Alternative approaches to develop environmental contours from metocean data

Manuel, Lance; Nguyen, Phong T. T.; Jarred, Canning,; Coe, Ryan G.; Eckert-Gallup, Aubrey Celia; Martin, Nevin

doi:10.1007/s40722-018-0123-0

Cited by 58 publications

(24 citation statements)

References 25 publications

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“…Note that the establishment of environmental contour relies on different distributional assumptions and the dependency of environmental variables, and the results obtained using different method may have demonstrable differences. 17…”

Section: Environmental Contour Approachmentioning

confidence: 99%

“…Another popular method to avoid a complex integral is to use the environmental contour approach, which is derived from the inverse first-order reliability method (IFORM). [12][13][14][15][16][17][18][19] A review on environmental contours for marine and coastal designs was presented by Ross et al 20 The environmental contour contained all environmental parameters with an exceeding probability related to a reliability index, b, and the design environmental parameters corresponded to the maximum structural response along the environmental contour line. [21][22][23][24] Velarde et al 25 applied the environmental contour method to conduct a probabilistic analysis of offshore wind turbines under extreme resonant responses.…”

Section: Introductionmentioning

confidence: 99%

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Long-term extreme response analysis for semi-submersible platform mooring systems

Zhao

Dong

2020

Proceedings of the Institution of Mechanical Engineers, Part M:

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The accurate assessment of long-term extreme responses of floating-structure mooring system designs is important because of small failure probabilities caused by long-term and complex ocean conditions. The most accurate assessment would involve considering all conceivable sea states in which each sea state is regarded as a stochastic process and performing nonlinear time-domain numerical simulations of mooring systems to estimate the extreme response from a long-term analysis. This procedure would be computationally intensive because of the numerous short-term sea states involved. Here, a more feasible approach to evaluate the long-term extreme response is presented through immediate integration combined with Monte Carlo simulations. A parameter fitting procedure of the short-term extreme response distribution under irregular wave conditions is employed to solve the long-term response integration. Case studies were conducted on a semi-submersible platform using environmental data measurements of the Gulf of Mexico and a joint distribution model of the environmental parameters was considered. This approach was observed to be effective and the results were compared with those of traditional methodologies (univariate extreme value design and environmental contour methods). The differences were reflected using a reliability analysis of mooring lines, which indicated that the design standards must be stricter when using long-term analysis.

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Section: Environmental Contour Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Long-term extreme response analysis for semi-submersible platform mooring systems

Zhao

Dong

2020

Proceedings of the Institution of Mechanical Engineers, Part M:

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“…Other approached for environmental contours exist, see e.g. [10,11,12,13,14,15,16,17] or the recent review in [18]. In this paper various approaches to environmental contours will be used, and the results from an approximate long-term analysis using such contours will be compared to an approximate long-term analysis based on a statistical response emulator.…”

Section: Introductionmentioning

confidence: 99%

Comparing different contour methods with response-based methods for extreme ship response analysis

et al. 2020

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Environmental contours are often applied in probabilistic structural reliability analysis to identify extreme environmental conditions that may give rise to extreme loads and responses. They facilitate approximate long term analysis of critical structural responses in situations where computationally heavy and time-consuming response calculations makes full long-term analysis infeasible. The environmental contour method identifies extreme environmental conditions that are expected to give rise to extreme structural response of marine structures. The extreme responses can then be estimated by performing response calculations for environmental conditions along the contours. Response-based analysis is an alternative, where extreme value analysis is performed on the actual response rather than on the environmental conditions. For complex structures, this is often not practical due to computationally heavy response calculations. However, by establishing statistical emulators of the response, using machine learning techniques, one may obtain long time-series of the structural response and use this to estimate extreme responses. In this paper, various contour methods will be compared to response-based estimation of extreme vertical bending moment for a tanker. A response emulator based on Gaussian processes regression with adaptive sampling has been established based on response calculations from a hydrodynamic model. Long timeseries of sea-state parameters such as significant wave height and wave period are used to construct Nyear environmental contours and the extreme N-year response is estimated from numerical calculations for identified sea states. At the same time, the response emulator is applied on the time series to provide long time-series of structural response, in this case vertical bending moment of a tanker. Extreme value analysis is then performed directly on the responses to estimate the N-year extreme response. The results from either method will then be compared, and it is possible to evaluate the accuracy of the environmental contour method in estimating the response. Moreover, different contour methods will be compared.

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“…In particular, the direct sampling contours will by definition always enclose a convex set, whereas the IFORM contours will tend to follow the scatter of the data more closely. Other approached for environmental contours exist, see, eg, previous studies . The most common applications of environmental contours are restricted to two‐dimensional problems and with only linear variables, although generalizations to higher dimensions are, in principle, straightforward .…”

Section: Introductionmentioning

confidence: 99%

Environmental contours for circular‐linear variables based on the direct sampling method

2019

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Environmental contours are often used in the design of engineering structures to identify extreme environmental conditions that may give rise to extreme loads and responses. The perhaps most common application of environmental contours is for wave climate variables such as significant wave height and wave period. However, for the design of wind energy installations, the joint distribution of wind speed and wind direction may be equally important. In this case, joint modelling of linear (wind speed) and circular (wind direction) variables are needed, and methods for establishing environmental contours for circular-linear variables will be required.In this paper, different ways of establishing environmental contours for circular-linear variables will be presented and applied to a joint distribution model for wind speed and wind direction.In particular, the direct sampling approach to environmental contours will be modified to the case where one of the variables is cyclic. In addition, contours based on exceedance planes in polar coordinates will be established, and circular-linear contours will also be calculated based on the inverse FORM (I-FORM) approach.

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Alternative approaches to develop environmental contours from metocean data

Cited by 58 publications

References 25 publications

Long-term extreme response analysis for semi-submersible platform mooring systems

Long-term extreme response analysis for semi-submersible platform mooring systems

Comparing different contour methods with response-based methods for extreme ship response analysis

Environmental contours for circular‐linear variables based on the direct sampling method

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