Ships navigating in ice-infested regions need strengthened hull to resist the loads arising from the interactions with ice. Correct estimation of the maximum ice loads a ship may encounter during its lifetime is of vital importance for the design of ship structures. Due to the stochastic nature of ice properties and interaction processes, probabilistic approaches are useful to make long-term estimations of local ice loads on the hull. The Event Maximum Method (EMM) is an existing probabilistic approach for the long-term estimation of ice loads on the hull. This paper aims to extend the current EMM, first by introducing a model for the intercept of the linear regression line on the abscissa in order to quantify this value. Moreover, ice concentration is considered in the extended method as the second ice condition parameter in addition to thickness. The proposed method is applied to the full-scale measurement of the ship S.A. Agulhas II using the data obtained from the 2018/19 Antarctic voyage. The obtained model is then validated against six-year measurement data from 2013 to 2019, which shows reasonable similarity.

在冰冻地区航行的船舶需要加强船体以抵抗与冰相互作用产生的载荷。正确估算船舶在其使用寿命期间可能遇到的最大冰载荷对于船舶结构设计至关重要。由于冰特性和相互作用过程的随机性，概率方法可用于对船体上的局部冰载荷进行长期估计。事件最大值法 (EMM) 是一种现有的概率方法，用于长期估计船体上的冰载荷。本文旨在扩展当前的 EMM，首先通过引入横坐标上线性回归线的截距模型来量化该值。此外，在扩展方法中，冰浓度被认为是除厚度之外的第二个冰条件参数。使用从 2018/19 南极航行获得的数据，将所提出的方法应用于 SA Agulhas II 船的全尺寸测量。然后将获得的模型与 2013 年至 2019 年的六年测量数据进行验证，显示出合理的相似性。