Wave spectrum estimation conditioned on machine learning-based output using the wave buoy analogy

In this work, a hybrid approach for wave spectrum estimation is proposed. Fundamentally, the approach is based on the wave buoy analogy, processing ship response measurements, via a framework combining machine learning and a physics-based method dependent on available transfer functions. Specifically, a non-parametric (Bayesian) estimate is obtained of the directional wave spectrum conditioned on integral wave parameters established by a convolutional neural network. The developed method is assessed in a case study considering about two years of data obtained from an in-service container ship. The method produces good results, significantly improved when compared to the initial estimate made without constraints.     

Sea trials of Sigma wave energy converter – slacking and snapping of TLP mooring lines

Sigma Energy has performed its foremost prototype tests of scaled wave energy converter in a real sea environment. The prototype was a point absorber with a cylindrical buoy, a mechanical power take-off system with a counterweight, moored to the seabed as a tension leg platform (TLP) with three equal tendons. In these extensive experiments, numerous device characteristics were measured and analysed. The present paper focuses on the dynamic forces in the mooring lines, and some unexpected and rare data obtained. It is well known that TLP tendons are prone to a brief loss of tension (the slacking) and that, after such events, high snapping forces of short duration can arise. Partly by intention, and partly due to underestimation of the dynamical forces, several such slacking-snapping incidents were recorded during the experiments. In some severe storms, the snapping forces were up to six times higher than the tendon pretension. The paper presents several recordings of dynamic forces and platform motion during these critical events. It analysis them, and gives a typical scenario under which they occur. It gives also some theoretical explanations, and numerical predictions of dynamical tendon forces, with their comparison to the experimental results.     

Hydrodynamic modelling of a multi-body wave energy converter using the Moving Frame Method

Significant wave energy conversion may be achieved with multiple floats with several modes of motion combining constructively to generate power. With the M4 system, power take off is at hinges to absorb resulting pitch motions. Complexity increases with number of floats and conventional vectorial multi-body dynamics may be conveniently replaced by the recently formulated moving frame method based on the calculus of variations to avoid free-body diagrams and joint reaction forces. Furthermore by utilising group theory to gather spatial rotations and angular velocities in a common structure, the obtained notation is general and straight-forward to apply for single and multi-body systems. This paper lays the foundations for incorporating hydrodynamic forces into the moving frame method. The method is applied to 3, 6 and 8 float cases in regular and irregular waves with results compared to the vectorial method and experimental measurements, showing close agreement. It is suggested that this is a more natural and general approach for complex multi-body, multi-hinge hydrodynamics systems.     

Required test durations for converged short-term wave and impact extreme value statistics — Part 1: Ferry dataset

For the design of maritime structures in waves, the extreme values of responses such as motions and wave impact loads are required. Waves and wave-induced responses are stochastic, so such responses should always be related to a probability. This information is not easy to obtain for strongly non-linear responses such as wave impact forces. Usually class rules or direct assessment via experiments or numerical simulations are applied to obtain extreme values for design. This brings up questions related to the convergence of extreme values: how long do we need to test in order to obtain converged statistics for the target duration? Or, vice versa: given testing data, what is the uncertainty of the associated statistics? Often the test or simulation duration is cut up in ‘seeds’ or ‘realisations’, with an exposure duration of one or three hours based on the typical duration of a steady environmental condition at sea, or the time that a ship sails a single course. The required number of seeds for converged results depends on the type of structure and response, the exposure duration, and the desired probability level. The present study provides guidelines for the convergence of most probable maximum (MPM) wave crest heights and MPM green water wave impact forces on a ferry. Long duration experiments were done to gain insight into the required number of seeds, and the effect of fitting. The present paper presents part 1 of this study; part 2 [1] presents similar results for wave-in-deck loads on a stationary deck box.     

Required test durations for converged short-term wave and impact extreme value statistics–Part 2: Deck box dataset

In the assessment of wave-in-deck loads for new and existing maritime structures typically model tests are carried out. To determine the most critical conditions and measure sufficient impact loads, a range of sea states and various seeds (realisations) for each sea state are tested. Based on these measurements, probability distributions can be derived and design loads determined. In air gap model testing usually only few, if any, impact loads occur per 3-hour seed. This can make it challenging to derive reliable probability distributions of the measured loads, especially when only a few seeds are generated. In addition wave impact forces, such as greenwater loading, slamming, or air gap impacts are typically strongly non-linear, resulting in a large variability of the measured loads. This results in the following questions: How many impacts are needed to derive a reliable distribution? How is the repeatability of individual events affecting the overall distribution? To answer these questions wave-in-deck model tests were carried out in 100 x 3-hour realisations of a 10,000 year North Sea sea state. The resulting probability distributions of the undisturbed wave measurements as well as the measured wave-in-deck loads are presented in this paper with focus on deriving the number of seeds and exposure durations required for a reliable estimate of design loads.The presented study is Part 2 of a combined study on guidance for the convergence and variability of wave crests and impact loading extreme values. The data set of Part 1 ([1]) is based on greenwater loads on a sailing ferry and the data set of Part 2 on wave-in-deck loads on a stationary deck box.     

Review of the uncertainties associated to hull girder hydroelastic response and wave load predictions

This paper reviews the importance of uncertainties in hull girder loads influenced by flexible fluid structure interactions. The focus is on developments in the field of hydroelastic modelling, simulation and model tests of practical relevance to the prediction hull girder wave load predictions and their validation. It is concluded that whereas hydroelastic methods for use in design development and assessment become increasingly useful, challenges in realizing and modelling uncertainties can be attributed to: (1) the limitations of numerical methods to suitably model nonlinearities; (2) the ambiguity of model tests; and (3) the systematic use of data emerging from computational, model- or full-scale methods. An approach is recommended to assess the uncertainty in the hydroelastic responses to wave loading and an example is provided to demonstrate the application of the procedure.