Formulation of Ice Resistance in Level Ice Using Double-Plates Superposition

Abstract

The estimation of ship resistance in ice is a fundamental area of research and poses a substantial challenge for the design and safe use of ships in ice-covered waters. In order to estimate the ice resistance with greater reliability, we develop in this paper an improved Lindqvist formulation for the estimation of bending resistance in level ice based on the superposition of double-plates. In the developed method, an approximate model of an ice sheet is firstly presented by idealizing ice sheeta as the combination of a semi-infinite elastic plate and an infinite one resting on an elastic foundation. The Mohr–Coulomb criterion is then introduced to determine the ice sheet’s failure. Finally, an improved Lindqvist formulation for estimation of ice resistance is proposed. The accuracy of the developed formulation is validated using full-scale test data of the ship KV Svalbard in Norway, testing the model as well as the numerical method. The effect of ice thickness, stem angle and breadth of bow on ship resistance is further investigated by means of the developed formulation.

A Critical Review of Constitutive Models Applied to Ice-Crushing Simulations

“…Their loci are illustrated in Figure 4. Examples of applications of these models in ice-crushing simulations are references [16][17][18][19] for M-C and [19][20][21][22][23] for D-P. The M-C criterion can be expressed by…”

On risk management of shipping system in ice-covered waters: Review, analysis and toolbox based on an eight-year polar project

“…The models can be categorized based on their scenario features into e.g. models on global ice loas in level ice (Tan et al, 2014;Xuan et al, 2021;Li et al, 2020;Li et al, 2020b;Ni et al, 2020) as well as escort in level ice (Liu and Ji, 2021), ice resistance in pack and thin ice (Zong and Zhou, 2019), ship resistance in open-water ice channel (Huang et al, 2021), narrow ice channel (Sazonov and Dobrodeev, 2021;Li et al, 2021) as well as in restricted brash ice channel (Zhang et al, 2022;Luo et al, 2020;Xie et al, 2022), ship resistance in unconsolidated ridges (Gong et al, 2019), resistance in ice floes (Huang et al, 2020(Huang et al, , 2021b, broken ice pieces . In addition, Kim et al (2020) and Sun et al (2022) applied machine learning method to estimate ice resistance based on model test data, while Milaković et al (2020) established machine learning model based on simulation data.…”