Uncertainty Quantification and Sensitivity Analysis of Transonic Aerodynamics with Geometric Uncertainty
Airfoil geometric uncertainty can generate aerodynamic characteristics fluctuations. Uncertainty quantification is applied to compute its impact on the aerodynamic characteristics. In addition, the contribution of each uncertainty variable to aerodynamic characteristics should be computed by the unc...
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2017/8107190 |
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| author | Xiaojing Wu Weiwei Zhang Shufang Song |
| author_facet | Xiaojing Wu Weiwei Zhang Shufang Song |
| author_sort | Xiaojing Wu |
| collection | DOAJ |
| description | Airfoil geometric uncertainty can generate aerodynamic characteristics fluctuations. Uncertainty quantification is applied to compute its impact on the aerodynamic characteristics. In addition, the contribution of each uncertainty variable to aerodynamic characteristics should be computed by the uncertainty sensitivity analysis. In the paper, Sobol’s analysis is used for uncertainty sensitivity analysis and a nonintrusive polynomial chaos method is used for uncertainty quantification and Sobol’s analysis. It is difficult to describe geometric uncertainty because it needs a lot of input parameters. In order to alleviate the contradiction between the variable dimension and computational cost, a principal component analysis is introduced to describe geometric uncertainty of airfoil. Through this technique, the number of input uncertainty variables can be reduced and typical global deformation modes can be obtained. By uncertainty quantification, we can learn that the flow characteristics of shock wave and boundary layer separation are sensitive to the geometric uncertainty in transonic region, which is the main reason that transonic drag is sensitive to the geometric uncertainty. The sensitivity analysis shows that the model can be simplified by eliminating unimportant geometric modes. Moreover, which are the most important geometric modes to transonic aerodynamics can be learnt. This is very helpful for airfoil design. |
| format | Article |
| id | doaj-art-6eb5e11ade514d16b9f7c46d7a9f6f04 |
| institution | Kabale University |
| issn | 1687-5966 1687-5974 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj-art-6eb5e11ade514d16b9f7c46d7a9f6f042025-08-20T03:34:08ZengWileyInternational Journal of Aerospace Engineering1687-59661687-59742017-01-01201710.1155/2017/81071908107190Uncertainty Quantification and Sensitivity Analysis of Transonic Aerodynamics with Geometric UncertaintyXiaojing Wu0Weiwei Zhang1Shufang Song2School of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, ChinaAirfoil geometric uncertainty can generate aerodynamic characteristics fluctuations. Uncertainty quantification is applied to compute its impact on the aerodynamic characteristics. In addition, the contribution of each uncertainty variable to aerodynamic characteristics should be computed by the uncertainty sensitivity analysis. In the paper, Sobol’s analysis is used for uncertainty sensitivity analysis and a nonintrusive polynomial chaos method is used for uncertainty quantification and Sobol’s analysis. It is difficult to describe geometric uncertainty because it needs a lot of input parameters. In order to alleviate the contradiction between the variable dimension and computational cost, a principal component analysis is introduced to describe geometric uncertainty of airfoil. Through this technique, the number of input uncertainty variables can be reduced and typical global deformation modes can be obtained. By uncertainty quantification, we can learn that the flow characteristics of shock wave and boundary layer separation are sensitive to the geometric uncertainty in transonic region, which is the main reason that transonic drag is sensitive to the geometric uncertainty. The sensitivity analysis shows that the model can be simplified by eliminating unimportant geometric modes. Moreover, which are the most important geometric modes to transonic aerodynamics can be learnt. This is very helpful for airfoil design.http://dx.doi.org/10.1155/2017/8107190 |
| spellingShingle | Xiaojing Wu Weiwei Zhang Shufang Song Uncertainty Quantification and Sensitivity Analysis of Transonic Aerodynamics with Geometric Uncertainty International Journal of Aerospace Engineering |
| title | Uncertainty Quantification and Sensitivity Analysis of Transonic Aerodynamics with Geometric Uncertainty |
| title_full | Uncertainty Quantification and Sensitivity Analysis of Transonic Aerodynamics with Geometric Uncertainty |
| title_fullStr | Uncertainty Quantification and Sensitivity Analysis of Transonic Aerodynamics with Geometric Uncertainty |
| title_full_unstemmed | Uncertainty Quantification and Sensitivity Analysis of Transonic Aerodynamics with Geometric Uncertainty |
| title_short | Uncertainty Quantification and Sensitivity Analysis of Transonic Aerodynamics with Geometric Uncertainty |
| title_sort | uncertainty quantification and sensitivity analysis of transonic aerodynamics with geometric uncertainty |
| url | http://dx.doi.org/10.1155/2017/8107190 |
| work_keys_str_mv | AT xiaojingwu uncertaintyquantificationandsensitivityanalysisoftransonicaerodynamicswithgeometricuncertainty AT weiweizhang uncertaintyquantificationandsensitivityanalysisoftransonicaerodynamicswithgeometricuncertainty AT shufangsong uncertaintyquantificationandsensitivityanalysisoftransonicaerodynamicswithgeometricuncertainty |