Aquaculture becomes an important industry and associates with many targets of sustainable development goals. As the aquaculture industries go forward offshore, the design of the floating net cage must be able to withstand extreme sea conditions. One of the vulnerable parts of floating net cage is the floater, especially at the bracket. There is load transfer in the bracket from net drag force, mooring tension, and horizontal force of the wave. Thus, this study aims to analyze the bracket under current and wave using the finite element method. Hydrodynamic force is based on the Morison formula. The numerical model was validated with the data obtained from corresponding experimental and numerical tests. On the basis, using the environmental condition in Pangandaran, Indonesia, the structure is simulated globally to obtain the deformation and tension. The simulations of the fish cage consist of single and double pipes. Then, the bracket at the floater will be analyzed locally to get the deformation and stress distribution. The maximum stress occurs at the connection between the horizontal and outer pipe of the bracket.

World fish production is increasing every year. This is mainly because of the trend to use floating net cages in aquaculture. One of the common net cage types is the collar cage. The net cage system must withstand the environmental and accidental loads, particularly on the mooring system as its function to maintain the position. Thus, this study focuses on analysis in mooring tension of the fully scaled net cage using numerical methods. The model scale data obtained from a previous experimental study and then scaled up to obtain the fully scaled net cage. After validation, current and wave data at Pangandaran bay, Indonesia is adapted to the simulation. Morison’s hydrodynamic force formula is used. Configuration of the mooring system is a rectangular array with a variation of spread angles of mooring lines between 90°, 60°, and 30°. The load cases used for simulation considering the operation and extreme conditions also the directions in lines and between lines. The result shows that the smallest mooring tension and offset is the configuration 30° in which the mooring lines spread evenly in each direction.

One of the main problems of floating net cages when operating is the escape of fish caused by breaking or tearing of the net. This is due to the influence of environmental loads that have been studied by several researchers. However, the influence of fish on net strength has not been considered. The schooling of fish in the cage can make the hydrodynamic flow change downstream of the cage. The collision of fish in groups on the net can increases 10–28% of the environmental load received by the net. Besides, fish bites on the net reduce the net cross-sectional area and lead to axial stiffness reduction. So, this study focuses on the analysis of the net strength to determine the net maximum tension, deformation, and the location of each parameter by considering the influence of fish in the net cage Simulations are conducted out using finite element method software with cage models based on physical and numerical experiments from prior studies. The results show that the net could withstand operating conditions. Meanwhile, in extreme conditions, the net could only survive in the 0° loading direction. The largest deformation reached 2.5 times the diameter of the cage. The collision of fish in groups on the net showed that the tensile force increased significantly when adding stress loading factor. While the effect of fish bites showed that the tensile force significantly decreased on all threads with a reduction in cross-sectional area.

In recent years, the implementation of subsea pipelines for oil and gas transportation has increased. One of the important aspects of the design process of the subsea pipeline is scour prediction. Scouring causes the subsea pipeline to lose its support and is susceptible to failure due to deflection. This paper presents the result of a literature review of scouring-related research to obtain a method to increase scouring prediction accuracy. Based on the literature research, it is known that the errors found in Computational Fluid Dynamics (CFD) are mainly affected by the flow models. Existing flow models cannot fully represent the complexity of turbulent flow that occurs during the scouring process. Artificial Neural Network (ANN) can reduce the error value. But, the CFD-ANN hybrid methods can potentially decrease the error value by about 20% more than CFD. Therefore, the CFD-ANN hybrid method is expected to be a new method that could be used to predict subsea pipeline scouring in the oil and gas industry.