基于窄带随机过程理论和Hermite变换法,本文提出了一种预测船舶参数横摇极值响应的新方法.以C11集装箱船为例,预测了其随机参数横摇极值响应的均值.将该结果与基于Monte Carlo法的数值结果对比,误差小于1%,证明了本文方法的正确性.同时,本文方法使用20条时间历程样本的预测精度与Monte Carlo法使用10⁴条时间历程样本的预测精度相同,由此可以证明本文方法的高效性.本文还利用传统Gumbel模型对C11船参数横摇极值响应进行了预测.通过比较可以发现传统Gumbel模型的极值预测误差很大,证明传统Gumbel模型不适用于参数横摇这类非线性较强的运动极值预测.但是,即使利用新方法预测极值,也和模型试验结果之间存在一定的偏差.通过分析认为,这种预测误差是由于忽略了极大值之间的相关性导致的.

Based on the narrow-band stochastic processes theory and Hermite transform, this paper proposed a method to study the extreme dynamic response of the parametric roll of ships. Taking the C11 container ship as an example, the average extremum of the stochastic parametric roll of the ship was estimated. A comparison of the results of Monte Carlo simulation indicates that the estimation error is lower than 1%, which proves that the proposed method is valid. Meanwhile, the prediction accuracy of the proposed method in this paper by using 20 time history samples is the same as that of the Monte Carlo method by using 10⁴ time history samples, which proves the efficiency of the proposed method. Then, the conventional Gumbel model was used to estimate the extremum of the C11 parametric roll. A comparison of the results shows that the estimation error of the conventional Gumbel model is quite large, proving that the conventional Gumbel model is not appropriate to estimate the extreme responses of strong non-linear motions, such as the parametric roll of ships. However, even if the proposed method is used to predict extreme values, there is a certain deviation from the model test results. The analysis indicates that this prediction error is caused by ignoring the correlation between the maximum values.