Evaluation and Analysis of Curvature-Corrected Filter-based Turbulent Model
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Rui Zhang
Abstract
Prediction of the characteristics of turbulent flow with streamline curvature is of great importance in engineering applications. In this paper, a curvature-corrected filter-based turbulent model is suggested by applying the Spalart-Shur correction term. This new version of the model (FBM-CC) has been tested and verified through two canonical benchmarks with strong streamline curvature: the flow in a two-dimensional U-duct and the free shear flow past NACA0012 airfoil with a round tip. Predictions of the FBM-CC model are compared with available experimental data and the corresponding results of the original FBM model. The numerical results show that the FBM-CC model significantly improves the sensitivity to the effect of streamline curvature and the numerical calculation accuracy, in relatively good agreement with the experimental data, which suggests that this proposed model may be employed to simulate the turbulent curved flow in engineering applications.
Funding statement: Funding: This work is supported by Natural Science Foundation of Jiangsu Province (No. BK20150808) and Fundamental Research Funds for the Central Universities (No. 2014B12314).
Nomenclature
- C
chord length, m
- Cp
pressure coefficient
- cr1, cr2, cr3
empirical constants of the FBM-CC turbulent model
- C3, C1ε, C2ε
turbulent model constants
- Cμ
eddy-viscosity coefficient
- Gk
production of turbulence kinetic energy
- H
channel height, m
- k
turbulence kinetic energy
- Re
Reynolds number
- s
streamwise distance, m
- S
strain tensor magnitude
- Sij
components of the mean strain tensor
- u, v, w
Cartesian velocity components, m/s
- U
inlet velocity, m/s
- x, y, z
Cartesian coordinate directions
- Y
coordinate normal to wall
- μ
molecular viscosity
- μt
turbulent viscosity
- νt
turbulent kinematic viscosity
- ε
dissipation rate of turbulent kinetic energy, m2/s3
- ω
specific dissipation rate of turbulence, s–1
- Ω
rotation-rate magnitude
- Ωij
components of the vorticity tensor
- Ωm
components of the system rotation vector
- εimn
tensor of Levi–Civita
- Δ
filter size
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Articles in the same Issue
- Frontmatter
- Effects of Cavity Configurations on Flameholding and Performances of Kerosene Fueled Scramjet Combustor
- Metaheuristic and Machine Learning Models for TFE-731-2, PW4056, and JT8D-9 Cruise Thrust
- Design Optimization Method for Composite Components Based on Moment Reliability-Sensitivity Criteria
- Use Deflected Trailing Edge to Improve the Aerodynamic Performance and Develop Low Solidity LPT Cascade
- A Co-modeling Method Based on Component Features for Mechatronic Devices in Aero-engines
- Evaluation and Analysis of Curvature-Corrected Filter-based Turbulent Model
- Aircraft Engine Thrust Estimator Design Based on GSA-LSSVM
- Effect of Inner Nozzle Lip Thickness on Co-flow Jet Characteristics
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Articles in the same Issue
- Frontmatter
- Effects of Cavity Configurations on Flameholding and Performances of Kerosene Fueled Scramjet Combustor
- Metaheuristic and Machine Learning Models for TFE-731-2, PW4056, and JT8D-9 Cruise Thrust
- Design Optimization Method for Composite Components Based on Moment Reliability-Sensitivity Criteria
- Use Deflected Trailing Edge to Improve the Aerodynamic Performance and Develop Low Solidity LPT Cascade
- A Co-modeling Method Based on Component Features for Mechatronic Devices in Aero-engines
- Evaluation and Analysis of Curvature-Corrected Filter-based Turbulent Model
- Aircraft Engine Thrust Estimator Design Based on GSA-LSSVM
- Effect of Inner Nozzle Lip Thickness on Co-flow Jet Characteristics
- Comparisons of Two Non-probabilistic Structural Reliability Analysis Methods for Aero-engine Turbine Disk
