. Gabrielsen","doi":"10.1115/omae2019-96000","DOIUrl":"https://doi.org/10.1115/omae2019-96000","url":null,"abstract":"\u0000 Chains are extensively used in the Oil and Gas industry for mooring vessels or floating platforms, both for temporary and long-term moorings. Moreover, recently they found a new application in the mooring of floating wind turbines. The integrity of mooring systems is of great importance for both industries. Failure Records [1]–[2] indicate that fatigue of mooring chains is one of the main causes of failure, and therefore their lifetime prediction represents an important challenge for industry. Chains are intended to work under Tension Loading, however, anomalous loading modes such as Out-of-Plane Bending (OPB) or Twisting can appear. For example, OPB caught the attention of engineers after the Girassol incident; where it was identified as the main cause of failure of several chain links eight months after the installation [3]. Since this failure, OPB has attracted the attention of several research programs and multiple publications can be found in the literature (For example, [4]–[5]). Twist may occur during the installation of a chain or during service due to torque generated in the near-by elements of the mooring (for example wire cables). This paper presents a computational fatigue assessment of mooring chains working in twisted conditions. It is based on a two steps analysis: a mechanical and a fatigue analysis. The mechanical analysis accounts for the initial residual stress state of the chain after manufacturing and subsequent proof loading. The result is the stabilized cycle of the multiaxial stress field, which is obtained through an elastic-plastic three-dimensional Finite Element Analysis (FEA). Then, the fatigue analysis is performed to predict the failure location and determine the lifetime. The predicted failure location has shown good agreement with fatigue cracks found in recovered chain links in the North Sea after more than 15 years of service.","PeriodicalId":314553,"journal":{"name":"Volume 3: Structures, Safety, and Reliability","volume":"228 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133798668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-Term Extreme Response of a Straight Floating Bridge Across the Bjørnafjord","authors":"Finn-Idar Grøtta Giske, A. Fredriksen","doi":"10.1115/omae2019-95212","DOIUrl":"https://doi.org/10.1115/omae2019-95212","url":null,"abstract":"\u0000 In this paper, long-term extreme response analysis is performed for a straight floating bridge across the Bjørnafjord, using a recently developed inverse first-order reliability method (IFORM) approach. Full integration of the long-term extreme response formulation is also performed for comparison. Two different environmental models are estimated based on a scatter diagram of significant wave height and peak period for the given location. The IFORM method is seen to provide reasonable estimates of the long-term extreme response, at a significantly reduced computational effort.","PeriodicalId":314553,"journal":{"name":"Volume 3: Structures, Safety, and Reliability","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133437044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of VOS and ERA-Interim Wave Data","authors":"R. Vettor, C. Soares","doi":"10.1115/omae2019-95287","DOIUrl":"https://doi.org/10.1115/omae2019-95287","url":null,"abstract":"\u0000 Accuracy of Voluntary Observing Ship’s reports is evaluated by a one-to-one comparison with ERA-interim database, specifically considering significant wave height. A first screening allows to detect the most common and undeniable mistakes, as for instance clear errors in reporting the position of the vessel, and delete these observations. Moreover, previous literature is considered to remove systematic biases. Then each report is matched with the appropriate numerical data in terms of location and time, in order to evaluate the scattering of the data, to identify the outliers, and to further prune the database. The procedure allows not only to maintain a database clean from clearly wrong information, which can compromise the statistics, but also to recognize areas and conditions in which the mismatch between numerical data and observations is critical, eventually speculating on the motivations.","PeriodicalId":314553,"journal":{"name":"Volume 3: Structures, Safety, and Reliability","volume":" 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113946328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On Calculating the Crack Growth Within a Single Load-Dwell-Unload Cycle for Metal Structures","authors":"F. Wang, Xuezhong Zhang, Zhe Jiang, W. Cui","doi":"10.1115/omae2019-95327","DOIUrl":"https://doi.org/10.1115/omae2019-95327","url":null,"abstract":"\u0000 Some structures such as components of deep-sea submersibles, will endure cyclic loads with a period of dwell time at high stress level within each loading-unloading cycle. For components subjected to cyclic loads, fatigue life analysis is an important issue. Approaches based on fracture mechanics are reliable, in which choice of crack growth model plays an important role. The commonly-used crack growth rate model can make fatigue crack increment by cycle-by-cycle integration, which neglects the crack length change within a single cycle. Some researchers proposed the concept of crack growth rate model in small time domain to consider the crack growth within one load-unload cycle. However, during the dwell time, the crack increment can also be detected. In this paper, the model in small time domain will be extended to that for a single load-dwell-unload cycle. The model can be applied to calculate the life of metal structures under dwell-fatigue conditions.","PeriodicalId":314553,"journal":{"name":"Volume 3: Structures, Safety, and Reliability","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114303564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Extended Kalman Filtering for Estimating Drag and Inertia Coefficients for Slender Offshore Structures","authors":"Dhruv Bhagtani, N. Saha","doi":"10.1115/omae2019-96630","DOIUrl":"https://doi.org/10.1115/omae2019-96630","url":null,"abstract":"\u0000 System identification is used in location detection, target tracking, prediction in oil markets and so on. In this paper, the Kalman Filter (extended) technique is explored in monitoring the health of a jacket structure, in a stochastic excited wave environment. Hydrodynamic coefficients drag (CD) and inertia (CM), usually experimentally obtained, are important parameters to assess the force on a structure using the Morison’s equation. Usually these coefficients appearing in the force equation are un-known for majority of the slender offshore structures and are a priori obtained using some set of prototype experiments as these parameters depend on lot of factors (Keulegan-Carpenter number, roughness, dimensions and so on). Therefore, the recourse to parameter identification techniques based on Kalman filtering can be an alternative.\u0000 In this paper, the problem is analysed using Airy wave theory where a cylinder is assumed to be fixed at the seabed. Numerical analysis is done to create experimental conditions to observe the dynamic response of the system. These numerical results are then plagued with white noise to represent the observations from experiments. These measurements are subsequently used in identification of the drag and inertia coefficients for the cylinder. This is presently attempted using the Extended Kalman Filter technique.\u0000 With the use of this model the Extended Kalman Filter is shown to be able to identify time varying drag and inertia coefficients of the cylinder problem. For the present case, measurement sensors are placed for the measured force, along with the motions: velocity and acceleration. The above method can easily be implemented in jacket structures or similar offshore structures for attention due to increase in forces owing to marine growth.","PeriodicalId":314553,"journal":{"name":"Volume 3: Structures, Safety, and Reliability","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131962507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Motion and Load Prediction of Floating Platform in South China Sea Using Deep Learning and Prototype Monitoring Information","authors":"Ji Yao, Wenhua Wu, Ziqiang Zhao","doi":"10.1115/omae2019-95412","DOIUrl":"https://doi.org/10.1115/omae2019-95412","url":null,"abstract":"\u0000 The offshore floating platform shows the strong nonlinear characteristics subject to harsh ocean environmental conditions. It is of practical significance and engineering value to predict the marine environmental load and platform motion response by using the prototype monitoring information. Meanwhile, under the interaction of the high-frequency six degrees of freedom (DOF) movements of the platform.\u0000 Based on the long-term prototype monitoring data of a semi-submersible platform in the South China Sea, the present paper mainly studies the following two aspects:\u0000 1.The prediction of ocean environmental load considering time correlation is studied based on the method of long-short-term memory (LSTM) neural network with the combination of the field monitoring data. The comparison between predicted and measured results shows that the present prediction method has the high accuracy and low computation cost. Besides, this method can be extended to short-term predictions of other environmental loads.\u0000 2.The nonlinear mapping relationship between the ocean environment load and the floater motions is constructed based on the deep learning method. The simulated results indicated that the mapping relationship can be used to predict the six DOFs motions of the platform with high accuracy by using the forecasting prototype monitoring data and ocean weather information. Based on this research and the short-term prediction of environmental loads, we can do some studies on short-term prediction of floater motions in the future.","PeriodicalId":314553,"journal":{"name":"Volume 3: Structures, Safety, and Reliability","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134057572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}