Aerodynamic and Stealth Integrated Design of DSI Inlet by Surrogate-Based Multi-Objective Optimization with EHVI Infill Criterion

Huayu Fan,Hao Zhan,Shixin Cheng,Baigang Mi

doi:10.1051/jnwpu/20193750918

Abstract

To deal with the problem of aerodynamic and stealth integrated optimization of DSI inlet, a multi-objective optimization study on aerodynamic and stealth of the DSI inlet is carry out which based on the deformation of the three-dimensional compression bump surface. The FFD parametric method is used to parameterize the bump surface; CFD calculation based on RANS equations is used to analyze the aerodynamic performance of the DSI inlet, large element physical optical method and uniform theory of diffraction are used to calculate RCS of the DSI inlet; And ASMOPSO algorithm with the Kriging surrogate model which based on the expect hyper-volume improvement infill criterion is adopted for integrated optimization design. The results of DSI inlet aerodynamic and stealth integrated optimization exhibit considerable improvement.

Highlights

To deal with the problem of aerodynamic and stealth integrated optimization of DSI inlet, a multi⁃ objective optimization study on aerodynamic and stealth of the DSI inlet is carry out which based on the deformation of the three⁃dimensional compression bump surface
The FFD parametric method is used to parameterize the bump surface; CFD calculation based on RANS equations is used to analyze the aerodynamic performance of the DSI in⁃ let, large element physical optical method and uniform theory of diffraction are used to calculate RCS of the DSI in⁃ let; And ASMOPSO algorithm with the Kriging surrogate model which based on the expect hyper⁃volume improve⁃ ment infill criterion is adopted for integrated optimization design
Æ1.School of Aeronautics, Northwestern Polytechnical University, Xi′an 710072, China;ö ç è2.School of Aerospace Engineering, Tsinghua University, Beijing 100084, China ø

Summary

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始样本空间精度的依赖,采用基于自适应加点的动态 Kriging 代理模型对粒子群中的未观测点进行近似评估, 动态更新代理模型样本点过程中, 使用 EHVI( expected hyper⁃volume improvement) 加点准则. 为此文献[20] 提出了一种动态的 EHVI 值计算方式[20] ,函数测试表明其可以极大地节约超体积期望改善的计算时间。本文所使用加点准则就是基于此动态计算方法的 EHVI 加点准则。. 最大 EHVI 值的子优化过程,本文计算当前种群中所有个体的 EHVI 值并对它们进行降序排列,选取前几个个体进行真实函数评估并加入样本集并且用于更新外部非支配解档案来引导 ASMOPSO 中个体的移动。. 结合多目标粒子群算法、 Kriging 代理模型、 EHVI 加点形成的高效多目标优化算法,详细步骤如下: 1) 给定粒子群规模大小N, 外部档案规模 NREP ,最大迭代步数 Imax ,并将外部档案初始化为空, 即 REP = Ø;设置超体积计算参考点 REF - Pnt; 2) 使用拉丁超立方法生成 Nsamples 个样本点,计算目标函数向量,使用公式始外形,以 DSI 进气道的 bump 面为研究对象,以超声速设计点时进气道出口平面的总压畸变系数和前向 RCS 均值为优化目标,以亚、超声速设计点时的总压恢复、质量流率为约束,并使用 FFD( free form deformation) 方法对三维 bump 面进行参数化处理。. 0°,Re = 6.85 × 106 ; 设计点 2:H = 11 km,Ma∞ = 1.70,α = 0.0°,Re = 1.24 × 107 ; 按照上文所述的优化设置建立的优化数学模型. 在进行 FFD 参数化之后,使用曲面插值方法重新生成 bump 压缩面,这时与原始 bump 面相比几何误差的大小取决于插值点的数量和分布,但是它对进气道气动特性的影响一般都不是特别大。为了直观的说明这个误差的大小,对其进行 CFD 仿真比较, CFD 计算结果数据的比较见表 1,可以看出在跨声速设计点时,两者的差距几乎可以忽略不记,而在超声速设计点时也仅有一些微小差异。

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