Flow enhancement of tomographic particle image velocimetry measurements using sequential data assimilation
Flow enhancement of tomographic particle image velocimetry measurements using sequential data assimilation
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DOI：
10.1063/5.0082460
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发表时间：
2022-03
影响因子：
4.6
通讯作者：
Chuangxin He;Peng Wang;Yingzheng Liu;L. Gan
中科院分区：
文献类型：
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作者：
Chuangxin He;Peng Wang;Yingzheng Liu;L. Gan
利用层析粒子图像测速仪(TOMO-PIV)对圆形射流的三维流场进行了序贯数据同化。这项工作的重点是深入分析流动增强和根据体积流量测量数据确定压力。该喷嘴从内径为[公式：见文本]20 mm的圆形喷嘴中喷出。包括两个高速摄像机的分屏配置被用来从四个不同的视角捕捉粒子图像，用于在Tomo-PIV测量中对体素进行层析重建。还进行了平面PIV，以获得用于验证的基准二维速度场。采用基于伴随的序贯DA方法，利用阈值函数注入测量不确定度，恢复了高保真、低测量误差的流场。压力由直接模式或分离模式确定，直接模式直接在DA求解器中实现，分离模式包括求解DA恢复的流场上的泊松方程。顺序DA恢复了由于观测的间歇性限制而具有分段平滑时间变化的高信噪比流场，而仅选择观测实例上的场的时间序列作为DA输出。误差显著减小，DA改善了三维流场的发散条件。DA还增强了涡旋结构的动力学特征，两种模式确定的压强都成功地捕捉到了涡环的下游对流特征。
Sequential data assimilation (DA) was performed on three-dimensional flow fields of a circular jet measured by tomography particle image velocimetry (tomo-PIV). The work focused on an in-depth analysis of the flow enhancement and the pressure determination from volumetric flow measurement data. The jet was issued from a circular nozzle with an inner diameter of [Formula: see text] 20 mm. A split-screen configuration including two high-speed cameras was used to capture the particle images from four different views for a tomography reconstruction of the voxels in the tomo-PIV measurement. Planar PIV was also performed to obtain the benchmark two-dimensional velocity fields for validation. The adjoint-based sequential DA scheme was used with the measurement uncertainty implanted using a threshold function to recover the flow fields with high fidelity and fewer measurement errors. The pressure was determined by either the direct mode, with implementation directly in the DA solver, or by the separate mode, which included solving the Poisson equation on the DA-recovered flow fields. Sequential DA recovered high signal-to-noise flow fields that had piecewise-smooth temporal variations due to the intermittent constraints of the observations, while only the temporal sequence of the fields at the observational instances was selected as the DA output. Errors were significantly reduced, and DA improved the divergence condition of the three-dimensional flow fields. DA also enhanced the dynamical features of the vortical structures, and the pressure determined by both modes successfully captured the downstream convection signatures of the vortex rings.