Pragmatic Prediction Model of Droplet Trajectory in a Turbine CascadeSource: Journal of Turbomachinery:;2024:;volume( 146 ):;issue: 012::page 121003-1DOI: 10.1115/1.4065785Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Droplet deposition on a turbine cascade is important for the turbine system performance but its experimental analysis is difficult. Thus, the simulation of a droplet liquid phase in a gas flow field was studied to optimize turbine cascade design. However, the computational fluid dynamics (CFD)-based approach for such droplet problems requires enormous costs. Thus, the application of CFD simulation in the turbine blade's early-stage design is challenging, requiring iterative optimization for adjusting design with performance prediction. Therefore, this study proposed an analytical prediction method, having a reasonable cost and moderate accuracy, as an alternative to the whole multi-phase numerical simulation approach. The proposed method predicts droplet motion using the outline of the turbine blade and gas–liquid physical properties. Furthermore, the approach was validated by performing a three-dimensional Eulerian–Lagrangian simulation with low-pressure turbine blade T106. It was found that the droplet trajectories in the turbine cascade are governed by Stokes number. Furthermore, the streamlines of the gas flow were characterized by the shape of the turbine blade. The proposed model reproduced droplet trajectories obtained using CFD within an error margin of 10%. Consequently, it was concluded that the proposed analytical model is a promising approach to predict the droplet trajectory in a turbine cascade, obtained by the three-dimensional numerical simulation at a low cost.
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| contributor author | Oshima, Ippei | |
| contributor author | Furuichi, Mikito | |
| date accessioned | 2024-12-24T18:44:15Z | |
| date available | 2024-12-24T18:44:15Z | |
| date copyright | 7/15/2024 12:00:00 AM | |
| date issued | 2024 | |
| identifier issn | 0889-504X | |
| identifier other | turbo_146_12_121003.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4302654 | |
| description abstract | Droplet deposition on a turbine cascade is important for the turbine system performance but its experimental analysis is difficult. Thus, the simulation of a droplet liquid phase in a gas flow field was studied to optimize turbine cascade design. However, the computational fluid dynamics (CFD)-based approach for such droplet problems requires enormous costs. Thus, the application of CFD simulation in the turbine blade's early-stage design is challenging, requiring iterative optimization for adjusting design with performance prediction. Therefore, this study proposed an analytical prediction method, having a reasonable cost and moderate accuracy, as an alternative to the whole multi-phase numerical simulation approach. The proposed method predicts droplet motion using the outline of the turbine blade and gas–liquid physical properties. Furthermore, the approach was validated by performing a three-dimensional Eulerian–Lagrangian simulation with low-pressure turbine blade T106. It was found that the droplet trajectories in the turbine cascade are governed by Stokes number. Furthermore, the streamlines of the gas flow were characterized by the shape of the turbine blade. The proposed model reproduced droplet trajectories obtained using CFD within an error margin of 10%. Consequently, it was concluded that the proposed analytical model is a promising approach to predict the droplet trajectory in a turbine cascade, obtained by the three-dimensional numerical simulation at a low cost. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Pragmatic Prediction Model of Droplet Trajectory in a Turbine Cascade | |
| type | Journal Paper | |
| journal volume | 146 | |
| journal issue | 12 | |
| journal title | Journal of Turbomachinery | |
| identifier doi | 10.1115/1.4065785 | |
| journal fristpage | 121003-1 | |
| journal lastpage | 121003-12 | |
| page | 12 | |
| tree | Journal of Turbomachinery:;2024:;volume( 146 ):;issue: 012 | |
| contenttype | Fulltext |