The Design And Integration Of Winds And Waves Database And The Study On Long-term Wave Height Statistical Approach

The marine environment is the basis for the seakeeping performance prediction of ship and marine structures at real sea, which requires a large number of reliable data of wind and wave. Therefore, the winds and waves database has an enormous significance on the design and operation of ship and marine structures.This paper has briefly introduced the tasks that have been done on the winds and waves database, analyzed user's current demand in details on this topic, and offered the whole integration frame. Based on the analysis and integration frame, Visual Basic (6.0) and Excel 2003 VBA programming languages are used to form the program of the winds and waves database. The integration process is divided into four modules: the visual function module, the data inquiring module, the data update module, and the interface module. It has achieved the visualizing function of winds and waves database, preliminarily completed the interface design between database and the long-term seakeeping prediction system, and improved the functions of other modules as well. Visual Basic (6.0) programming language is used to form the statistical program for the winds and waves database. Winds and waves data measured in East China Sea from 1997 to 2002, in South China Sea from 1997 to 2005,and hindcasted by numerical simulation from 2000 to 2006 are integrated into the database by using the statistical program. It has become a database with the sustainable development function, friendly interfaces, various kinds of reliable data, which is able to provide winds and waves data to satisfy the requirement of the long-term seakeeping performance prediction of ship and naval marine structures at real sea.At present, most of the functions used to describe long-term significant wave height distribution are derived from experience, which can bring unavoidable subjectivity into the results, because different results may be obtained due to different assumptions and fitting methods. In order to solve the problem, the maximum entropy probability density function (PDF) is derived from the maximum entropy principle without subjective assumption and performed to describe the long-term distribution of significant wave height in this paper. Meanwhile, the widely used parameterized model and its derivation steps in long-term significant wave height statistics are discussed in details. In order to test the accuracy of these two methods, the long-term winds and waves data measured by buoys in the East China Sea are applied to fit the significant wave height PDF. The PDFs of the above-mentioned two methods are compared with the observed data. The results indicate that the maximum entropy PDF is simple and the parameters are easy to be determined from the observed data. The value of parameter? in the maximum entropy PDF can demonstrate the complexity of the real sea state. Besides, the maximum PDF fits well at different wind speeds. The PDF derived from the parameterized model fits well with the observed data at lower wind speed, but the derivation may occur at higher wind speed.