Extreme value prediction of the roll motion under random seas

ObjectiveIn this work, two stability failure models, i.e., the dead ship condition and parametric roll are selected in order to study and evaluate ship stability as well as safety at seas. MethodsSpecifically, roll motion equations are established for the dead ship condition and the parametric roll condition, respectively. Subsequently, these equations are coupled with the linear filter, and the roll responses time histories under time random seas are obtained by solving the coupled equations using the Runge Kutta method. The stochastic process X(t) is defined as the absolute value of the roll response, and the average conditional exceedance rate (ACER) method is employed to predict the extreme value distribution of X(t). ResultsThe results show that the ACER method can provide effective predictions of the extreme value distributions for the roll response under the dead ship condition and the parametric roll condition. The exceedance probability for the stochastic process X(t) at the critical level (e.g. the flooding angle), can be applied as an effective index to evaluate ship capsizing at seas. ConclusionExtreme value prediction of the roll motion by application of the ACER method could be an important reference to evaluate ship stability at seas.