Development of environmental contours for first-year ice ridge statistics

Chai, Wei; Leira, Bernt J.; Næss, Arvid; Høyland, Knut V.; Ehlers, Sören

doi:10.1016/j.strusafe.2020.101996

Cited by 5 publications

(7 citation statements)

References 47 publications

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“…The resulting values of the two parameters are found to be 2.97 (shape) and 0.54 (scale) based on application of the moment estimators. Fitting of a Gamma distribution to the data is illustrated in Figure 5 [39].…”

Section: Statistical Models For Key Parameters Associated With Ice Ridgesmentioning

confidence: 99%

“…where the scale parameter α and the shape parameter β are determined as 0.582 and 2.090, respectively, by means of regression estimators as implemented in a probability paper. A fitted Weibull density function (PDF) for the flexural strength of first-year sea ice in the Arctic is shown in Figure 6 [39].…”

Section: Statistical Models For Key Parameters Associated With Ice Ridgesmentioning

confidence: 99%

“…The fitted lognormal density function and histograms of the measured data are shown in Figure 7 [39]. It should be noted that the present probabilistic model for the crushing strength is based on the measured samples from the Barents Sea and Svalbard regions.…”

Section: Statistical Models For Key Parameters Associated With Ice Ridgesmentioning

confidence: 99%

“…Two specific examples of three-parameter combinations are (i) layer thickness/crushing strength/flexural strength and (ii) layer thickness/keel draft/flexural strength. Both of these cases are considered in [39]. Here, only the first alternative is addressed.…”

Section: Three-dimensional Contour Surfacesmentioning

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

Self Cite

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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: Statistical Models For Key Parameters Associated With Ice Ridgesmentioning

confidence: 99%

Section: Statistical Models For Key Parameters Associated With Ice Ridgesmentioning

confidence: 99%

Section: Statistical Models For Key Parameters Associated With Ice Ridgesmentioning

confidence: 99%

Section: Three-dimensional Contour Surfacesmentioning

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

Self Cite

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“…By proposing a new method of numerical simulation, the damage of sea ice to propagation was analyzed in [19]. Chai provided a reference for ship structure design through statistics of the characteristics of on year ice in Arctic waters [20,21]. Such studies focus on the impact of the interaction between sea ice and ship's structure, leading to ship-ice accidents.…”

Section: Introductionmentioning

confidence: 99%

Risk Reasoning from Factor Correlation of Maritime Traffic under Arctic Sea Ice Status Association with a Bayesian Belief Network

Gao

et al. 2020

Sustainability

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Sustainable growth should not only be beneficial to the shipping industry in the future, but is also an urgent need to respond to resource and environmental crises and strengthen shipping governance. Maritime traffic in Arctic waters is prone to encounter dangerous ice conditions, and it is essential to study the mechanism of ice collision risk formation in relation to ice conditions. Taking the ship-ice collision risk in Arctic waters as the research object, we propose a dynamic assessment model of ship-ice collision risk under sea ice status dynamic association (SDA) effect. By constructing the standard paradigm of risk factor dynamic association (DA) effect, taking SDA as the key association factor. Combing with other risk factors that affect ship-ice collision accidents, the coupling relationship between risk factors were analyzed. Then, using the Bayesian network method to build a ship-ice collision accident dynamic risk assessment model and combing with the ice monitoring data in summer Arctic waters, we screen five ships’ position information on the trans-Arctic route in August. The risk behavior of ship-ice collision accidents on the selected route under SDA is analyzed by model simulation. The research reveal that the degree of SDA is a key related factor for the serious ice condition and the possibility of human error during ship’s navigation, which significantly affects the ship-ice collision risk. The traffic in Arctic waters requires extra vigilance of the SDA effect from no ice threat to ice threat, and continuous ice threat. According to the ship-ice collision risk analysis under the SDA effect and without SDA effect, the difference in risk reasoning results on the five stations of the selected route are 32.69%, −32.33%, −27.64%, −10.26%, and −30.13% respectively. The DA effect can optimize ship-ice collision risk inference problem in Arctic waters.

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A simplified calculation method of ice–structure–water dynamic interaction under earthquake action

Huang¹,

Huang

2021

Extreme Mechanics Letters

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Development of environmental contours for first-year ice ridge statistics

Cited by 5 publications

References 47 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

Risk Reasoning from Factor Correlation of Maritime Traffic under Arctic Sea Ice Status Association with a Bayesian Belief Network

A simplified calculation method of ice–structure–water dynamic interaction under earthquake action

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