Speaker
Description
In maritime engineering ocean waves often play an important role. The sea state generates dynamic loads on structures and floating bodies from which motion or stresses result. Often the ocean wave state is irregular and may be understood as chaotic or turbulent. As a consequence of the corresponding high-dimensional nature of the wave states under consideration, numerical simulation of the evolution of the sea state forms a considerable challenge. Moreover, identifying initial and boundary conditions, and reconciling them with the wave evolution, forms another task. In the present talk different approaches to the problem of wave identification and wave simulation will be presented. The approaches range from ideas anchored more in traditional numerical simulation, to ideas employing machine learning, including physics informed neural networks for envelope equations and potential flow. It is demonstrated, how the different approaches deal with differing efficiency and accuracy objectives, and how the turbulent ocean wave dynamics, even including rare rogue wave events, can be identified and mapped out.
