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Progressive Subdivision Curves for Aerodynamic Shape Optimisation

机译:用于空气动力形状优化的渐进细分曲线

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This work presents a shape parameterisation method based on multi-resolutional subdivision curves and investigates its application to aerodynamic optimisation. Subdivision curves are defined as the limit curve of a recursive application of a subdivision rule, which provides an intrinsically hierarchical set of control polygons that can be used to provide surface control at varying levels of fidelity. This is used to construct a progressive aerofoil parameterisation that allows an optimisation to be initialised with a small number of design variables, and then periodically increased in resolution through the optimisation. This brings the benefits of a low dimensional design space (high convergence rate, increased robustness, low cost finite-difference gradients) while still allowing the final results to be from a high-dimensional design space. In this work the progressive refinement technique is tested on a variety of optimisation problems. For each problem a range of 'static' (non-progressive) subdivision schemes (equivalent to cubic B-splines) are also used as a control group. For all the optimisation cases the progressive schemes perform comparably or better than the static methods, often providing a significant computational advantage, and in many cases allowing a solution to be found when the static method would otherwise finish prematurely in a local optimum.
机译:该工作提出了一种基于多分辨率细分曲线的形状参数化方法,并研究其在空气动力学优化的应用。细分曲线被定义为细分规则的递归应用的限制曲线,其提供了一个本质上分层的控制多边形集,可用于在不同程度的保真度下提供表面控制。这用于构造逐步的翼船参数化,其允许用少量设计变量初始化优化,然后通过优化定期以分辨率提高。这带来了低维设计空间(高收敛速度,鲁棒性,低成本的有限差分梯度)的好处,同时仍允许最终结果来自高维设计空间。在这项工作中,在各种优化问题上测试了渐进式细化技术。对于每个问题,一系列“静态”(非逐行)细分方案(等于立方B样条)也用作对照组。对于所有优化情况,逐步方案比静态方法相当或更好地执行,通常提供显着的计算优势,并且在许多情况下,允许在静态方法将在局部最佳上过早地完成时发现解决方案。

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