深海浮筏式网箱高效有限元分析及结构轻量化

Efficient finite element analysis and structural lightweight of deep-sea floating raft cage

  • 摘要: 针对深海浮筏式养殖网箱由于结构复杂、载荷多样导致的有限元建模繁琐问题,提出了一种高效有限元分析与结构优化的方法。文章以某直径40 m的深海浮筏式养殖网箱为例,通过梳理算法与程序开发,实现了节点与单元定义、风浪流等载荷的参数化计算与施加,以及优化参数实时更新等功能,进行了基于ANSYS软件的二次开发,完成了网箱有限元模型的高效建模和重构。在此基础上,结合遗传算法进行网箱结构优化,并通过引入幂次变异函数来增强优化算法的鲁棒性。结果表明,在结构强度一致的情况下,优化后的网箱质量减少了17.98%。该方法可为深海浮筏式养殖网箱的设计与结构优化提供参考。

     

    Abstract: Regarding the cumbersome finite element modeling problem caused by the complex structure and diverse loads of deep-sea floating raft aquaculture cages, we applied an efficient finite element analysis and designed a structural optimization method. Taking a 40-meter-diameter deep-sea raft-type aquaculture cage as an example, we achieved parametric calculation and application of loads including wind, wave, and current through systematic algorithm development and programming. The work implemented functions such as node/element definition and real-time optimization parameter updates, while conducting secondary development based on ANSYS software. This approach enabled efficient modeling and reconstruction of the cage's finite element model. On the basis of the efficient finite element modeling, the structural optimization based on the genetic algorithm was realized, and the robustness of the optimization algorithm was enhanced by introducing the power variation function. The results show that under the condition of consistent structural strength, the optimized cage effectively reduced the mass by 17.98%. The method in this paper can provide a reference for the design and structural optimization of deep-sea floating raft aquaculture cages.

     

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