TY - JOUR
T1 - Improved prediction of coherent structure in an intermediate turbine duct
AU - Hu, Chenxing
AU - Qiao, Tianyang
AU - Zheng, Siyu
AU - Zheng, Mingqiu
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/10/15
Y1 - 2023/10/15
N2 - Modeling the unsteady flow in an intermediate turbine duct in an aero-engine is highly challenging partly owing to the complex physics subjected to unsteady vortical flow upstream. In this paper, the high-fidelity detached eddy simulations of an aggressive intermediate turbine duct are performed and validated against published data. The dominating coherent flow motions are then captured with sparsity-promoting dynamics mode decomposition under different tip gap sizes and rotating speeds of the rotor blade. Furthermore, a novel low-order spectrum reconstruction method based on selected flow modes and Gaussian fitting is proposed for fast prediction of the instantaneous flowfield in the intermediate turbine duct. The sources of error are discussed and a potential approach to improve the prediction accuracy is proposed. It reveals that the proposed method achieves accurate and generalized performance in reconstructing and predicting flow fields with periodic features for a small cost of calculation time. The maximum root mean squared error in the scenario of tip gap size and rotating speed variation is below 5.96 and 8.41, respectively. The error analysis shows that the variation of flow modes under different inflow conditions and nonlinearity of interacting flow structure accounts for the major part of prediction error. By applying a Proper orthogonal decomposition (POD) interpolation on the flow modes, the maximum root mean squared error in the scenario of tip gap size and rotating speed variation can drop to 4.76 and 2.69 without breaking the physical meaning of the representative modes. The novelty of the present work lies at the proposed prediction method combining DMDSP and POD-interpolation, of which the majority of the physical information are maintained and the prediction accuracy is improved. It may provide a promising approach for turbomachinery design, flow prediction, and investigating underlying mechanisms with low data requirements.
AB - Modeling the unsteady flow in an intermediate turbine duct in an aero-engine is highly challenging partly owing to the complex physics subjected to unsteady vortical flow upstream. In this paper, the high-fidelity detached eddy simulations of an aggressive intermediate turbine duct are performed and validated against published data. The dominating coherent flow motions are then captured with sparsity-promoting dynamics mode decomposition under different tip gap sizes and rotating speeds of the rotor blade. Furthermore, a novel low-order spectrum reconstruction method based on selected flow modes and Gaussian fitting is proposed for fast prediction of the instantaneous flowfield in the intermediate turbine duct. The sources of error are discussed and a potential approach to improve the prediction accuracy is proposed. It reveals that the proposed method achieves accurate and generalized performance in reconstructing and predicting flow fields with periodic features for a small cost of calculation time. The maximum root mean squared error in the scenario of tip gap size and rotating speed variation is below 5.96 and 8.41, respectively. The error analysis shows that the variation of flow modes under different inflow conditions and nonlinearity of interacting flow structure accounts for the major part of prediction error. By applying a Proper orthogonal decomposition (POD) interpolation on the flow modes, the maximum root mean squared error in the scenario of tip gap size and rotating speed variation can drop to 4.76 and 2.69 without breaking the physical meaning of the representative modes. The novelty of the present work lies at the proposed prediction method combining DMDSP and POD-interpolation, of which the majority of the physical information are maintained and the prediction accuracy is improved. It may provide a promising approach for turbomachinery design, flow prediction, and investigating underlying mechanisms with low data requirements.
KW - Intermediate turbine duct
KW - Pod interpolation
KW - Sparsity-promoting dynamics mode decomposition
KW - Tip leakage vortices
KW - Unsteady flow prediction
UR - http://www.scopus.com/inward/record.url?scp=85160534922&partnerID=8YFLogxK
U2 - 10.1016/j.ijmecsci.2023.108497
DO - 10.1016/j.ijmecsci.2023.108497
M3 - Article
AN - SCOPUS:85160534922
SN - 0020-7403
VL - 256
JO - International Journal of Mechanical Sciences
JF - International Journal of Mechanical Sciences
M1 - 108497
ER -