For operations at sea it is important to have a good estimate of the current local sea state. Often, sea state information comes from wave buoys or weather forecasts. Sometimes wave radars are used. These sources are not always available or reliable. Being able to reliably use ship motions to estimate sea state characteristics reduces the dependency on external and/or expensive sources. In this paper, we present a method to estimate sea state characteristics from time series of 6-DOF ship motions using machine learning. The available data consists of ship motion and wave scanning radar measurements recorded for a period of two years on a frigate type vessel. The research focused on estimating the relative wave direction, since this is most difficult to estimate using traditional methods. Time series are well suited as input, since the phase differences between motion signals hold the information relevant for this case. This type of input data requires machine learning algorithms that can capture both the relation between the input channels and the time dependence. To this end, convolutional neural networks (CNN) and recurrent neural networks (RNN) are adopted in this study for multivariate time series regression. The results show that the estimation of the relative wave direction is acceptable, assuming that the data set is large enough and covers enough sea states. Investigating the chronological properties of the data set, it turned out that this is not yet the case. The paper will include discussions on how to interpret the results and how to treat temporal data in a more general sense.

Hydrodynamic wave loading on structures plays an important role in areas such as coastal protection, harbor design and offshore constructions (FPSO’s, mooring), and there is a need for its prediction up to a detailed level (max./min. pressures, duration of pressure peaks, shear stresses, etc.). In close cooperation with industry, long-year joint-industry projects are carried out to develop a numerical simulation method: the CFD method ComFLOW. The two major application areas are the prediction of extreme wave forces on offshore platforms and offloading vessels, and the prediction of impact forces on coastal protection structures. The paper will present a short overview of the method, some recent results and future plans.

To study extreme hydrodynamic wave impact in offshore and coastal engineering, the VOF-based CFD simulation tool ComFLOW is being developed. Recently, much attention has been paid to turbulence modeling, local grid refinement, wave propagation and absorbing boundary conditions. The turbulence model has to cope with coarse grids as used in industrial applications. Thereto a blend of a QR-model and a regularization model has been designed, in combination with a dedicated wall model. Local grid refinement is based on a semi-structured approach. Near refinement interfaces special discretization stencils have been designed. The computational domain is restricted to the close environment of the objects studied. To suppress unphysical reflections, special generating and absorbing boundary conditions have been designed. The combined performance of the new ingredients will be demonstrated with several applications. For validation, experiments have been carried out at MARIN.

Breaking waves have been studied for many decades and are still of interest as these waves contribute significantly to the dynamics and loading of offshore structures. In current MARIN research this awareness has led to the setup of an experiment to determine the kinematics of breaking waves using Particle Image Velocimetry (PIV). The purpose of the measurement campaign is to determine the evolution of the kinematics of breaking focussed waves. In addition to the PIV measurements in waves, small scale wave-in-deck impact load measurements on a fixed deck box were carried out in the same wave conditions. To investigate the link between wave kinematics and wave-in-deck impact loads, simplified loading models for estimating horizontal deck impact loads were applied and compared to the measured impact loads. In this paper, the comparison of the model test data to estimated loads is presented.

In this paper, the use of an absorbing boundary condition (ABC) is investigated for the numerical simulation of free surface water waves. An enhanced type of an ABC based on the first-and second-order Higdon boundary conditions is presented. The numerical implementation of the ABC using a staggered grid arrangement is explained in detail. Numerical examples are provided to demonstrate the performance of the proposed boundary conditions.