Offshore oil reserves are abundant, most of which are concentrated on the continental shelf, with broad development prospects. Offshore oil and gas platforms used to use offshore oil are called offshore platforms. Compared with marine facilities, marine platforms have the characteristics of harsh natural environment, small space, large investment and high technical requirements. Accidents such as pressure vessel leakage, platform damage, fire and explosion on offshore platforms will cause huge property losses and casualties. The high risk of safety accidents on offshore platforms requires more perfect safety measures. The purpose of this paper is to study the marine engineering safety analysis based on the joint probability model of wind and waves. This paper proposes a safety analysis method based on a probabilistic test model to conduct quantitative safety analysis of ship technology and improve the analysis performance. The research content focuses on the following points: Firstly, the density concentration of the cylindrical foundation, the SQP optimization method and the improvement of genetic algorithm are applied to the overall size optimization design of the cylindrical foundation. Under the conditions of satisfying the strength, stiffness and stability of the foundation, the design optimization and topology optimization are generated, and the finite element method is used to carry out the local optimization design of the large-diameter cylindrical foundation power transmission system. Finally, to demonstrate the reliability of the results and the validity of the method, this paper validates the performance results using a traditional family tree and compares the entire model-based approach with traditional security methods. The method adopted in this paper can carry out a comprehensive safety analysis of complex systems, the calculation results are reliable, and the efficiency of safety analysis is improved.

Sujata Bisen. Safety Analysis of Marine Engineering Based on Joint Probability Model of Wind and Waves. Frontiers in Ocean Engineering (2022), Vol. 3, Issue 3: 46-54. https://doi.org/10.38007/FOE.2022.030306.

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