Multipoint and Multi-Objective Aerodynamic Shape Optimization
Multipoint and Multi-Objective Aerodynamic Shape Optimization
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DOI：
10.2514/1.10415
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发表时间：
2002-09
期刊：
影响因子：
2.5
通讯作者：
M. Nemec;D. Zingg;T. Pulliam
中科院分区：
文献类型：
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作者：
M. Nemec;D. Zingg;T. Pulliam
提出了一种单段和多段翼型气动优化的Newton-Krylov算法。流动由可压缩Navier-Stokes方程和单方程湍流模型控制。应用预条件广义最小残差法求解离散伴随方程，从而快速计算精确的目标函数梯度。优化约束是通过惩罚制定强制执行，并通过拟牛顿法求解所产生的无约束问题。设计实例包括升力增强和多点升力约束阻力最小化问题。最后，将该算法应用于多目标优化问题的Pareto前沿面计算，并通过遗传算法对计算结果进行了验证。总的来说，新算法为解决复杂的空气动力学问题提供了一种可靠的方法
A Newton‐Krylov algorithm is presented for the aerodynamic optimization of singleand multi-element airfoil configurations. The flow is governed by the compressible Navier‐Stokes equations in conjunction with a one-equation turbulence model. The preconditioned generalized minimum residual method is applied to solve the discreteadjoint equation, leading to a fast computation of accurate objective function gradients. Optimization constraints are enforced through a penalty formulation, and the resulting unconstrained problem is solved via a quasi-Newton method. Design examples include lift-enhancement and multi-point lift-constrained drag minimization problems. Furthermore, the new algorithm is used to compute a Pareto front for a multi-objective problem, and the results are validated using a genetic algorithm. Overall, the new algorithm provides an ecient and robust approach for addressing the issues of complex aerodynamic