Non-Stationary Estimation of Joint Design Criteria With a Multivariate Conditional Extremes Approach

Raghupathi, Laks; Randell, David; Ewans, Kevin; Jonathan, Philip

doi:10.1115/omae2016-54355

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…Other recent work (e.g. Raghupathi et al (2016b)) has outlined how the method can be extended to the conditional modelling of one variate (e.g. storm peak current speed) given extreme values of another (e.g.…”

Section: Discussionmentioning

confidence: 99%

Consistent Design Criteria for South China Sea With a Large-Scale Extreme Value Model

Raghupathi

Randell

Jonathan

et al. 2016

Day 4 Fri, March 25, 2016

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Existing metocean design criteria for offshore facilities in the South China Sea have been estimated using different data and procedures, some of which are at least partly ad hoc. As a result, it is probable that existing criteria are inconsistent, in the sense that assets designed to the same design codes have different realised levels of integrity. To address this concern in this paper, we apply a large-scale extreme value model adapted to parallel computing environment, applied to the recent high-resolution SEAFINE hindcast database. This not only ensures design criteria that are statistically and spatially consistent but is also faster by avoiding the need for repetitive site-specific analysis. We have to overcome several challenges before we can apply a large-scale extreme model on the SEAFINE database. These include identifying a spatially consistent set of storm peaks and validating the hindcast data with real measurements. We then estimate marginal return values for significant wave height for locations within a large spatial neighbourhood, accounting for spatial and storm directional variability of peaks over threshold. A quantile regression identifies the extreme value threshold, the rate of exceedance of which is described using a Poisson process. The size of threshold exceedances is described by a generalised Pareto model. The characteristics of the threshold, rate and size models are all non-stationary with respect to directional and spatial covariates, parameterised in terms of (multidimensional) penalised B-splines. Parameter estimation is computationally challenging, but a combination of efficient generalised linear array algorithms executed within a parallel computing environment enable maximum likelihood estimation of all models. Bootstrap resampling is used to estimate uncertainties of model parameters and return values. We thus estimate consistent marginal return values for significant wave height and their uncertainties, at all locations in the spatial neighbourhood. In addition, we quantify directional variability of return values across different return periods. We rigorously validate the proposed spatiodirectional model with that of a direction-only model by deriving model diagnostics for the same site and demonstrating equivalent goodness of fits. To our knowledge this is the first of a kind of application of large-scale estimation for the South China Sea. With this approach, design criteria for large spatial domains, non-stationary with respect to the appropriate environmental covariates, can be estimated efficiently, consistently and with quantified uncertainty.

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Section: Discussionmentioning

confidence: 99%

Consistent Design Criteria for South China Sea With a Large-Scale Extreme Value Model

Raghupathi

Randell

Jonathan

et al. 2016

Day 4 Fri, March 25, 2016

View full text Add to dashboard Cite

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“…Ewans [38], where an extended conditional model incorporating covariate effects was described and illustrated for joint modelling of storm peak significant wave height and peak period with storm direction as covariate at a northern North Sea location. Towe, Eastoe [39] [41], applied in the northern North Sea for current speed sconditional on significant wave height with wave and current direction as two covariates. The estimated omni-directional joint extreme value for current speeds was found to be significantly reduced compared to the corresponding marginal value.…”

Section: Parametersmentioning

confidence: 99%

Joint description of waves and currents applied in a simplified load case

2018

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In order to perform a more accurate analysis of marine structures, joint probability distributions of different metocean parameters have received an increasing interest during the last decade, facilitated by improved availability of reliable joint metocean data. The main objective of this article is twofold; first to establish a joint distribution of significant wave height and current speed and then to assess the possible conservatism in the Norwegian design standard by applying this joint distribution in a simplified load case. As there still seems to be no general consensus with regard to the approach of estimating the joint probability distributions of metocean parameters, a general overview of recent studies exploring different joint models for metocean parameters is first presented. Based on simulated current data and NORA10 wave data, a joint model for significant wave height and current speed at one location in the northern North Sea is presented. Since episodes of wind-generated inertial oscillations is the governing current conditions at this location, a conditional joint model with current speed conditional on significant wave height is suggested. A peak-overthreshold approach is selected and the significant wave height is found to be very well modelled by a 2-parameter Weibull distribution for significant wave height exceeding 8 m, while a log-normal distribution describes the current speed well. This model is used to Monte-Carlo simulate joint significant wave heights and current speeds for periods corresponding to the ultimate and accidental limit states (ULS and ALS), i.e. 100 and 10 000 years. The possible conservatism in the Norwegian design standard is assessed by a simplified case study. The results give a clear indication that the Norwegian design standard in not necessarily conservative, neither at ULS nor ALS level.

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Non-Stationary Estimation of Joint Design Criteria With a Multivariate Conditional Extremes Approach

Cited by 2 publications

References 12 publications

Consistent Design Criteria for South China Sea With a Large-Scale Extreme Value Model

Consistent Design Criteria for South China Sea With a Large-Scale Extreme Value Model

Joint description of waves and currents applied in a simplified load case

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