基于动力学模态分解的大跨度平屋盖风压场研究

RESEARCH ON WIND PRESSURE FIELD OF LARGE-SPAN FLAT ROOF BASED ON DYNAMIC MODE DECOMPOSITION

  • 摘要: 采用经过嵌入维数改进的动力学模态分解(DMD)方法和本征正交分解(POD)方法对大跨度平屋面的随机风压场进行分析。结果表明:利用Takens嵌入定理来增加原始快照矩阵的空间维数,能够挖掘风洞试验数据集中隐藏的模糊动态特征;POD和DMD的模态分布均能够反映脉动压力场典型漩涡的主要特征,但POD的每个模态包含多个频率的信息,这在一定程度上让POD的模态成为多个频率段脉动的耦合,而DMD方法分解模态是单频模态并且可以得到每个模态的稳定性。相同比例的POD模态所占的能量比例大于DMD模态结果,但当使用相同比例的模态进行脉动风压场重构时,DMD方法比POD方法的重构结果更能够描述和契合原始脉动压力场的局部特征,这是由于DMD方法是直接对压力场进行重建,而POD方法主要是重建能量场,因此在揭示随机风压场时空演化特征,DMD方法更具优势。

     

    Abstract: The dynamic mode decomposition (DMD) method improved by embedded dimension and the proper orthogonal decomposition (POD) method are used to analyze the random wind pressure field of a large-span flat roof. The results show that the fuzzy dynamic features hidden in the wind tunnel test data can be discovered by using the Takens embedding theorem to increase the spatial dimension of the original snapshot matrix. The modal distributions of POD and DMD can reflect the main characteristics of typical vortices in a fluctuating pressure field. However, each mode of POD contains the information of multiple frequencies, which to a certain extent makes the mode of POD become the fluctuating coupling of multiple frequency bands. The mode decomposed by DMD method is a single-frequency mode and the stability of each mode can be obtained. At the same proportion, POD modes contain more energy than DMD modes. But when the same proportion of modes are used to reconstruct the fluctuating wind pressure field, the reconstruction results of DMD method can better describe and fit the local characteristics of the original fluctuating pressure field than those of POD method. This is because DMD method reconstructs the pressure field directly, while POD method mainly reconstructs the energy field. Therefore, the DMD method has more advantages in revealing the spatial-temporal evolution characteristics of a random wind pressure field.

     

/

返回文章
返回