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Mesh Movement for a Discrete-Adjoint Newton-Krylov Algorithm for Aerodynamic Optimization

机译:用于空气动力学优化的离散伴奏Newton-Krylov算法的网格运动

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A grid movement algorithm based on the linear elasticity method with multiple increments is presented. The method is computationally expensive, but is exceptionally robust, producing high quality elements even for large shape changes. It is integrated with an aerodynamic shape optimization algorithm that uses an augmented adjoint method for gradient calculation. The discrete adjoint equations are augmented to explicitly include the sensitivities of the mesh movement, resulting in an increase in efficiency and numerical accuracy. This gradient computation method requires less computational time than a function evaluation, and leads to significant computational savings as dimensionality is increased. The results from application of these techniques to several large deformation and optimization cases are presented.
机译:提出了一种基于具有多种增量的线性弹性方法的电网运动算法。该方法是计算昂贵的,但是非常坚固,即使对于大形状的变化,也产生高质量元素。它与空气动力学优化算法集成,它使用了用于梯度计算的增强伴随方法。离散伴随方程被增强以明确地包括网格运动的敏感性,从而提高效率和数值准确性。该梯度计算方法需要较少的计算时间而不是函数评估,并且导致显着的计算节省,因为维度增加。介绍了这些技术的结果,提出了几种大变形和优化案例。

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