Sen Li, Xu Zhang, Wenwu Zhou, Chuangxin He, Yingzheng Liu
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引用次数: 0
摘要
本研究采用连续的邻接数据同化(DA)算法来增强对横流中倾斜圆形射流(JICF)的三维流动行为的预测。为了纠正布森斯克近似产生的模型形式误差,实施了力校正,并纳入了涡流粘度的线性部分以实现数值稳定性。从理论上推导出的 DA 模型可最大限度地减少粒子图像测速仪(PIV)测量与主-关节系统数值预测之间的差异,从而确定力校正的最佳贡献。观测数据是通过在 JICF 中心面进行平面 PIV 测量获得的,速度比固定为 1.2,体积雷诺数为 150,000。使用 PIV 结果验证了延迟脱离涡模拟,并将其作为评估 DA 方法重建能力的补充数据。研究探讨了数据同化程序中的各种正则化参数,强调了它们对涡流粘度、校正力和整体流动预测精度的影响。研究结果强调了正则化在促进优化场的平滑性方面的有效性,从而减轻了过拟合和不规则解。对关键流动特征(包括反向旋转涡对和雷诺应力强迫)的深入分析,为数据同化程序所实现的精度提供了启示。尽管测量数据有限,但研究证明了所提出的方法有能力成功恢复全球流场。
Particle image velocimetry, delayed detached eddy simulation and data assimilation of inclined jet in crossflow
This research employs a continuous adjoint data assimilation (DA) algorithm to enhance the prediction of three-dimensional flow behavior in the inclined round jet in crossflow (JICF). To rectify model-form errors arising from the Boussinesq approximation, a force correction is implemented, and the linear part of the eddy viscosity is incorporated for numerical stability. The DA model is theoretically derived to minimize discrepancies between particle image velocimetry (PIV) measurement and the numerical predictions of the primary-adjoint system, thus enabling determination of the optimal contribution of the force correction. Observational data are acquired through planar PIV measurement in the centerplane of JICF with a fixed velocity ratio of 1.2 and a bulk Reynolds number of 150,000. Delayed detached eddy simulation is validated using PIV results and serves as supplementary data for evaluating the reconstruction capabilities of the DA method. The research explores various regularization parameters in the data assimilation procedure, emphasizing their impact on eddy viscosity, correction force, and overall flow prediction accuracy. The findings underscore the effectiveness of regularization in promoting smoothness in the optimized field, thereby mitigating overfitting and irregular solutions. In-depth analyses of critical flow features, including counter-rotating vortex pairs and Reynolds stress forcing, provide insights into the accuracy achieved by the data assimilation procedure. Despite limited measurement data, the study demonstrates the capability of the presented method to successfully recover global flow fields.
Journal of VisualizationCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY
CiteScore
3.40
自引率
5.90%
发文量
79
审稿时长
>12 weeks
期刊介绍:
Visualization is an interdisciplinary imaging science devoted to making the invisible visible through the techniques of experimental visualization and computer-aided visualization.
The scope of the Journal is to provide a place to exchange information on the latest visualization technology and its application by the presentation of latest papers of both researchers and technicians.