Efficient Global Aerodynamic Shape Optimization of a Full Aircraft Configuration Considering Trimming
Efficient Global Aerodynamic Shape Optimization of a Full Aircraft Configuration Considering Trimming
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DOI：
10.3390/aerospace10080734
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发表时间：
2023-08
期刊：
影响因子：
2.6
通讯作者：
Kai Wang;Zhonghua Han;Keshi Zhang;Wenping Song
中科院分区：
文献类型：
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作者：
Kai Wang;Zhonghua Han;Keshi Zhang;Wenping Song
现有的气动外形优化(ASO)研究大多没有考虑平衡俯仰力矩，因此必须对优化后的布局进行修剪，以确保零俯仰力矩，这会造成额外阻力，显著降低ASO的效益。本文提出了一种直接施加零俯仰力矩约束的高效全局ASO方法。采用自由变形(FFD)参数化方法，结合拉普拉斯光滑化方法，实现了整机外形的参数化，并保证了足够光滑的气动外形。求解雷诺平均的N-S方程(RANS)来模拟跨音速粘性流动。采用基于代理的多轮优化策略来驱动ASO向全局最优方向发展。为了验证所提方法的有效性，我们对NASA共同研究模型(CRM)的机翼-机身-尾翼布局采用了两种设计优化策略。第一种策略是在不考虑俯仰力矩平衡的情况下对布局进行优化，然后通过偏转水平尾部来手动修剪优化的布局。二是在优化模型中直接施加零俯仰力矩约束，并将水平尾翼的偏转角作为附加设计变量。结果表明：(1)对于第一种策略，当人工修剪最优构型时，会损失大约4次的减阻效益；(2)第二种策略可以获得比第一种策略多3.2次的减阻效益；(3)与基于梯度的优化(GBO)相比，基于代理的优化(SBO)对于约80个设计变量的ASO问题比GBO更有效，而SBO所获得的ASO效益与GBO相当。
Most existing aerodynamic shape optimization (ASO) studies do not take the balanced pitching moment into account and thus the optimized configuration has to be trimmed to ensure zero pitching moment, which causes additional drag and reduces the benefit of ASO remarkably. This article proposes an efficient global ASO method that directly enforces a zero pitching moment constraint. A free-form deformation (FFD) parameterization combing Laplacian smoothing method is implemented to parameterize a full aircraft configuration and ensure sufficiently smooth aerodynamic shapes. Reynolds-averaged Navier–Stokes (RANS) equations are solved to simulate transonic viscous flows. A surrogate-based multi-round optimization strategy is used to drive ASO towards the global optimum. To verify the effectiveness of the proposed method, we adopt two design optimization strategies for the NASA Common Research Model (CRM) wing–body–tail configuration. The first strategy is to optimize the configuration without considering balance of pitching moment, and then manually trim the optimized configuration by deflecting the horizontal tail. The second one is to directly enforce the zero pitching moment constraint in the optimization model and take the deflection angle of the horizontal tail as an additional design variable. Results show that: (1) for the first strategy, about 4-count drag-reducing benefits would be lost when manually trimming the optimal configuration; (2) the second strategy can achieve 3.2-count more drag-reducing benefits than the first strategy; (3) compared with gradient-based optimization (GBO), surrogate-based optimization (SBO) is more efficient than GBO for ASO problems with around 80 design variables, and the benefit of ASO achieved by SBO is comparable to that obtained by GBO.