This paper proposes a novel Inertial Coordinates Independent (ICI) aerodynamic model using the condensed degrees of freedom (DOFs) technology. Through a management of the ICI inputs, the aerodynamic forces will not be restricted by the selection of inertial coordinates and will have the same prediction effect for different coordinates. In addition, by including the self-excited force and the buffeting force, and by reducing the appropriate number of aerodynamic DOF, the ability of the proposed model to describe the nonlinear aerodynamic characteristics such as memory effect is enhanced. It can be directly applied to any non-stationary inputs in the time domain, and improve its applicability to structures with large deformations. With the self-developed computational fluid dynamics (CFD) software, the aerodynamic to-be-identified parameters can be identified by a data-driven method, and the correctness of each term of this model has been verified. Finally, the overall accuracy of the proposed method is examined by comparing both the self-excited force and the hysteresis patterns of ICI model with those results based on a series of CFD simulations of a streamlined bridge deck section.

中文翻译：

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基于压缩自由度技术的新型颤振和抖振非线性空气动力学模型

本文提出了一种使用压缩自由度 (DOF) 技术的新型惯性坐标独立 (ICI) 空气动力学模型。通过对 ICI 输入的管理，气动力将不受惯性坐标选择的限制，对不同坐标具有相同的预测效果。此外，通过包含自激力和抖振力，并通过减少适当的气动自由度数，提高了模型描述记忆效应等非线性气动特性的能力。它可以直接应用于时域中的任何非平稳输入，提高了对大变形结构的适用性。借助自主研发的计算流体动力学（CFD）软件，通过数据驱动的方法可以识别出气动待识别参数，验证了该模型各项的正确性。最后，通过将 ICI 模型的自激力和滞后模式与基于流线型桥面截面的一系列 CFD 模拟的结果进行比较，来检验所提出方法的整体准确性。