Antonio Mikulić

Rapid ship seakeeping methods are particularly attractive when computational efficiency is of primary importance or when detailed hull geometry is unavailable. However, even under these constraints, ensuring a reasonable level of accuracy remains essential. This study compares two widely used rapid methods for estimating transfer functions of the vertical wave bending moment (VWBM) at midship, namely Sikora’s method and a closed-form expression (CFE). The comparison is carried out using the Frequency Independent Model Error (FIME) as a measure of model uncertainty, obtained by benchmarking both methods against model-scale experimental data. The results indicate the consistently better performance of Sikora’s method for the considered dataset, particularly by demonstrating reduced variability in the model error.

This paper investigates the change in hull girder failure probabilities and partial safety factors caused by the implementation of the new procedure for direct computation of wave loads recommended by the International Association of Classification Societies (IACS). Differences between new and previous procedures are primarily related to the different associated scatter diagrams, and secondarily due to the assumptions on wave spectrum, wave energy spreading, and ship speed. This study performs a comparative structural reliability analysis of the global longitudinal bending of five oil tankers of different sizes between two procedures for wave load computation. Firstly, failure probabilities are compared, and secondly, modified partial safety factors are proposed, resulting in similar failure probabilities according to two separate procedures. It is found that implementation of the new revision of the IACS procedure for direct computation of wave loads results in a reduction of the minimum required ultimate vertical bending capacity of a ship hull by 10%. In addition to the novel investigation of the safety of oil tankers using a revised wave scatter diagram, this study offers a new rapid method for calculation of extreme vertical wave bending moments based on the regression of the parameters of the Weibull function, used for the long-term probability distribution of wave-induced loads.

The environmental contours represent an approach for defining extreme environmental conditions, resulting in extreme responses of marine structures with a given return period. Over the past decade, an increasing number of studies have been developed dealing with the methods for defining environmental contours and enhancing their practical application in different marine environments. In the present study, environmental contours describing significant wave heights and peak wave periods are created for the Adriatic Sea. This small semi-enclosed sea basin within the Mediterranean Sea encounters increasing maritime and offshore activities. Considering also a great but still unused potential for the installation of renewable energy facilities, the main motives for the presented study are concluded. The environmental contours are established based on 24 years of hindcast wave data extracted from the WorldWaves database. Joint distributions consisting of the marginal distribution of significant wave height and conditional distributions of peak wave periods are used as a basis for the creation of environmental contours using the IFORM and ISORM methods. Return periods of 1 year, 25 years, and 100 years are considered relevant for the marine operation, design of ships, and offshore structures, respectively. A possibility of environmental contour practical application to the calculation of global wave loads upon ship structures is presented. Based on the uncertainty assessment performed, conservative environmental contours for the whole Adriatic are also presented.

The extreme significant wave height predictions often neglect within-year wave climate variability and wave directionality. Depending on a geographical region, local wind patterns and year climate variability could have an influence on the long-term prediction of waves. The Adriatic Sea having two dominant wind patterns of different characteristics, Bura and Jugo, is a great example for the case study. The 23-year hindcast wave data used in the presented study is extracted from the WorldWaves database. Based on wind and wave data, annual extreme significant wave heights generated by different wind patterns and for different months are fitted by Gumbel distribution using maximum likelihood estimation. Combined long-term extremes are then predicted by calculating system probability. It was found that considering the wave directionality, and especially the seasonality of wave climate, leads to a larger prediction of extreme significant wave heights. The extreme value prediction considering wave directionality on average yields 4% larger significant wave heights, while considering within-year climate variability leads to, on average, 8% larger extremes compared to the predictions when both effects are neglected.

Resistance of the bare hull of the tourist submarine with spherical heads, moving in forward and transverse directions is analyzed in OpenFOAM using Computational Fluid Dynamics. The resistance coefficients of the submarine are estimated for different length-to-diameter ratios and Reynolds numbers. The Artificial Neural Network with the optimum number of neurons is then trained to predict the resistance coefficients. Two simplified Artificial Neural Network models and Nonlinear Least Squares Marquardt-Levenberg algorithm are employed to fit the results in the form of equations that may be used in the initial design of this type of submarines. The comparative analysis of different prediction models is performed and guidelines for their practical application are given.

Wave directionality is often neglected when calculating extreme significant wave heights. However, some geographical regions hold dominant wind patterns yielding distinct wave characteristics. A typical example is the Adriatic Sea having two dominant wind patterns, namely bora and sirocco, generating distinguished wave types. The WorldWaves database is used to investigate the directionality effect in the Adriatic Sea, applying the past 24 years of data. Based on wind and wave data, the study considers sea states generated by different wind patterns. Yearly extreme values are extracted separately for studied directions, and extreme value distributions are fitted using the Annual Extreme Method. Long-term extreme values of significant wave heights are then calculated. System probability is employed to estimate combined long-term extreme significant wave heights. Obtained extreme values are then compared to ones determined by considering all wave data together, i.e., neglecting the wave directionality effect.