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介绍了基于当地变量的γ-Reθ转捩模型,并将该模型应用到后掠机翼的转捩预测和人工转捩最佳粗糙带高度以及人工转捩技术能够模拟的大气飞行雷诺数的确定中。为检验γ-Reθ转捩模型对后掠机翼转捩的预测能力,对ONERA M6机翼和DLR-F4标模机翼进行了边界层转捩预测,采用结构化网格和有限体积法求解雷诺平均Navier-Stokes(RANS)方程,得到了机翼表面的摩擦阻力系数分布,从而可以得到相应的转捩位置,预测得到的转捩位置与试验结果比较吻合,说明该模型对后掠机翼转捩预测是可信的。最后在DLR-F4标模机翼上表面固定了粗糙带,通过相同的方法得到了转捩位置,从而确定了马赫数为0.785、雷诺数为3.0×106时最佳粗糙带高度为0.11mm;通过不断增大雷诺数使自由转捩位置不断向前缘移动,验证了人工转捩对大气飞行雷诺数的模拟能力。结果表明,在最佳粗糙带高度为0.11mm下,可以实现对大气飞行高雷诺数的模拟。
The γ-Reθ transition model based on local variables is introduced, and the model is applied to determine the Reynolds number of the air-to-air flight that can be simulated by the transition forecast of the swept-back wing and the optimal roughness height of the artificial turret and artificial turndown technology in. In order to test the predicting ability of γ-Reθ transition model for the swept-back wing transition, the boundary layer transition was predicted for ONERA M6 wing and DLR-F4 model wing. Structured grids and finite volume method Reynolds averaged Navier-Stokes (RANS) equation, the friction coefficient distribution of the wing surface is obtained, and the corresponding transition position can be obtained. The predicted transition position is in good agreement with the test result, The turnaround forecast is credible. Finally, the rough band was fixed on the upper surface of DLR-F4 model wing, and the rotation position was obtained by the same method, thus the Mach number was 0.785 and the optimum roughness height was 0.11mm when the Reynolds number was 3.0 × 106. By continuously increasing the Reynolds number, the position of free transfer was continuously moved to the front edge, which verified the artificial ability of simulation to simulate the Reynolds number of atmospheric flight. The results show that the simulation of high Reynolds number of atmospheric flight can be achieved with the best roughness height of 0.11mm.