Probabilistic methods for estimation of the extreme value statistics of ship ice loads

Chai, Wei; Leira, Bernt J.; Næss, Arvid

doi:10.1016/j.coldregions.2017.11.012

Cited by 33 publications

(22 citation statements)

References 18 publications

(26 reference statements)

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“…Second order corrections to this approximation can be obtained, e.g., by the so-called SORM approximation. Generally, various types of Monte Carlo simulation techniques are also applied as a supplement to (or sometimes instead of) the approximation in Equation (5).…”

Section: Environmental Contour Methodsmentioning

confidence: 99%

“…Subsequently, the contact area and the crushing force will increase when the ship penetrates the ice feature. The ice sheet eventually deforms out of its plane, and the resulting bending stresses induce a flexural failure at a certain distance away from the region where crushing occurs [5]. The rubble can be broken by means of the kinetic and propulsive ship hull energy, and by the broken parts of the consolidated layer.…”

Section: Ship-ridge Interactionmentioning

confidence: 99%

“…These codes and rules are primarily based on experience and deterministic solutions, and they are attractive in connection with practical design due to their simplicity [4]. However, ship-ice loads are random by nature [5,6]. This randomness is due to the inherent variability of ice conditions (such as the physical ice characteristics including the mechanical properties) and also by the great span of ship-ice interaction processes [7].…”

Section: Introductionmentioning

confidence: 99%

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On Characteristics of Ice Ridges and Icebergs for Design of Ship Hulls in Polar Regions Based on Environmental Design Contours

2021

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Ice ridges and icebergs generally pose a major threat to both ships and offshore facilities that operate in Polar regions. In many cases these features will govern the structural design loads associated with the Ultimate Limit State (ULS) and the Accidental Limit State (ALS). In general, a large number of load cases must be considered in order to ascertain an adequate structural resistance. Alternatively, conservatively high values of the relevant design parameters can be applied, which implies cost penalties. Accordingly, it is natural to consider methods that can serve to reduce the number of relevant load cases. Based on relevant information about the statistical properties of the parameters that characterize ice ridges and icebergs, the most likely combinations of these parameters for design purposes are highly relevant. On this background, the so-called environmental contour method is applied. Probabilistic models of the key parameters that govern the ship and ice interaction process are introduced. Subsequently, the procedure referred to as inverse reliability methods (IFORM) is applied for identification of the environmental contour. Different forms (i.e., dimensions) of environmental contours are generated to reflect the characteristics of the interaction process. Furthermore, the effect of an increasing correlation between the basic parameters is studied. In addition, the increase of the design parameter values for increasing encounter frequencies is illustrated.

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Section: Environmental Contour Methodsmentioning

confidence: 99%

Section: Ship-ridge Interactionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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On Characteristics of Ice Ridges and Icebergs for Design of Ship Hulls in Polar Regions Based on Environmental Design Contours

2021

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“…For the analysis of nonstationary time series, the ACER method is also applicable [28]. The idea of the ACER is that a sequence of nonparametric distribution functions is constructing in order to approximate the distribution of the collected history of extreme values.…”

Section: Problem Statementmentioning

confidence: 99%

Risks Estimation Method by Clustered Extreme Data of Process Covariates

Tereshchenko

Shtangey

2020

RIC

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Context. This paper presents a method for solving the problem of detecting and taking into account the influence of various (external and/or internal) factors on extreme and risky values of the multivariate observed parameters (covariates) of technological and/or diagnostic processes. Taking into account external and internal influence factors on covariates, by analogy with critical process parameters, is a significant addition to the extreme values statistics and the estimations the influence of the variability of process's covariates on the expected losses, i.e. value at risk. Risk-oriented analysis is an actual tool for the data behavior investigation of the multivariate observations of process's parameters. Objective. To disclose a method for detecting and taking into account the factors influence on the distribution functions parameters of the observed extreme values of process's covariates and determine the influence of these distribution functions parameters on estimates of risks values. Method. The method consistently uses: the procedures of multivariate statistical cluster analysis, transformation the matrix of observed extreme values of process's covariates into data frame with factor variables, estimation the extremal index and distribution functions parameters of nonclustered and clustered the observed extreme data of covariates and estimation the risk values on the calculated values of distribution functions parameters. The proposed sequence of actions is aimed at implementing the information technology of statistical causal analysis of the influence of factors on the variability of process's covariates and their risk values due to the application of the clustering procedure for observed multivariate extreme values of covariates. The method is implementing the R-language packages software. Results. Clustering of the multivariate observed extreme values of process's covariates allows to identifying the influence of environmental (manufacturing) factors and estimates the covariates' risky values taking into account of this influence. Conclusions. The method is an information technology of statistical causal analysis of factors influence on the variability of process's covariates and theirs risk values due to the application of the clustering procedure of covariates' multivariate values. The prospect of further research is to improve the methods of causal multivariate statistical analysis of the various factors influence on the exogenous and endogenous parameters of manufacturing and other processes in order to reduce the variability of these parameters and, as a result, minimize the risks.

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“…It is challenging to define the ice conditions (or ice environment) that the ship is expected to encounter, since many parameters are required for such a description. The required parameters mainly include: level ice thickness, ice concentration, ice types (level ice, ice ridge, rubble field, iceberg) and ice age (first-year ice, multiyear ice) [3]. For ice properties, both physical and mechanical properties of the sea ice should be considered.…”

Section: Introductionmentioning

confidence: 99%

Statistics of thickness and strength of first-year ice along the Northern Sea Route

et al. 2020

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In this paper, statistics of ice thickness and ice strength of first-year sea ice along the Northern Sea Route (NSR) is studied to provide useful information for the design and operation of Arctic ships. Specifically, ice thickness, ice strength and other physical parameters of the sea ice are estimated. Four representative sites are selected to study the ice environment and ice strength in different sea areas along the NSR during the ice growth season. Besides that, a good knowledge of the co-variation relationships between these ice parameters in a particular region would promote the estimation of ice loads acting on structures located in this region. In this work, a novel probabilistic model is introduced to describe the probability distribution of the ice flexural strength. The co-variation relationships between ice thickness and ice strength are quantified in terms of correlation coefficients. The influence of air temperature on ice properties is also investigated and discussed.

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Probabilistic methods for estimation of the extreme value statistics of ship ice loads

Cited by 33 publications

References 18 publications

On Characteristics of Ice Ridges and Icebergs for Design of Ship Hulls in Polar Regions Based on Environmental Design Contours

On Characteristics of Ice Ridges and Icebergs for Design of Ship Hulls in Polar Regions Based on Environmental Design Contours

Risks Estimation Method by Clustered Extreme Data of Process Covariates

Statistics of thickness and strength of first-year ice along the Northern Sea Route

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