基于并行变可信度置信下界算法的航行体天线罩结构优化设计

Optimization design of antenna cover of deeply submerged body based onparallel variable-fidelity LCB algorithm

    摘要
  • 摘要:
      目的  为了使水下发射的航行体天线罩结构在满足碰撞性能要求的条件下，尽可能减轻结构质量，提出一种并行变可信度置信下界(PVF-LCB)算法，对航行体天线罩结构尺寸进行优化设计。
      方法  变可信度置信下界(VF-LCB)函数在设计过程中可自适应地分配计算资源，可以使用高/低精度代理模型构建影响函数(IF)，选取对模型改善较大的多个样本点，最后与相应的约束处理策略结合，从而对航行体天线罩结构尺寸进行优化。
      结果  提出的方法使航行体天线罩的结构尺寸优化设计满足了要求，且质量比基于变可信度代理模型的串行优化方法降低了约50%，并缩短了设计优化时间；相比单精度并行优化方法，天线罩质量降低约30%，搜索优化可行解的效率得到提高。
      结论  该方法在航行体的天线罩结构优化设计中不仅缩短了设计周期，而且提高了优化解的质量，在工程应用中具有一定的发展前景及指导意义。

     

    Abstract:
      Objectives  In order to reduce the weight while maintaining the performance of the antenna cover of a deeply submerged body, a parallel variable-fidelity lower confidence bound (PVF-LCB) approach is proposed to optimize the structure of the antenna cover.
      Methods  The proposed algorithm adaptively allocates computational resources of different fidelities through a variable-fidelity LCB (VF-LCB) function, allowing it to select several candidate samples based on influence functions (IFs) constructed by the variable-fidelity Kriging model. Moreover, the proposed method is assisted with widely used constraint-handling methods to solve the structural optimization problem.
      Results  The proposed approach obtains an optimized antenna cover structure which satisfies all constraints. Compared with the well-known variable-fidelity optimization method, the optimized structure is about 50% lower in weight. Additionally, the proposed approach reduces the weight of the antenna cover by about 30% compared with the results of single-fidelity parallel optimization methods.
      Conclusions  The proposed method can not only reduce the design cycle of engineering optimization, but improve the quality of the optimal solution, giving it certain development prospects and guiding significance for engineering applications.

     

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