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Improvement of Computing Efficiency and Regularization of Inner Boundary Shape Optimization in Temperature Field

机译:提高计算效率并修正温度场内边界形状的规则化

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The purpose of this study is the improvement of the efficiency of design process that reaches to detail design from initial design. Genetic algorithm is applied to the initial design stage and conjugate gradient method is applied to the detail design stage. The design solution obtained by GA can be adopted as an initial design solution in the detail design stage because GA has the advantage of the capability of the global search in the optimization process. Furthermore, the regularization method is applied as an avoidance strategy of the ill-posedness that encounters at the process of the detail shape determination. The effectiveness of the proposed method is examined through an application to the optimization problem of the inner boundary shape determination in temperature field.
机译:本研究的目的是提高设计过程的效率,从最初的设计到详细设计。遗传算法应用于初始设计阶段,共轭梯度法应用于详细设计阶段。由于GA在优化过程中具有全局搜索的优势,因此可以将GA获得的设计解决方案作为详细设计阶段的初始设计解决方案。此外,正则化方法被用作避免在细节形状确定过程中遇到的不适的策略。通过对温度场内边界形状确定的优化问题的应用,检验了该方法的有效性。

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