One of the most important issues in designing coastal and offshore structures is the prediction of wave and current forces on slender cylinders. Such forces are often considered as dominate loadings. Many analytical and empirical methods such as Morison equation have been suggested for estimation of waves and current forces. Such methods, however, have shown inaccuracies in predicting hydrodynamic forces. On the other hand, Artificial Neural Networks (ANNs) have received a great deal of attention in recent years and are being touted as one of the greatest computational tools ever developed. In fact, ANNs are nonlinear systems consisting of a large number of highly interconnected processing units, nodes or artificial neurons, which have the ability of learning. In this research, ANNs have been used to estimate wave and current forces on slender cylinders. Data of 308 experimental specimens have been used for training and testing the networks. Considering the aim of this research for the application of ANNs, these data were consisted of recorded force values in different time series. The supervised learning neural networks models have been used in this research. The results indicate the success of the application of neural networks approach which can efficiently predict waves and current forces on slender cylinders after carrying out appropriate training. Furthermore, the results are within acceptable accuracy in comparison with experimental results and the results obtained from Morison equation.

Monopile platforms are rather slim structures which are sensitive to wave loadings and the natural period of them are within the range of sea waves’ periods. Therefore, suitable dynamic analysis and wave modeling for these platforms is necessary. There are two methods for analyzing such flexible structures under wave loading, i.e., deterministic and random methods. In deterministic method, a regular wave representing the sea state is used while random analysis considers irregular wave including spectral and time history analysis. A comprehensive research has been carried out by applying the above mentioned methods for several monopile platforms to evaluate the validity of these methods. Results show that time history random method has the most reliable responses because of accurate modeling of waves and considering nonlinearities in the analysis. However, spectral method accuracy is acceptable if inertia term of wave loading is dominated and natural period of platform is far from wave period. Deterministic method can be used when platform has high rigidity.

Development of advanced spectral wind wave models has been the subject of comprehensive researches which has led to reliable wave predictions for assessing the impact of waves on the natural environment, coastal protection, offshore structures and harbor over the past two decades. On the other hand, the Geographical Information Systems (GIS) are developed for working with geographical data which as standard tools are able to manage and represent such data. In the present work, linking the third-generation wind wave model of SWAN and GIS has been implemented to ease data management and representation of inputs and outputs of the model that are geo-reference data. Then the effect of computational time step has been investigated using available data for Urmia Lake situated in the Northwest of Iran. As SWAN has the ability to perform the options of 1st, 2nd and 3rd generation modeling, these options have been used to evaluate results obtained by applying these models. Results indicate that the 3rd generation wave model is more sensitive to higher computational time steps than other modes of wave generation models. However, the convergence behavior of the third-generation model is much faster than that of other models.

Tension leg platforms are compliant structures for oil extraction in deep water consisting of hull, deck foundation, tendons and risers. The hull is very important part of a TLP from functionality, weight and cost point of views that is made of vertical column and horizontal pontoon with circular and rectangular sections. The hull geometry plays very important rule in optimum action of the structure. The ratio of columns volume to total volume ( ), that is the function of pontoon length ( ), column length ( ), pontoon diameter ( ), column diameter ( ), is an important parameter in structure response against waves loading. In the present research a parametric study has been carried out to investigate the effect of hull geometry on TLP’s responses under wave attack. A wide range of geometric parameters have been considered. A number of models have been set up by changing pontoon length, column length, pontoon diameter and column diameter. In these models the displacement volume, total volume and tendons’ tension were kept constant. Then the structural models were analyzed under wave load using a finite element software. In this paper, results of this parametric study is presented and discussed. Based on these results, appropriate range of dimensionless geometry parameters are proposed for conceptual design of TLPs hull.

This paper presents results of an experimental investigation on stability of reshaping breakwaters. Results of 82 test cases have been used to study the reshaped profile condition of such breakwaters during the process of wave attacks. In this research, first 7 independent parameters having significant effects on structure stability have been identified and their consequence on geometric parameters of stability (6 parameters) have been studied. These 6 dependant parameters are selected so that they show completely the deformed geometry of the structure with the least probable tries. Then, using experimental data and fitting them to various statistical models, some formulae are suggested for estimation of geometrical parameters of reshaped profiles. Also efforts to increase the validity of these experimental formulae are presented. Finally a software called IB has been developed using results of the present research. Then comparisons have been made between IB and BREAKWAT program. Results show that BREAKWAT fails to predict the reshaped profile in some test cases.

In this paper, the procedure of developing an unconstrained Genetic Algorithm code to solve mooring pattern optimization problems for floating structures is described. How to spread mooring lines around the offshore structures and tension level of these lines are the factors that have direct effect on response or offset of floating units which experience environmental conditions such as waves, wind and current. A GA may be used to search optimum mooring pattern and the best tension of lines to minimize floating structures offset. In this work, dynamic analysis is used to estimate floating units responses in a mooring optimization problem. Waves and wind are defined by appropriate spectra and analysis is performed in frequency domain. The goal for optimization is to minimize the objective function which is the sum of squares of the floating unit’s displacements for each set of environmental conditions. The considered variables of optimization are: position of anchors, line lengths and vessel heading relative to environmental conditions. Also size of mooring lines, and their material and strength are considered to be constant. It is assumed that all lines are from the same size and material and no buoy or counter weight is attached to the lines. To demonstrate the capability of the developed code, its application in a case study is presented and some conclusions are derived.

The berm recession of a reshaping berm breakwater has a very important role in the stability and reshaping of this structure. In this research, the recession of the berm due to wave parameters has been studied based on 2D experimental modeling method in a wave flume. Irregular waves with JONSWAP spectrum were used. A total of 60 tests have been performed to cover the impact of wave parameters such as significant wave height, mean wave period and storm duration on berm recession. A new dimensionless parameter is introduced to evaluate the simultaneous influence of wave height and wave period. Then, a new formula that includes the wave parameters is derived using the new dimensionless parameter for estimating the berm recession. A comparison is made between the estimated berm recessions by this new formula and formulae given by other researchers. The results of this new formula in comparison with the other investigators formula show a proper correlation with the present experimental data and other experimental results.