Research on the Water Ridge and Slamming Characteristics of a Semisubmersible Platform under Towing Conditions

During the towing of semisubmersible platforms, waves impact and superpose in front of the platform to form a ridge shaped “water ridge”, which protrudes near the platform and produces a large slamming pressure. The water ridges occur frequently in the towing conditions of semisubmersible platforms. The wave–slamming on the braces and columns of platform is aggravated due to the water ridges, particularly in rough sea conditions. The effect of water ridges is usually ignored in slamming pressure analysis, which is used to check the structural strengths of the braces and columns. In this paper, the characteristics of the water ridge at the braces of a semisubmersible platform are studied by experimental tests and numerical simulations. In addition, the sensitivity of the water ridge to the wave height and period is studied. The numerical simulations are conducted by a Computational Fluid Dynamics (CFD) method, and their accuracy is validated based on experimental tests. The characteristics of the water ridge and slamming pressure on the braces and columns are studied in different wave conditions based on the validated numerical model. It is found that the wave extrusion is the main reason of water ridge. The wave–slamming pressure caused by the water ridge has an approximately linear increase with the wave height and is sensitive to the wave period. With the increase of the wave period, the wave–slamming pressure on the brace and column of the platform increases first and then decreases. The maximum wave–slamming pressure is found when the wave period is 10 s and the slamming pressure reduces rapidly with an increase of wave period.

Wind and wave regime over the Bombay high area under the influence of cyclonic storms

Temporal distributions of wind and wave over Bombay High Area (BHA) during cyclone period have been studied. Ten years’ (1990-99) data of BHA during cyclone period have been used. It is found that under the influence of cyclonic storms strong southwesterly winds prevail over the BHA in pre-monsoon and weaker east to southeasterly winds during post-monsoon. Southwesterly wave with heights exceeding 20 feet are encountered in BHA during pre-monsoon and south easterlies with wave height reaching up to 12 feet in post monsoon. Analysis of situations with different storm locations also yielded similar results. Relationships between wind speeds and wave height as well as the distance of the storm centre over BHA have been established.

Prototype-Scale Physical Model of Wave Attenuation Through a Mangrove Forest of Moderate Cross-Shore Thickness: LiDAR-Based Characterization and Reynolds Scaling for Engineering With Nature

This study investigates the potential of a Rhizophora mangrove forest of moderate cross-shore thickness to attenuate wave heights using an idealized prototype-scale physical model constructed in a 104 m long wave flume. An 18 m long cross-shore transect of an idealized red mangrove forest based on the trunk-prop root system was constructed in the flume. Two cases with forest densities of 0.75 and 0.375 stems/m2 and a third baseline case with no mangroves were considered. LiDAR was used to quantify the projected area per unit height and to estimate the effective diameter of the system. The methodology was accurate to within 2% of the known stem diameters and 10% of the known prop root diameters. Random and regular wave conditions seaward, throughout, and inland of the forest were measured to determine wave height decay rates and drag coefficients for relative water depths ranging 0.36 to 1.44. Wave height decay rates ranged 0.008–0.021 m–1 for the high-density cases and 0.004–0.010 m–1 for the low-density cases and were found to be a function of water depth. Doubling the forest density increased the decay rate by a factor two, consistent with previous studies for other types of emergent vegetation. Drag coefficients ranged 0.4–3.8, and were found to be dependent on the Reynolds number. Uncertainty in the estimates of the drag coefficient due to the measured projected area and measured wave attenuation was quantified and found to have average combined standard deviations of 0.58 and 0.56 for random and regular waves, respectively. Two previous reduced-scale studies of wave attenuation by mangroves compared well with the present study when their Reynolds numbers were re-scaled by λ3/2 where λ is the prototype-to-model geometric scale ratio. Using the combined data sets, an equation is proposed to estimate the drag coefficient for a Rhizophora mangrove forest: CD = 0.6 + 3e04/ReDBH with an uncertainty of 0.69 over the range 5e03 < ReDBH < 1.9e05, where ReDBH is based on the tree diameter at breast height. These results may improve engineering guidance for the use of mangroves and other emergent vegetation in coastal wave attenuation.

Comparing the Currents Measured by CARTHE, CODE and SVP Drifters as a Function of Wind and Wave Conditions in the Southwestern Mediterranean Sea

Instruments drifting at the ocean surface are quasi-Lagrangian, that is, they do not follow exactly the near-surface ocean currents. The currents measured by three commonly-used drifters (CARTHE, CODE and SVP) are compared in a wide range of sea state conditions (winds up to 17 m/s and significant wave height up to 3 m). Nearly collocated and simultaneous drifter measurements in the southwestern Mediterranean reveal that the CARTHE and CODE drifters measure the currents in the first meter below the surface in approximately the same way. When compared to SVP drogued at 15 m nominal depth, the CODE and CARTHE currents are essentially downwind (and down-wave), with a typical speed of 0.5–1% of the wind speed. However, there is a large scatter in velocity differences between CODE/CARTHE and SVP for all wind and sea state conditions encountered, principally due to vertical and horizontal shears not related to the wind. For the CODE drifter with wind speed larger than 10 m/s and significant wave height larger than 1 m, about 30–40% of this difference can be explained by Stokes drift.

Estimation of Wave-Breaking Index by Learning Nonlinear Relation Using Multilayer Neural Network

Estimating wave-breaking indexes such as wave height and water depth is essential to understanding the location and scale of the breaking wave. Therefore, numerous wave-flume laboratory experiments have been conducted to develop empirical wave-breaking formulas. However, the nonlinearity between the parameters has not been fully incorporated into the empirical equations. Thus, this study proposes a multilayer neural network utilizing the nonlinear activation function and backpropagation to extract nonlinear relationships. Existing laboratory experiment data for the monochromatic regular wave are used to train the proposed network. Specifically, the bottom slope, deep-water wave height and wave period are plugged in as the input values that simultaneously estimate the breaking-wave height and wave-breaking location. Typical empirical equations employ deep-water wave height and length as input variables to predict the breaking-wave height and water depth. A newly proposed model directly utilizes breaking-wave height and water depth without nondimensionalization. Thus, the applicability can be significantly improved. The estimated wave-breaking index is statistically verified using the bias, root-mean-square errors, and Pearson correlation coefficient. The performance of the proposed model is better than existing breaking-wave-index formulas as well as having robust applicability to laboratory experiment conditions, such as wave condition, bottom slope, and experimental scale.

Wave Analysis for Offshore Aquaculture Projects: A Case Study for the Eastern Mediterranean Sea

The investigation of wave climate is of primary concern for the successful implementation of offshore aquaculture systems as waves can cause significant loads on them. Up until now, site selection and design (or selection) of offshore cage system structures on extended sea areas do not seem to follow any specific guidelines. This paper presents a novel methodology for the identification of favorable sites for offshore aquaculture development in an extended sea area based on two important technical factors: (i) the detailed characterization of the wave climate, and (ii) the water depth. Long-term statistics of the significant wave height, peak wave period, and wave steepness are estimated on an annual and monthly temporal scale, along with variability measures. Extreme value analysis is applied to estimate the design values and associated return periods of the significant wave height; structures should be designed based on this data, to avoid partial or total failure. The Eastern Mediterranean Sea is selected as a case study, and long-term time series of wave spectral parameters from the ERA5 dataset are utilized. Based on the obtained results, the most favorable areas for offshore aquaculture installations have been identified.