Validation of ship manoeuvring models using metamodels

This paper describes how simplified auxiliary models—metamodels—can be used to create benchmarks for validating ship manoeuvring simulation models. A metamodel represents ship performance for a limited range of parameters, such as rudder angles and surge velocity. In contrast to traditional system identification methods, metamodels are identified from multiple trial recordings, each containing data on the ship’s inherent dynamics (similar for all trials) and random disturbances such as environmental effects and slightly different loading conditions. Thus, metamodels can be used to obtain these essential data, where simple averaging is not possible. In addition, metamodels are used to represent a ship’s behaviour and not to obtain physical insights into ship dynamics. The experimental trials used for the identification of metamodels can be found in in-service recorded data. After the metamodel is identified, it is used to simulate trials without substantial deviations from the ship state parameters used for the identification. Subsequently, the predictions of the metamodels are compared with the predictions of a tested manoeuvring simulation model. We present two case studies to demonstrate the application of metamodels for moderate turning motions of two ships.     

Comparison of wind and wave measurements and models in the Western Mediterranean Sea

We have hindcast the wind and wave conditions in the Mediterranean Sea for two one month periods. Four different meteorological models and three different wave models have been used. The results have been compared with satellite and buoy wind and wave observations.Several conclusions concerning both the instruments and the models have been derived. The quality of both wind and wave results has been assessed. Close to the coasts high resolution, nested wave models are required for sufficient reliability.A wave threshold analysis suggests a sufficient reliability only off the coast, with a substantial decrease for low wave heights.     

Modelling the long-term distribution of significant wave height with the Beta and Gamma models

The paper suggests modelling the long-term distribution of significant wave height with the Gamma, Beta of the first and second kind models. The three models are interrelated, flexible and cover the three different tail types of Extreme Value Theory. They can be used simultaneously as a means of assessing the uncertainty effects that result from choosing equally plausible models with different tail types. This procedure is intended for those applications that require the long-term distribution of significant wave height as input rather than the prediction of extreme values. The models are fitted to some significant wave data as an illustration. Details about maximum likelihood estimation are given in A.