| Nonlinear uncertainty quantification of the impact of geometric variability on compressor performance using an adjoint method |
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| 作者姓名： | Qian ZHANG Shenren XU Xianjun YU Jiaxin LIU Dingxi WANG Xiuquan HUANG |
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| 作者单位： | School of Power and Energy,Northwestern Polytechnical University,Xi'an 710072,China;School of Power and Energy,Northwestern Polytechnical University,Xi'an 710072,China;Key Laboratory of Aeroengine Internal Flows,Northwestern Polytechnical University,Xi'an 710129,China;School of Energy and Power Engineering,Beihang University,Beijing 100083,China;Research Institute of Aeroengine,Beihang University,Beijing 100083,China;School of Energy and Power Engineering,Beihang University,Beijing 100083,China |
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| 基金项目： | funded by the National Natural Science Foundation of China (No. 52006177)；;National Science and Technology Major Project, China (No. 2017-II-0009-0023)； |
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| 摘 要： | Manufactured blades are inevitably different from their design intent, which leads to a deviation of the performance from the intended value. To quantify the associated performance uncertainty, many approaches have been developed. The traditional Monte Carlo method based on a Computational Fluid Dynamics solver(MC-CFD) for a three-dimensional compressor is prohibitively expensive. Existing alternatives to the MC-CFD, such as surrogate models and secondorder derivatives based on the adjoint metho...
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| 收稿时间： | 23 April 2021 |
Nonlinear uncertainty quantification of the impact of geometric variability on compressor performance using an adjoint method |
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| Qian ZHANG,Shenren XU,Xianjun YU,Jiaxin LIU,Dingxi WANG,Xiuquan HUANG.Nonlinear uncertainty quantification of the impact of geometric variability on compressor performance using an adjoint method[J].Chinese Journal of Aeronautics,2022,35(2):17-21. |
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| Authors: | Qian ZHANG Shenren XU Xianjun YU Jiaxin LIU Dingxi WANG Xiuquan HUANG |
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| Institution: | 1. School of Power and Energy, Northwestern Polytechnical University, Xi’an 710072, China;2. Key Laboratory of Aeroengine Internal Flows, Northwestern Polytechnical University, Xi’an 710129, China;3. School of Energy and Power Engineering, Beihang University, Beijing 100083, China;4. Research Institute of Aeroengine, Beihang University, Beijing 100083, China |
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| Abstract: | Manufactured blades are inevitably different from their design intent,which leads to a deviation of the performance from the intended value.To quantify the associated performance uncertainty,many approaches have been developed.The traditional Monte Carlo method based on a Computational Fluid Dynamics solver (MC-CFD) for a three-dimensional compressor is pro-hibitively expensive.Existing alternatives to the MC-CFD,such as surrogate models and second-order derivatives based on the adjoint method,can greatly reduce the computational cost.Neverthe-less,they will encounter 'the curse of dimensionality'except for the linear model based on the adjoint gradient (called MC-adj-linear).However,the MC-adj-linear model neglects the nonlinearity of the performance function.In this work,an improved method is proposed to circumvent the low-accuracy problem of the MC-adj-linear without incurring the high cost of other alternative models.The method is applied to the study of the aerodynamic performance of an annular transonic com-pressor cascade,subject to prescribed geometric variability with industrial relevance.It is found that the proposed method achieves a significant accuracy improvement over the MC-adj-linear with low computational cost,showing the great potential for fast uncertainty quantification. |
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| Keywords: | Adjoint method Aerodynamics Compressor Manufacturing Monte Carlo method Nonlinearity Uncertainty quantification |
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