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

本课题探讨了用一种新的波浪随机模型重建长期预报基本算法的概率问题。该模型是a.a.a thanassoulis等人提出的计算海浪长期统计量的合理长期随机模型，在将波浪气候视为随机模型的相同框架下，研究了海浪中船舶响应的长期统计预测算法。并结合一些数据格式存在差异的长波频率数据进行了改进。同时，本课题提出了一种格式差异较大的波浪统计数据，特别是波浪数据采集周期差异较大的波浪统计数据的简单组合方法，明确了其算法。并与参考长期预测结果进行了比较，结果表明，基于新随机模型方法的波浪资料简单组合方法可以获得更可靠的长期估计。对几种波浪数据组合模式进行了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）的长期预测，并对算法的重建进行了进一步的研究。

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.