基于POD和代理模型的高压捕获翼表面流场快速预测方法
RAPID PREDICTION METHOD FOR HIGH-PRESSURE CAPTURING WING SURFACE FLOW FIELD BASED ON PROPER ORTHOGONAL DECOMPOSITION AND SURROGATE MODEL
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摘要: 高超声速飞行器气动特性的快速预测是其多学科优化设计中的核心环节. 当前, 针对升力体和翼身组合体等常规气动布局, 高超声速气动特性工程计算方法已趋于成熟并得到广泛应用. 然而, 面对部件间存在显著气动干扰的高压捕获翼新型气动布局, 传统工程计算方法面临显著的局限性. 为解决这一问题, 文章结合计算流体力学(CFD)技术、本征正交分解(POD)方法与径向基函数代理模型, 提出了一种高效准确的高压捕获翼表面流场快速预测方法, 并据此构建了完整的气动特性快速预测框架. 基于高压捕获翼基本设计原理, 综合考虑了关键几何参数和来流条件的影响, 对典型构型捕获翼下表面的复杂压强分布进行了预测验证. 研究结果表明, 当保留13个POD基模态时, 所提出的快速预测方法与直接CFD计算结果相比, 翼面压强预测的平均相对误差仅为1.6%, 气动力预测误差更是低至0.3%. 值得注意的是, 进一步增加POD基模态数量对预测精度的提升效果并不显著. 该方法在确保高精度流场重建和预测的同时, 显著提升了计算效率, 为高压捕获翼构型的优化设计提供了可靠的技术支持.Abstract: The rapid prediction of aerodynamic characteristics for hypersonic vehicles is a critical component in their multidisciplinary optimization design. Currently, engineering calculation methods for hypersonic aerodynamic characteristics have matured and are widely applied to conventional aerodynamic configurations such as lifting bodies and wing-body combinations. These methods are highly efficient and provide reasonably accurate results for traditional designs. However, traditional engineering calculation methods face significant limitations when dealing with novel aerodynamic configurations like high-pressure capturing wing (HCW), where there is substantial aerodynamic interaction between components. This limitation stems from the inability of conventional methods to accurately capture the complex flow interactions and pressure distributions associated with such advanced configurations. To address this issue, this paper proposes an efficient and accurate rapid prediction method for the surface flow field of HCW by integrating computational fluid dynamics (CFD) technology, proper orthogonal decomposition (POD) method, and radial basis function surrogate modeling. Based on this, a comprehensive framework for rapid prediction of aerodynamic characteristics is constructed. Considering the basic design principles of HCW and the influence of key geometric parameters and inflow conditions, the complex pressure distributions on the lower surface of the capturing wing for a typical HCW configuration were predicted and validated. The research results indicate that when 13 POD basis modes are retained, the average relative error in wing surface pressure prediction compared to direct CFD calculation results is only 1.6%, and the aerodynamic force prediction error is as low as 0.3%. It should be noted that further increasing the number of POD basis modes does not significantly enhance prediction accuracy. This method ensures high-accuracy flow field reconstruction and prediction while significantly improving computational efficiency, providing reliable technical support for the design optimization of HCW configurations. The proposed approach has the potential to be extended to other complex aerodynamic configurations with strong interaction effects, thereby contributing to the advancement of hypersonic vehicle design methodologies.