Transition Modelling With the SST Turbulence Model and an Intermittency Transport Equation

2003 ◽  
Author(s):  
Koen Lodefier ◽  
Bart Merci ◽  
Chris De Langhe ◽  
Erik Dick
Keyword(s):  
Turbulence Model ◽  
Turbulent Viscosity ◽  
Transition Model ◽  
Bypass Transition ◽  
Model Following ◽  
Sst Model ◽  
Sst Turbulence Model ◽  
Transition Modelling ◽  
Intermittency Factor

A transition model for describing bypass transition is presented. It is based on a two-equations k–ω model and a dynamic equation for intermittency factor. The intermittency factor is a multiplier of the turbulent viscosity computed by the turbulence model. Following a suggestion by Menter et al. [1], the start of transition is computed based on local variables. The choice of the Shear-Stress Transport (SST) model instead of a k–ε model is explained. The quality of the transition model, developed on flat plate test cases, is illustrated for cascades.

An Unsteady RANS Transition Model With Dynamic Description of Intermittency

2005 ◽  
Author(s):  
Koen Lodefier ◽  
Erik Dick
Keyword(s):  
Turbulence Model ◽  
Turbulence Intensity ◽  
Free Stream ◽  
Turbulent Viscosity ◽  
Suction Side ◽  
Transition Model ◽  
Free Stream Turbulence ◽  
Sst Turbulence Model ◽  
Intermittency Factor ◽  
Dynamic Description

A transition model for describing wake-induced transition is presented. It is based on the SST turbulence model by Menter, with the k–ω part in low-Reynolds form according to Wilcox, and two dynamic equations for intermittency: one for near-wall-intermittency and one for free-stream-intermittency. The total intermittency factor, which is the sum of the two, multiplies the turbulent viscosity computed by the turbulence model. The quality of the transition model is illustrated on the T106a test cascade using experimental results for flow with low free-stream turbulence intensity and transition in separated state and for flow with high free-stream turbulence intensity and transition in attached state. The unsteady results are presented in S–T diagrams of the shape factor and wall shear stress on the suction side. Results show the capability of the model to capture the basics of unsteady transition.

A Four-Equation Eddy-Viscosity Approach for Modeling Bypass Transition

2014 ◽  
Vol 6 (4) ◽  
pp. 523-538
Author(s):  
Guoliang Xu ◽  
Song Fu
Keyword(s):  
Kinetic Energy ◽  
Transport Equation ◽  
Eddy Viscosity ◽  
Turbulent Viscosity ◽  
Transitional Region ◽  
Transition Model ◽  
Bypass Transition ◽  
Turbulence Transition ◽  
Sst Turbulence Model ◽  
Layer Flow

AbstractIt is very important to predict the bypass transition in the simulation of flows through turbomachinery. This paper presents a four-equation eddy-viscosity turbulence transition model for prediction of bypass transition. It is based on the SST turbulence model and the laminar kinetic energy concept. A transport equation for the non-turbulent viscosity is proposed to predict the development of the laminar kinetic energy in the pre-transitional boundary layer flow which has been observed in experiments. The turbulence breakdown process is then captured with an intermittency transport equation in the transitional region. The performance of this new transition model is validated through the experimental cases of T3AM, T3A and T3B. Results in this paper show that the new transition model can reach good agreement in predicting bypass transition, and is compatible with modern CFD software by using local variables.

RANS Modelling of Wake Induced Transition With the Dynamic Intermittency Concept

2006 ◽  
Author(s):  
Koen Lodefier ◽  
Erik Dick
Keyword(s):  
Turbulence Model ◽  
Free Stream ◽  
Stokes Equations ◽  
Turbulent Viscosity ◽  
Suction Side ◽  
Navier Stokes ◽  
Transition Model ◽  
Navier Stokes Equations ◽  
Free Stream Turbulence ◽  
Sst Turbulence Model

A transition model for describing wake-induced transition is presented based on the SST turbulence model by Menter and two dynamic equations for intermittency: one for near-wall intermittency and one for free-stream intermittency. In the Navier-Stokes equations, the total intermittency factor, which is the sum of the two, multiplies the turbulent viscosity computed by the turbulence model. The quality of the transition model is illustrated on the T106A test cascade for different levels of inlet free-stream turbulence intensity. The unsteady results are presented in space-time diagrams of shape factor, wall shear stress, momentum thickness and intermittency on the suction side. Results show the capability of the model to capture the physics of unsteady transition. Inevitable shortcomings are also revealed.

scholarly journals Prediction of the Propeller Performance at Different Reynolds Number Regimes with RANS

2021 ◽  
Vol 9 (10) ◽  
pp. 1115
Author(s):  
João Baltazar ◽  
Douwe Rijpkema ◽  
José Falcão de Campos
Keyword(s):  
Reynolds Number ◽  
Turbulence Model ◽  
Scale Effects ◽  
Open Water ◽  
Reynolds Numbers ◽  
Navier Stokes ◽  
Transition Model ◽  
Sst Turbulence Model ◽  
Propeller Performance ◽  
Selection Of

In this study, a Reynolds averaged Navier-Stokes solver is used for prediction of the propeller performance in open-water conditions at different Reynolds numbers ranging from 104 to 107. The k−ω SST turbulence model and the γ−R˜eθt correlation-based transition model are utilised and results compared for a conventional marine propeller. First, the selection of the turbulence inlet quantities for different flow regimes is discussed. Then, an analysis of the iterative and discretisation errors is made. This work is followed by an investigation of the predicted propeller flow at variable Reynolds numbers. Finally, the propeller scale-effects and the influence of the turbulence and transition models on the performance prediction are discussed. The variation of the flow regime showed an increase in thrust and decrease in torque for increasing Reynolds number. From the comparison between the turbulence model and the transition model, different flow solutions are obtained for the Reynolds numbers between 105 and 106, affecting the scale-effects prediction.

Sensitization of the SST Turbulence Model to Rotation and Curvature by Applying the Spalart-Shur Correction Term

2008 ◽  
Author(s):  
Pavel E. Smirnov ◽  
Florian R. Menter
Keyword(s):  
Turbulent Flows ◽  
Turbulence Model ◽  
Transport Model ◽  
Correction Term ◽  
Computational Cost ◽  
Reynolds Stresses ◽  
Wide Range ◽  
Sst Model ◽  
Shear Stress Transport Model ◽  
Sst Turbulence Model

A rotation-curvature correction suggested earlier by Spalart and Shur for the one-equation Spalart-Allmaras turbulence model is adapted to the Shear Stress Transport model. This new version of the model (SST-CC) has been extensively tested on a wide range of both wall-bounded and free shear turbulent flows with system rotation and/or streamline curvature. Predictions of the SST-CC model are compared with available experimental and DNS data, on one hand, and with the corresponding results of the original SST model and advanced Reynolds stresses transport model (RSM), on the other hand. It is found, that in terms of accuracy the proposed model significantly improves the original SST model and is quite competitive with the RSM, whereas its computational cost is significantly less than that of the RSM.

scholarly journals Simulation of transonic flows through a turbine blade cascade with various prescription of outlet boundary conditions

2018 ◽  
Vol 180 ◽  
pp. 02056
Author(s):  
Petr Louda ◽  
Petr Straka ◽  
Jaromír Příhoda
Keyword(s):  
Boundary Conditions ◽  
Turbine Blade ◽  
Turbulence Model ◽  
Numerical Results ◽  
Transition Model ◽  
Computational Domain ◽  
Transonic Flows ◽  
Blade Cascade ◽  
Experimental Configuration ◽  
Sst Turbulence Model

The contribution deals with the numerical simulation of transonic flows through a linear turbine blade cascade. Numerical simulations were carried partly for the standard computational domain with various outlet boundary conditions by the algebraic transition model of Straka and Příhoda [1] connected with the EARSM turbulence model of Hellsten [2] and partly for the computational domain corresponding to the geometrical arrangement in the wind tunnel by the γ-ζ transition model of Dick et al. [3] with the SST turbulence model. Numerical results were compared with experimental data. The agreement of numerical results with experimental results is acceptable through a complicated experimental configuration.

Adjoint-Based Optimization Method With Linearized SST Turbulence Model and a Frozen Gamma-Theta Transition Model Approach for Turbomachinery Design

2015 ◽  
Author(s):  
Pengfei Zhang ◽  
Juan Lu ◽  
Zhiduo Wang ◽  
Liming Song ◽  
Zhenping Feng
Keyword(s):  
Turbulence Model ◽  
Entropy Generation ◽  
Adjoint System ◽  
Optimization Method ◽  
Adjoint Equations ◽  
Transition Model ◽  
Transition Flow ◽  
Flow Optimization ◽  
Sst Turbulence Model ◽  
Continuous Adjoint

In this paper, based on the grid node coordinates variation and Jacobian Matrices, the turbulent continuous adjoint method with linearized turbulence model is studied and developed to fully account for the variation of turbulent eddy viscosity. The corresponding adjoint equations, boundary conditions and the final sensitivities are formulated with a general expression. To implement the adjoint optimization of the transition flow, a flow solver combining the transition model with the turbulence model is employed, and an adjoint optimization framework with linearized SST turbulence model and a frozen Gamma-Theta transition model is established. In order to choose an appropriate objective for the transition flow optimization, four objectives are studied, including the entropy generation, the total pressure loss coefficient, the field integral of turbulent kinetic energy, the area ratio of transition and turbulent regions to the suciton side. And finally the entropy generation is adopted as the objective. Then, the derivation of the adjoint system for the entropy generation optimization is presented. To demonstrate the validity of the adjoint system for transition flow, four shape optimizations for the bypass transitions and the separation-induced transition are implemented. A 2D isentropic case for bypass transitions is conducted to compares the performances of the fully turbulent adjoint system and the frozen Gamma-Theta transition adjoint system, while the other isothermal case is performed to take the aerodynamic and heat transfer issues into account together. The case of separation-induced transition is performed and also consistent well with its flow mechanism. The four optimization results illustrate the effectiveness of the adjoint system for the transition flow optimization, which can improves the performance of overall cascades and the transition region.

scholarly journals Analysis of Flow Characteristics and Effects of Turbulence Models for the Butterfly Valve

2021 ◽  
Vol 11 (14) ◽  
pp. 6319
Author(s):  
Sung-Woong Choi ◽  
Hyoung-Seock Seo ◽  
Han-Sang Kim
Keyword(s):  
Turbulence Model ◽  
Dissipation Rate ◽  
Flow Characteristics ◽  
Turbulence Models ◽  
Flow Properties ◽  
Nominal Diameter ◽  
Large Pressure ◽  
Sst Model ◽  
Turbulence Effect ◽  
Valve Opening

In the present study, the flow characteristics of butterfly valves with different sizes DN 80 (nominal diameter: 76.2 mm), DN 262 (nominal diameter: 254 mm), DN 400 (nominal diameter: 406 mm) were numerically investigated under different valve opening percentages. Representative two-equation turbulence models of two-equation k-epsilon model of Launder and Sharma, two-equation k-omega model of Wilcox, and two-equation k-omega SST model of Menter were selected. Flow characteristics of butterfly valves were examined to determine turbulence model effects. It was determined that increasing turbulence effect could cause many discrepancies between turbulence models, especially in areas with large pressure drop and velocity increase. In addition, sensitivity analysis of flow properties was conducted to determine the effect of constants used in each turbulence model. It was observed that the most sensitive flow properties were turbulence dissipation rate (Epsilon) for the k-epsilon turbulence model and turbulence specific dissipation rate (Omega) for the k-omega turbulence model.

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