Планирование маршрута перехода морского судна с учетом параметров волнения

Freak waves have the properties of strong nonlinearity and suddenness, which are often accompanied by extreme weather conditions. As an important environmental load, wind has a significant transient characteristic and plays an important role in the generation of freak waves. In order to understand the statistical properties of waves under the action of wind, especially the influence of wind on freak waves, laboratory experiments were carried out. In this paper, based on the Benjamin-Feir instability, long time series of wave field under unsteady wind are simulated by Joint North Sea Wave Project (JONSWAP) spectra with random phases in a two-dimensional wave tank. The freak waves generated in the experiment are similar in shape to those measured at sea, and are more than twice the significant wave height of the sea state. Through the statistical analysis of wave significant wave height, kurtosis and skewness, the influence of unsteady wind on the statistical properties of wave evolution is analyzed, and the response of wave energy spectrum is further investigated. The results of experiment show that the waves with larger Benjamin-Feir index are often broken under the unsteady wind, resulting in the loss of wave energy and the significant decrease of wave significant wave height. The skewness of waves depends on the steepness and decreases slightly during wave evolution. It is worth noting that the wave kurtosis increases under the unsteady wind. As an important parameter to measure Benjamin-Feir index, kurtosis will play an important role in the generation of freak waves. The increase of kurtosis will increase the probability of freak waves. Through the analysis of wave energy spectrum, it is found that there is energy dissipation in the process of wave evolution. The wave breaking under the unsteady wind leads to the decrease of the peak value of energy spectrum, and the energy obtained by the wave from the wind is mainly concentrated in the high frequency part of the wave.

The Directional Hybrid Wave Model (DHWM) has been developed for the deterministic decomposition and prediction of irregular ocean waves. The Extended Maximum Likelihood Method (EMLM) is employed to determine the directional spreading of wave energy, and the initial phases of directional free-wave components are calculated by least-square fitting. The nonlinear effects are computed using a hybrid second-order wave-wave interaction model which is a combination of the conventional perturbation approach and the phase modulation approach, and are subtracted from the measurements. The free-wave components are obtained by iteratively decoupling the free-wave components and their nonlinear interactions. The DHWM can decompose a wave field defined by multiple fixed-point measurements into a set of directional free-wave components. Based on these derived free-wave components, the wave properties can be predicted in the vicinity of the measurements. The present method is verified numerically and applied to both laboratory and field measurements in various scenarios. Satisfactory agreement between the predictions based on the decomposed free-wave components and the corresponding measurements demonstrates that the DHWM is reliable and robust. It is expected that the DHWM will have a variety of applications to ocean science and engineering. Introduction Deterministic predictions, based on related measurements, of wave characteristics of directional sea waves are indispensable to many ocean and coastal science and engineering problems, such as wave groupness, maximum wave height and wave-structure interactions, etc. However, such a prediction tool has not been proposed in previous studies (Zhang et al. 1997). Ocean waves are usually the superpositions of many wave components of different frequencies, amplitudes and advancing in different directions, and the nonlinear interactions of these wave components. The basic wave components, known as free-wave (or linear) components, obey the dispersion relation. Due to the nonlinearity of surface waves, the interactions among these free-wave components result in bound-wave components which in general do not obey the dispersion relation. In the cases of steep waves, the free-wave components of frequencies near the spectral peak frequency are dominant but the amplitudes of boundwave components may be dominant or important with respect to the free-wave components of the same frequency in the frequency bands either far lower and higher than the peak frequency (Zhang et al. 1996a). It is known that the relationship between the amplitudes of the elevation and potential of a free-wave component is quite different from that of a bound-wave component. The existing linear wave theories either ignore bound-wave components or treat them in the same way as the free-wave components of the same frequency. Hence, wave characteristics predicted by using linear wave theory, e.g. wave kinematics based on measured wave elevation or wave elevation based on measured dynamic pressure, were found to be inaccurate (Torum & Gudmestad 1989; Spell et al. 1996; Zhang et al. 1996b). For accurate prediction, nonlinear wave effects have to be treated as what they are in the decomposition and superposition of a wave field. That is, the bound-wave components are decoupled from the measured wave characteristics before a wave field is decomposed into its free-wave components.

Plastic pollution in world oceans is estimated to have reached 270.000 tones, or 5.25 trillion pieces. This plastic is now ubiquitous, however due to ocean circulation patterns, it accumulates in the ocean gyres, creating “garbage patches”. This plastic debris is colonized by microorganisms which can create unique surfactants and bio-film ecosystems. Microbial colonization is the first step towards disintegration and degradation of plastic materials: a process that releases metabolic by-products from energy synthesis. These byproducts include the release of short-chain and more complex carbon molecules in the form of surfactants, which we hypothesize will affect the fluid dynamic properties of waves (change in viscosity and surface tension) and make them detectable by the SAR sensor. In this study we used Sentinel-1A and COSMO-SkyMed SAR images in selected sites of the North Pacific and North Atlantic oceans, close to the ocean gyres and away from the coastal interference. Together with SAR processing we conducted contextual image analysis, using ocean geophysical products of the sea surface temperature, surface wind, chlorophyll, wave heights and wave spectrum of the ocean surface. In addition, we started lab experiments under controlled conditions to test the behaviour of microbes colonizing the two most common marine pollutants, polyethylene (PE) and polyethylene terephthalate (PET) microplastics. The analysis of the SAR images had shown that a combination of surface wind speed and Langmuir cells- ocean circulation pattern is the main controlling factor in creating the distinct appearance of the surfactants, sea-slicks and microbial bio-films. The preliminary conclusion of our study is that SAR remote sensing may be able to detect plastic pollution in the open oceans and this method can be extended to other areas.

An investigation was undertaken to discover the extent to which statistical properties of wind-generated waves can be simulated on a small scale under laboratory conditions. Experimental data were collected in a wind and wave facility for more than 150 sea conditions at twelve fetches (9 ft to 65 ft) and ten wind speeds (19 fps to 72 fps). Continuous water surface elevation recordings, as sensed by capacitance wire transducers and recorded in analog form on magnetic tape, were digitized for analysis by computer. The wave energy spectra exhibit properties which are at least qualitatively similar to those obtained under oceanic conditions. Moreover, the data substantiate the analysis by Longuet-Higgins in which the wave heights are described by a Rayleigh probability distribution. Comparison of laboratory and field data demonstrates that statistical parameters derived on the basis of Longuet-Higgins' theoretical results are in good agreement over a large range of sea wave environments.

The prediction of converted energy by one way gears wave energy converter may be influenced by non-linearity properties of the ocean waves. To date there has not been an adequate analytical model to predict the power production of one way gear wave energy converter under irregular wave condition. In this work, analytical model is developed to describe the interaction of one way gear wave energy converter that utilized gravity force of the gravityweight (M) with irregular ocean waves using JONSWAP (Joint North Sea Wave Project) model. This interaction model has been simulated numerically by means of computer software. The simulation result showed that wave height is strongly determining the converted output power. The outcome of harnessing the gravity force instead of buoyant force of this proposed model that commonly used by the previous wave energy converter demonstrate significant potential output power. The proposed model can be used to design feasible and efficient wave energy converter.

This article presents a thorough testing of the bathymetry estimation method known as Wave Kinematics Bathymetry. WKB is used with nautical radar and spaceborne optical imagery for shallow water zones [1], [2] and is based on the analysis of sea waves using two successive images of the same zone with an interval of only a few seconds. While in certain conditions the method seems to give promising results, a number of parameters during capture such as wind, Sun, and sensor position can reduce its precision considerably. In the article we set out to investigate this dependence of the WKB on external parameters in an empirical way. For this purpose we have developed a sea surface simulator that allows us to reproduce a large number of configurations of Sun and sensor positions, as well as of wave properties. We use our simulator in particular with respect to a set of real Pleiades images taken in Brittany, France, allowing us to pre-determine the subset suitable for bathymetry estimation. Our results can thus be useful from both a time and a cost saving perspective.