Effect of von Karman length scale in scale adaptive simulation approach on the prediction of supersonic turbulent flow
Effect of von Karman length scale in scale adaptive simulation approach on the prediction of supersonic turbulent flow
复制标题
尺度自适应模拟方法中冯卡门长度尺度对超音速湍流预测的影响
DOI:
10.1016/j.ast.2019.01.030
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发表时间:
2019-03
影响因子:
5.6
通讯作者:
Sun Jian Hong
中科院分区:
文献类型:
--
作者:
Xu Chang Yue;Zhang Tong;Yu Yuan Yuan;Sun Jian Hong
Numerical investigations of the supersonic axisymmetric base flow at Mach number 2.46 and Reynolds number 2.858× 10 6 are carried out using the scale-adaptive simulation (SAS) approach. To achieve SAS computation, three mathematical forms of von Karman length scale are utilized. The first one is calculated from the strain rate tensor and second derivative of the velocity field (this SAS can be marked as “SAS-1”). Computation of the second one is employed using the vorticity and its first derivative (this SAS can be denoted as “SAS-2”). The third one is computed from the vorticity and the second derivative of the velocity field (this SAS can be named as “SAS-3”). Their effects on the quantitative predictions are assessed. Two inflow conditions are also investigated, ie, inflow condition with/without turbulent-boundary-layer profiles. Results show that the inflow conditions have the significant effects on the base-pressure and streamwise velocity distributions, and the predicted results at the inflow condition with profiles show better agreement with experimental data than that at the inflow condition without profiles. The inflow conditions and von Karman length scales only have the relatively slight effects on the radial velocity distributions. Similarly, at the inflow condition with profiles, the base-pressure distributions are also not sensitive to mathematical forms of von Karman length scale. More comparisons reveal that the best predictions can be obtained by SAS-2 and SAS-3. It may be associated with the vortex stretching effects explicitly considered in the von Karman length scales of SAS-2 and SAS-3. Although the mean flow field predicted by SAS-2 is slightly better than that obtained by SAS-3. However, SAS-3 can give the slightly better predictions for the Reynolds stresses than SAS-2.
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影响因子:
2.5
作者:
J. Herrin;J. Dutton
通讯作者:
J. Herrin;J. Dutton
影响因子:
2.5
作者:
R. Benay;P. Servel
通讯作者:
R. Benay;P. Servel
影响因子:
5.6
作者:
F. Nicolás-Pérez;F. Velasco;J. García-Cascales;R. Otón-Martínez;A. López-Belchí;D. Moratilla;F. Rey
通讯作者:
F. Nicolás-Pérez;F. Velasco;J. García-Cascales;R. Otón-Martínez;A. López-Belchí;D. Moratilla;F. Rey
DOI:
10.1201/9781420050288
发表时间:
1999-11
期刊:
--
影响因子:
--
作者:
T. Papanastasiou;G. Georgiou;A. Alexandrou
通讯作者:
T. Papanastasiou;G. Georgiou;A. Alexandrou
影响因子:
3.7
作者:
D. J. Hill;C. Pantano;D. Pullin
通讯作者:
D. J. Hill;C. Pantano;D. Pullin