Research for a New Stochastic Long-term Wave Model and it's Application

本研究项目探讨了利用一种新的海浪随机模型重建长期预报的基本算法的可能性。该模型是G.A.Athan assoulis等人提出的用于计算海浪长期统计量的合理的长期随机模型。在将波浪气候视为随机模型的相同框架下，研究了船舶在海浪中响应的长期统计预报算法。并对其进行了改进，以便使用一些数据格式有一定差异的长期波频数据的组合。同时，本课题通过对不同格式的海浪数据，特别是海浪数据采集周期的不同，提出了一种简单的海浪统计数据组合方法，使其算法更加清晰。并与长期预报结果进行了比较，结果表明，基于新的随机模型方法的波浪数据组合方法可以得到更可靠的长期预报结果，对波浪载荷和某些船舶响应(螺旋桨运动、甲板湿度、船舶加速度等)进行长期预报。对几种波形数据的组合方式进行了计算，并对该算法的进一步研究进行了讨论。

This research project discussed the probability on reconstruction of the essential algorithm of the long-term prediction by using a new wave stochastic model. The model is a rational long-term stochastic model for calculating the long-term statistics of sea waves which was proposed by G.A.Athanassoulis et al.On the basis of the same framework of treating the wave climate as a stochastic model, the algorithm for the long-term statistical prediction of ship responses in ocean waves was examined. And it was also improved for purpose of using the combination of some long-term wave frequency data that had been presented with some differences in data format. Meanwhile this project made its algorithm clearly by a proposed simple combination method of wave statistical data with some differences in format, especially the differences in wave data collecting period. And then comparing with reference to the long-term prediction results, it shows that it is possible to obtain more reliable long-term estimates by such a simple combination method for wave data, which based on the methodology of new stochastic model.The long-term predictions of wave loads and some ship responses (propeller racing, deck wetness, ship accelerations etc.) was executed for a few patterns of combination of wave data, and further investigations for reconstruction of the algorithm was discussed.