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基于点云编码器的结构不确定性机翼跨音速颤振边界预测

TRANSONIC FLUTTER BOUNDARY PREDICTION OF WINGS WITH STRUCTURAL UNCERTAINTIES BASED ON POINT CLOUD ENCODER

  • 摘要: 针对跨音速非定常气动力计算成本高, 且现有降阶模型难以考虑结构特性变化下非定常气动力预测的局限性, 本文提出了一种基于点云编码器和高低精度数据融合的变结构特性非定常气动力降阶模型及颤振预测方法. 以AGARD445.6机翼为研究对象, 基于偶极子格网法快速计算低精度非定常气动力, 结合CFD中给定模态运动的高精度非定常气动力数据作为标签数据, 分别针对结构参数确定与不确定性两种情形, 构建了用于颤振预测的长短期记忆网络(LSTM)模型. 首先建立了相同结构特性的变马赫数降阶模型(ROM1), 实现了Ma = 0.78-0.95不同马赫数下非定常气动力与颤振边界的准确快速预测. 之后针对结构不确定性需求, 在机翼模态振型发生改变的情况下, 发展了点云编码器方法提取变模态振型的空间几何特征, 建立了结构不确定性机翼在变马赫数工况下的降阶模型(ROM2), 并进行了颤振边界快速准确预测. 结果表明, ROM1在不同马赫数的测试集上的颤振速度预测误差小于8%, ROM2在不同结构和马赫数的测试集上的颤振速度预测误差小于11%. 在结构参数不确定性下, 不同马赫数工况的预测时间仅占CFD方法的0.2%, 在初步设计阶段结构参数变化时, 有效提升了机翼的跨声速非线性颤振预测和工程气动弹性设计的效率.

     

    Abstract: To address the high computational cost of transonic unsteady aerodynamic calculations and the limitations of existing reduced-order models in predicting unsteady aerodynamics under varying structural properties, this paper proposes a variable structural property unsteady aerodynamic reduced-order model and flutter prediction method based on a point cloud encoder and multi-fidelity data fusion. Taking the AGARD 445.6 wing as the research object, low-fidelity unsteady aerodynamic forces are rapidly calculated based on the Doublet Lattice Method (DLM), which are then combined with high-fidelity unsteady aerodynamic forces from CFD with prescribed modal motions as label data to construct Long Short-Term Memory (LSTM) models for flutter prediction under both deterministic and uncertain structural parameter scenarios. First, a reduced-order model (ROM1) for identical structural properties with variable Mach numbers is established, achieving accurate and rapid prediction of unsteady aerodynamics and flutter boundaries across different Mach numbers from Ma = 0.78 to 0.95. Subsequently, to address structural uncertainty requirements, a point cloud encoder method was developed to extract the spatial geometric features of variable modal shapes when the wing’s modal shapes change. A reduced-order model (ROM2) was established for wings with structural uncertainty under variable Mach number conditions, and rapid and accurate predictions of flutter boundaries were carried out. The results show that the flutter speed prediction error of ROM1 on the test set for different Mach numbers is less than 8%, and the flutter speed prediction error of ROM2 on the test set for different structures and Mach numbers is less than 11%. Under structural parameter uncertainty, the prediction time for various Mach number conditions is only 0.2% of that required by the CFD method. This effectively enhances the efficiency of transonic nonlinear flutter prediction and engineering aeroelastic design when structural parameters change during the preliminary design stage.

     

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