The key to coping with global warming is reconstructing energy governance from carbon-based to sustainable resources. Offshore energy sources, such as offshore wind turbines, are promising alternatives. However, the abnormal climate is a potential threat to the safety of offshore structures because construction guidelines cannot embrace climate outliers. A cosine similarity-based maintenance strategy may be a possible solution for managing and mitigating these risks. However, a study reporting its application to an actual field structure has not yet been reported. Thus, as an initial study, this study investigated whether the technique is applicable or whether it has limitations in the real field using an actual example, the Gageocho Ocean Research Station. Consequently, it was found that damage can only be detected correctly if the damage states are very similar to the comparison target database. Therefore, the high accuracy of natural frequencies, including environmental effects, should be ensured. Specifically, damage scenarios must be carefully designed, and an alternative is to devise more efficient techniques that can compensate for the present procedure.
Offshore jacket structures generally comprise steel members, and the safety standard for jacket structures typically focuses on the steel components. However, large amounts of concrete grouting is filled in the legs of the Gageocho jacket structure to aid in the recovery from typhoon damage. This paper proposes a safe and lightweight design for the Gageocho ocean research station comprising steel members instead of large amounts of concrete reinforcement in the legs. Based on the actual design, the structural members are grouped according to their functional roles, and the inner diameter of the cross-section in each design group is defined as a design variable. Structural optimization is carried out using a genetic algorithm to minimize the total weight of the structure. To satisfy the conservative safety standards in the offshore field, both the maximum stress and the unity check criteria are considered as design constraints during optimization. For enhanced safety confidence, extreme environmental conditions are assumed. The maximum marine attachment thickness and the section erosion in the splash zone are applied. Additionally, the design load is defined as the force induced by extreme waves, winds, and currents aligned in the same direction. All the loading directions surrounding the structure are considered to design the structure in a balanced and safe manner. As a result, compared with the current structure, the proposed structure features a 45% lighter design, satisfying the strict offshore safety criteria.
In this paper, we present the regression analysis and design optimization for improving the permeability of 3D woven materials based on numerical analysis data. First, the parametric analysis model is generated with variables that define the gap sizes between each directional wire of the woven material. Then, material properties such as bulk modulus, thermal conductivity coefficient, and permeability are calculated using numerical analysis, and these material data are used in the polynomial-based regression analysis. The Pareto optimal solution is obtained between bulk modulus and permeability by using multi-objective optimization and shows their trade-off relation. In addition, gradient-based design optimization is applied to maximize the fluid permeability for 3D woven materials, and the optimal designs are obtained according to the various minimum bulk modulus constraints. Finally, the optimal solutions from regression equations are verified to demonstrate the accuracy of the proposed method.
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