A data-driven Reynolds-number-dependent model for turbulent mean flow prediction in circular jets
A data-driven Reynolds-number-dependent model for turbulent mean flow prediction in circular jets
复制标题
数据驱动的雷诺数相关模型，用于预测圆形射流中的湍流平均流量
DOI：
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Yingzheng Liu
中科院分区：
文献类型：
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作者：
Zhiyang Li;Chuangxin He;Yingzheng Liu
本文提出了一个数据驱动的湍流模型，用于预测在较宽的雷诺数范围内的湍流圆形射流的平均流动。主要公式改编自众所周知的k-ε模型（其中k是湍流动能，ε是耗散率），模型常数随Re变化。采用Tam-Thies修正的k-ε模式，通过基于集合卡尔曼滤波的数据同化优化模式常数，以减小模式预测与实验数据之间的偏差。收敛射流在Re = 10 700，20 100，和95 500的模型常数拟合使用对数曲线相对于Re，以获得一个通用的公式，用于预测在各种流动条件下的射流平均流量。采用拟合的模型常数建立的k-ε-Re模型，在不同Re下，能较准确地预测收敛射流和孔板射流的平均流动。当k-ε-Re模型直接应用于管道射流时，在高雷诺数（目前Re ≥ 21 000）下，与默认k-ε模型相比，可以得到更好的预测结果。当Re = 6000和16000时，当5 ≤ x/D ≤ 15时，计算结果与实验值有一定的偏差。进一步的改进可以通过同化管道射流数据的拟合系数来实现。k-ε-Re模型具有较好的通用性，在中高Re（≥ 21 000）条件下可以较好地预测不同喷嘴的平均流场，而在低Re条件下，可以根据具体喷嘴类型进行数据同化和重新校准，进一步提高模型的精度。
This paper proposes a data-driven turbulence model for predicting the mean flow in turbulent circular jets over a wide range of Reynolds numbers (Re). The main formulation is adapted from the well-known k–ε model (where k is the turbulent kinetic energy, and ε is the dissipation rate) with a set Re-dependent variation of the model constants. The k–ε model with Tam–Thies correction is applied with model constants optimized using data assimilation based on the ensemble Kalman filter to minimize the deviation between the model prediction and experimental data. The model constants of converging jets at Re = 10 700, 20 100, and 95 500 are fitted using logarithmic curves with respect to Re to obtain a universal formulation for predicting the jet mean flow under various flow conditions. The model using the fitted model constants, named the k–ε–Re model, can accurately predict the mean flow in both converging and orifice jets at various Re. While the k–ε–Re model is directly applied to the pipe jets, much better prediction can be obtained at high Reynolds numbers (Re ≥ 21 000 presently) compared with the default k–ε model. However, certain discrepancy with experimental data is observed at 5 ≤ x/D ≤ 15 at Re = 6000 and 16 000. Further improvement can be achieved by assimilating the fitting coefficients based on the pipe jet data. The k–ε–Re model is adequately generalizable and can predict the mean flow in different circular jets at a moderate or high Re (≥ 21 000), while further improvement can be obtained by the data assimilation and recalibration based on the specific nozzle type at a small Re.
影响因子：
4.6
作者：
Chuangxin He;Peng Wang;Yingzheng Liu;L. Gan
通讯作者：
Chuangxin He;Peng Wang;Yingzheng Liu;L. Gan