Acoustic Inversion for Uncertainty Reduction in Reynolds-Averaged Navier-Stokes-Based Jet Noise Prediction | |
Zhang XL(张鑫磊)1; Xiao, Heng2; Wu T(吴霆)1; He GW(何国威)1 | |
发表期刊 | AIAA JOURNAL |
2022 | |
卷号 | 60期号:7页码:2407-2422 |
ISSN | 0001-1452 |
摘要 | The Reynolds-averaged Navier-Stokes (RANS)-based method is a practical tool to provide rapid assessment of jet noise-reduction concepts. However, the RANS-based method requires modeling assumptions to represent noise generation and propagation, which often reduces the predictive accuracy due to the model-form uncertainties. In this work, the ensemble Kalman filter-based acoustic inversion method is introduced to reduce uncertainties in the turbulent kinetic energy and dissipation rate based on the far-field noise and the axial centerline velocity data. The results show that jet noise data are more effective from which to infer turbulent kinetic energy and dissipation rate compared to velocity data. Moreover, the inferred noise source is able to improve the estimation of the turbulent flowfield and the far-field noise at unobserved locations. Further, the noise model parameters are also considered uncertain quantities, demonstrating the ability of the proposed framework to reduce uncertainties in both the RANS and noise models. Finally, one realistic case with experimental data is investigated to show the practicality of the proposed framework. The method opens up the possibility for the inverse modeling of jet noise sources by incorporating far-field noise data that are relatively straightforward to be measured compared to the velocity field. |
DOI | 10.2514/1.J060876 |
收录类别 | SCI ; EI |
语种 | 英语 |
WOS记录号 | WOS:000742546900001 |
关键词[WOS] | DATA ASSIMILATION ; MIXING NOISE ; MEAN-FLOW ; OPTIMIZATION ; ANALOGY ; SPACE ; MODEL ; SPEED |
WOS研究方向 | Engineering |
WOS类目 | Engineering, Aerospace |
资助项目 | National Science Foundation of China Basic Science Center Program for Multiscale Problems in Nonlinear Mechanics[11988102] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB22040104] ; Key Research Program of Frontier Sciences of the Chinese Academy of Sciences[QYZDJ-SSWSYS002] |
项目资助者 | National Science Foundation of China Basic Science Center Program for Multiscale Problems in Nonlinear Mechanics ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Key Research Program of Frontier Sciences of the Chinese Academy of Sciences |
论文分区 | 一类/力学重要期刊 |
力学所作者排名 | 1 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://dspace.imech.ac.cn/handle/311007/88376 |
专题 | 非线性力学国家重点实验室 |
通讯作者 | He GW(何国威) |
作者单位 | 1.Chinese Acad Sci, State Key Lab Nonlinear Mech, Beijing 100190, Peoples R China 2.Virginia Tech, Kevin T Crofton Dept Aerosp & Ocean Engn, Blacksburg, VA 24060 USA |
推荐引用方式 GB/T 7714 | Zhang XL,Xiao, Heng,Wu T,et al. Acoustic Inversion for Uncertainty Reduction in Reynolds-Averaged Navier-Stokes-Based Jet Noise Prediction[J]. AIAA JOURNAL,2022,60,7,:2407-2422. |
APA | Zhang XL,Xiao, Heng,Wu T,&He GW.(2022).Acoustic Inversion for Uncertainty Reduction in Reynolds-Averaged Navier-Stokes-Based Jet Noise Prediction.AIAA JOURNAL,60(7),2407-2422. |
MLA | Zhang XL,et al."Acoustic Inversion for Uncertainty Reduction in Reynolds-Averaged Navier-Stokes-Based Jet Noise Prediction".AIAA JOURNAL 60.7(2022):2407-2422. |
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