基于遗传算法的潜器压载敷设优化方法

Genetic algorithm based optimization method for kentledge laying of submersibles

  • 摘要:
      目的  针对工程实践中潜器固定压载敷设存在工作量大、随机性强、结果不优的难题,考虑将广泛用于函数寻优的智能算法引入这一领域,提出一种基于遗传算法的潜器固定压载敷设方法。
      方法  首先,对典型潜器固定压载敷设横剖面进行研究,通过有限元方法的逆向思考,构建其等效的简化数学模型,并提取约束函数和目标函数;然后,结合遗传算法进行寻优计算,得到重心较优的固定压载敷设方案;最后,构建不同参数的多个算例进行分析验证。
      结果  结果显示,在相同条件下,所提的较好的寻优方案相比一般方案(相当于人工方案)其重心下降约23%,可以很好地同时平衡纵向力矩与横向力矩。
      结论  研究表明:所提的模型简化和寻优方法可以有效提高敷设的工作效率,改善最终方案的重心效果;所总结的敷设原则对工程实践有参考价值。

     

    Abstract:
      Objectives   Typically, the fixed kentledge laying scheme of a submersible requires a significant amount of work and can often produce unpleasant results in engineering practice. Intelligent algorithms are considered for application in order to optimize the scheme. This paper proposes a genetic algorithm based method to solve the problem.
      Methods  First, by studying typical transverse sections of kentledge laying in a submersible and reverse-thinking the finite element method, a simplified equivalent mathematic model is constructed. Next, constraint functions and objective functions are extracted from the model. By using a genetic algorithm, improved fixed kentledge laying schemes are acquired with lower centers of gravity. By computing different examples, this method is proven to be effective in gaining good gravity center results with a much smaller workload.
      Results  The result shows that the gravity center of the improved scheme can be 23% lower compared to the ordinary scheme. This method is also effective in balancing longitudinal moment and lateral moment at the same time.
      Conclusions  This study shows that the equivalent mathematical model and optimization method are feasible, and can improve both work efficiency and gravity results. Several general principles are also concluded, which can be helpful in engineering practice.

     

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