A novel concept for non-linear multidisciplinary aerodynamic design optimization
A novel concept for non-linear multidisciplinary aerodynamic design optimization
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DOI：
10.1016/j.ast.2017.08.043
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发表时间：
2017-11
影响因子：
5.6
通讯作者：
S. Singh
中科院分区：
文献类型：
--
作者：
S. Singh
这里提出了一种基本的方法，以定义一个全面的属性，以克服现有气动设计/优化实践的限制。推导了一个新的参数，推广了热力学第二定律所考虑的损失模型。给出的方法试图定量地关联有限时间热力学不可逆性与特定形状类别的物体穿过流场。然后通过在外部和内部空气动力学中的应用对其进行解析研究。此外，使用气动结构优化的案例研究以及具有既定行为的其他物理量(多学科优化)来探索函数的物理行为。采用基于精英成员选择的多目标遗传算法对NACA1412和NACA 621112翼型气动扭转翼型基线模型进行了优化。结果表明，该函数具有更好的计算经济性和全面性。
A fundamental approach is presented here in order to define a comprehensive property that overwhelms the limitations of existing aerodynamic design/optimization practice. A novel parameter is derived extending the loss model accounted by the second law of thermodynamics. The given approach attempts to quantitatively relate the finite-time thermodynamic irreversibilities associated with a particular shape class of a body across a flow field. It is then studied analytically by applications in external and internal aerodynamics. Further, the physical behavior of the function is explored using a case study for aero-structural optimization along with other physical quantities with established behavior (Multi-Disciplinary-Optimization). A baseline model of aerodynamically twisted wing profile entailing NACA 1412 and NACA 621112 airfoils is optimized using Elite member selection based Multi-Objective Genetic Algorithm (MOGA). The proposed function is proven to be more computationally economical and comprehensive for optimization.