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基于混合雷诺平均/高精度隐式大涡模拟方法的高升力体气动噪声模拟

葛明明 王圣业 王光学 邓小刚

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基于混合雷诺平均/高精度隐式大涡模拟方法的高升力体气动噪声模拟

葛明明, 王圣业, 王光学, 邓小刚

Aeroacoustic simulation of the high-lift airfoil using hybrid reynolds averaged Navier-Stokes/high-order implicit large eddy simulation method

Ge Ming-Ming, Wang Sheng-Ye, Wang Guang-Xue, Deng Xiao-Gang
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  • 发展了基于七阶精度混合型耗散紧致格式(HDCS)的混合雷诺平均(RANS)/高精度隐式大涡模拟(HILES)模型(HRILES), 并结合Ffowcs Williams-Hawkings (FWH)声比拟方法对30P30N 高升力体气动噪声问题进行了模拟. 首先对雷诺数$ Re_{d} = 4.3\times10^4$的单圆柱绕流算例开展验证, 并与传统的延迟分离涡模拟(DDES) 模型进行对比. 结果表明HRILES模型具有对亚临界态尾迹区转捩流动的模拟能力, 平均阻力系数与阻力均方根值和实验结果符合更好, 结合FWH 声比拟方法得到了合理的远场声压级(SPL)的功率谱密度(PSD)分布. 然后将其应用于30P30N 高升力体气动噪声算例模拟, 结果表明HRILES模型准确预测缝翼凹腔剪切层各站位的平均速度、涡量和湍动能分布, 壁面脉动压力谱分布与实验符合较好, 近、远场噪声频谱准确预测了缝翼低频窄带噪声, 并得到了合理的噪声辐射指向性分布.
    A hybrid RANS/HILES method (HRILES) is developed by combining the RANS-SST model and high order implicit large eddy simulation method (HILES) and employed with the Ffowcs Williams-Hawkings (FW-H) equation to predict the slat noise of 30P30N high-lift airfoil. Comparison has been made between the HRILES method and the traditional DDES based on the full-turbulence model SST by simulating the single cylinder case with $Re_{{d}}=4.3\times10^4$. The HRILES method is able to predict the transition phenomenon and the small-scale separation bubble in the sub-critical wake region while the DDES can't and get a better mean wall pressure distribution than DDES. The amplitude and frequency spectrum of the far-field sound pressure level are in good agreement with the experimental data. In the simulation of 30P30N high-lift airfoil, the famous IDDES model is also used for comparison, both results are compared with experimental measurements. The computational mesh is provided by Japan Aerospace Exploration Agency (JAXA) in the Workshop on Benchmark problems for Airframe Noise Computations (BANC). The HRILES method obtains quantitative agreement with experimental data in terms of mean wall pressure coefficient, frequency spectrum of pressure fluctuations on the slat surface, and the mean flow statistics in the slat cusp shear layer. The IDDES model slightly underestimate the suction effect on the upper surface of the slat, and delays the instabilities in the slat cusp shear layer. The near-field noise spectra are compared with measurements obtained in JAXA low-speed Wind Tunnel. Narrow band peaks present are well recovered by both methods, while IDDES model overestimate the broadband noise. Far-field noise directivity results of every components, filtered in the band [256Hz–10KHz], are compared with each other, and the slat cove is confirmed to dominate the sound noise levels. The slat and flap noises show a typical dipole distribution, while the main wing noise's directivity is not apparent. Computational results show that the HRILES method, as one kind of generalized Hybrid RANS/LES method, HRILES can smoothly switch between the SST model and the HILES method. HRILES has the high-resolution simulation capability of the HILES in the LES region, and can reduce the requirements of the HILES method on the near-wall grid distribution by using the SST model in the inner boundary layer. As a result, the HRILES method has advantages in simulations at high reynolds numbers and aeroacoustic problems. Further research will be carried out in the applications at higher reynolds number flows with complex geometry in the future.
      通信作者: 邓小刚, xgdeng2000@vip.sina.com
    • 基金项目: 国家自然科学基金(批准号: 11572348)和国防科技大学重大应用基础研究项目(批准号: ZDYYJCYJ20140101)资助的课题
      Corresponding author: Deng Xiao-Gang, xgdeng2000@vip.sina.com
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 11572348) and the Basic Research Foundation of the National University of Defense Technology of China (Grant No. ZDYYJCYJ20140101)
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    Ishiko K, Shimada T 2010 48th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition Orlando, Florida, January 4−7, 2010 p923

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    Rizzetta D P, Visbal M R, Morgan P E 2008 Prog. Aerosp. Sci. 44 397Google Scholar

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    Deng X, Min Y, Mao M, Liu H, Tu G Zhang H 2013 J. Comput. Phys. 239 90Google Scholar

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    Spalart P, Jou W, Strelets M, Allmaras S 1997 Advances in DNS/LES (Columbus: Creyden Press) p137

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    Spalart P, Deck S, Shur M, Squires K, Strelets M, Travin A 2006 Theor. Comput. Fluid Dyn. 20 181Google Scholar

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    Shur M L, Spalart P R, Strelets M K, et al. 2008 Int. J. Heat Fluid Flow 29 1638Google Scholar

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    Deng X, Jiang Y, Mao M, Liu H, Li S, Tu G 2015 Comput. Fluids 116 29Google Scholar

    [26]

    Wang S, Deng X, Wang G, Xu D, Wang D 2016 Inter. J. Comput. Fluid Dynamics 30 7Google Scholar

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    Piomelli U 2008 Prog. Aerosp. Sci. 44 437Google Scholar

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    Kato C, Iida A, Takano Y, Fujita H, Ikegawa M 1993 31wst Aerospace Sciences Meeting & Exhibit Reno, NV, January 11−14, 1993 p145

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    Jacob M, Boudet J, Casalino D, Michard M 2005 Theiret. Comput. Fluid Dynamics 19 171Google Scholar

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    Terracol M, Manoha E, Murayama M, Yamamoto K, Kazuhisa A, Kentaro T 2015 21st AIAA/CEAS Aeroacoustics Conference Dallas, TX, June 22−26, 2015 p3132

    [35]

    Pascioni K, Cattafesta L, Choudhari M 2014 20th Aiaa/ceas Aeroacoustics Conference Atlanta, Georgia, June 16−20, 2014 p3062

    [36]

    Murayama M, Nakakita K, Yamamoto K, Ura H, Ito Y 2014 20th AIAA/CEAS Aeroacoustics Conference Atlanta, GA, June 16−20 2014 p2014

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    Gao J, Li X, Lin D 2017 23th AIAA/CEAS Aeroacoustics Conference Denver, Colorado, June 5−9, 2017 p3363

    [38]

    Zhang Y, Chen H, Wang K, Wang M 2017 AIAA Journal 55 4219Google Scholar

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    Choudhari M, Lockard D 2015 22ed AIAA/CEAS Aeroacoustics Conference Dallas, TX, June 22−26, 2015 p2844

  • 图 1  圆柱表面平均压力系数分布

    Fig. 1.  Mean wall pressure coefficient distribution of the rod

    图 2  流线分布 (a) HRILES; (b) SST-DDES

    Fig. 2.  Distribution of streamlines: (a) HRILES; (b) SST-DDES

    图 3  远场$ \theta = 90^\circ $, $ r = 180d $观测点声压级功率谱密度

    Fig. 3.  Farfield acoustic result of the rod: PSD at ($ \theta = 90^\circ,$ $ r = 180d $).

    图 4  30P30N计算网格

    Fig. 4.  Mesh of 30P30N airfoil

    图 5  $ QC/U_{\infty} = 5000 $等值面 (a) IDDES; (b) HRILES

    Fig. 5.  The isosurfaces of the Q-criterion ($ QC/U_{\infty} = 5000 $): (a) IDDES; (b) HRILES

    图 6  平均展向涡量云图 (a) IDDES; (b) HRILES

    Fig. 6.  Contours of meanmean spanwise vorticity: (a) IDDES; (b) HRILES

    图 7  平均流线分布 (a) 缝翼; (b) 襟翼

    Fig. 7.  Distribution of streamlines: (a) Slat; (b) flap

    图 8  壁面压力系数分布

    Fig. 8.  Distribution of wall pressure coefficient

    图 9  缝翼表面压力系数脉动均方根分布

    Fig. 9.  RMS of the fluctuating pressure coefficient on the surface of the slat

    图 10  各个站位的平均速度分布

    Fig. 10.  Mean velocity magnitudes along the seven lines across

    图 11  各个站位的平均展向涡量分布

    Fig. 11.  Mean spanwise vorticity along the seven lines across

    图 12  各个站位的平均湍动能分布

    Fig. 12.  Mean turbulent kinetic energy along the seven lines across

    图 13  脉动压力功率谱密度分布 (a) $ P_1 $; (b) $ P_4 $

    Fig. 13.  Frequency spectra of pressure fluctuations: (a) $ P_1 $; (b) $ P_4 $

    图 14  瞬态脉动压力云图

    Fig. 14.  Contours of pressure fluctuation

    图 15  $ r = 2.19C,\; \theta = 287.5^\circ $观测点声压级功率谱

    Fig. 15.  Power spectra density of sound pressure level at $ r = 2.19C,\; \theta = 287.5^\circ $

    图 16  $ r = 10C $, 远场声压级指向图

    Fig. 16.  Directivity of SPL at $ r = 10C $

    图 17  各部件远场($ r = 10C $)声压级指向对比图 (a) IDDES; (b) HRILES

    Fig. 17.  Directivity of components' SPL at $ r = 10C $: (a) IDDES; (b) HRILES

    表 1  单圆柱算例流动参数统计结果

    Table 1.  Statistical results of aerodynamic coefficients for the single cylinder

    CD, ave CD, rms Sr θsap
    HRILES 1.39 0.13 0.186 81.4
    SST-DDES 1.08 0.10 0.202 80.3
    LES[32] 1.24 0.10 0.187
    Exp.[31] 1.35 0.16 0.19
    下载: 导出CSV
  • [1]

    Busquin M 2001 http://www.acare4europe.org/sites/acare4europe.org/files/document/Vision%2020200.pdf [2019-5-22]

    [2]

    Dobrzynski W 2010 J. Aircraft 47 2

    [3]

    Pott P, Alvarez G, Dobrzynski W 2003 9th AIAA/CEAS Aeroacoustics Conference and Exhibit South Carolina, USA, May 12–14, 2003 p3228

    [4]

    Souza D, Rodríguez D, Simões L, Medeiros M 2015 Aerosp. Sci. Technol. 44 108Google Scholar

    [5]

    Choudhari M, Lockard D, Khorrami M, Mineck R 2011 INTER-NOISE and NOISE-CON Congress and Conference Proceedings Reston, VA, September 4−7, 2011 p3583

    [6]

    Slotnick J, Khodadoust A, Alonso J http://ntrs.nasa.gov/search.jsp?=20140003093/ [2019-5-22]

    [7]

    Grinstein F, Fureby C 2002 J. Fluids Eng.-Tran. ASME 124 848Google Scholar

    [8]

    Hahn M, Drikakis D 2005 Int. J. Numner. Methods Fluids 47 971Google Scholar

    [9]

    Fureby C, Grinstein F 1999 AIAA J. 37 544Google Scholar

    [10]

    Fureby C, Grinstein F 2002 J. Comput. Phys. 181 68Google Scholar

    [11]

    Ishiko K, Ohnishi N, Sawada K 2013 Aiaa Aerospace Sciences Meeting & Exhibit Reno, Nevada, January 9−12, 2006 p703

    [12]

    Ishiko K, Shimada T 2010 26th AIAA Applied Aerodynamics Conference Honolulu, Hawaii, August 18−21, 2008 p6579

    [13]

    Ishiko K, Shimada T 2010 48th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition Orlando, Florida, January 4−7, 2010 p923

    [14]

    Rizzetta D P, Visbal M R, Morgan P E 2008 Prog. Aerosp. Sci. 44 397Google Scholar

    [15]

    Deng X, Min Y, Mao M, Liu H, Tu G Zhang H 2013 J. Comput. Phys. 239 90Google Scholar

    [16]

    Jiang Y, Mao M, Deng X, Liu H 2014 Comput. Fluids 104 73Google Scholar

    [17]

    Jiang Y, Mao M, Deng X, Liu H 2015 Adv. Appl. Math. Mech. 7 407Google Scholar

    [18]

    Mao M, Jiang Y, Deng X, Liu H 2016 Adv. Appl. Math. Mech. 8 236Google Scholar

    [19]

    Argyropoulos C D, Markatos N C 2015 Appl. Math. Modell. 39 693Google Scholar

    [20]

    Spalart P, Jou W, Strelets M, Allmaras S 1997 Advances in DNS/LES (Columbus: Creyden Press) p137

    [21]

    Spalart P, Deck S, Shur M, Squires K, Strelets M, Travin A 2006 Theor. Comput. Fluid Dyn. 20 181Google Scholar

    [22]

    Shur M L, Spalart P R, Strelets M K, et al. 2008 Int. J. Heat Fluid Flow 29 1638Google Scholar

    [23]

    Nichols R 2003 41st Aerospace Sciences Meeting & Exhibit Reno, Nevada, January 6−9, 2003 p0083

    [24]

    Nichols R 2005 43rd Aiaa Aerospace Sciences Meeting & Exhibit Reno, Nevada, January 6−9, 2005 p498

    [25]

    Deng X, Jiang Y, Mao M, Liu H, Li S, Tu G 2015 Comput. Fluids 116 29Google Scholar

    [26]

    Wang S, Deng X, Wang G, Xu D, Wang D 2016 Inter. J. Comput. Fluid Dynamics 30 7Google Scholar

    [27]

    Piomelli U 2008 Prog. Aerosp. Sci. 44 437Google Scholar

    [28]

    Francescantonio P 1997 J. Sound Vibration 202 491Google Scholar

    [29]

    Kato C, Iida A, Takano Y, Fujita H, Ikegawa M 1993 31wst Aerospace Sciences Meeting & Exhibit Reno, NV, January 11−14, 1993 p145

    [30]

    Mustafa S, Tahir Y 2002 AIAA J. 40 1257Google Scholar

    [31]

    Szepessy S, Bearman P 1992 J. Fluid Mech. 234 91

    [32]

    Seo J, Chang K, Moon Y 2006 12th AIAA/CEAS Aeroacoustics Conference Cambridge, Massachusetts, May 8−10, 2006 p2573

    [33]

    Jacob M, Boudet J, Casalino D, Michard M 2005 Theiret. Comput. Fluid Dynamics 19 171Google Scholar

    [34]

    Terracol M, Manoha E, Murayama M, Yamamoto K, Kazuhisa A, Kentaro T 2015 21st AIAA/CEAS Aeroacoustics Conference Dallas, TX, June 22−26, 2015 p3132

    [35]

    Pascioni K, Cattafesta L, Choudhari M 2014 20th Aiaa/ceas Aeroacoustics Conference Atlanta, Georgia, June 16−20, 2014 p3062

    [36]

    Murayama M, Nakakita K, Yamamoto K, Ura H, Ito Y 2014 20th AIAA/CEAS Aeroacoustics Conference Atlanta, GA, June 16−20 2014 p2014

    [37]

    Gao J, Li X, Lin D 2017 23th AIAA/CEAS Aeroacoustics Conference Denver, Colorado, June 5−9, 2017 p3363

    [38]

    Zhang Y, Chen H, Wang K, Wang M 2017 AIAA Journal 55 4219Google Scholar

    [39]

    Pascioni K, Cattafesta L 2016 22ed AIAA/CEAS Aeroacoustics Conference Lyon, France, May 30–June 1, 2016 p2016

    [40]

    Choudhari M, Lockard D 2015 22ed AIAA/CEAS Aeroacoustics Conference Dallas, TX, June 22−26, 2015 p2844

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出版历程
  • 收稿日期:  2019-05-21
  • 修回日期:  2019-07-15
  • 上网日期:  2019-10-01
  • 刊出日期:  2019-10-20

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