Week 5 - Turbulence modelling challenge

Week 5 - Turbulence modelling challenge

1. In this challenge, you are required to do a literature review of various turbulence models explained in the Turbulence modeling video (Week-5) and explain why DNS isn’t feasible according to Kolmogorov's scale.
2. For the below geometry performs a 3D simulation and explain the recirculation region using velocity vectors.
3. Consider the flow direction of air, the ball is traveling opposite to it at 60m/s. Explain in which direction the ball will curve by visualizing the wake region.

Simulation

The Geometry ( Cross-Sectional View)

For the first we opened the geometry in Design Moddeller,

The next part is Meshing,

As of using the student version, the number of cell is limited to 500000,

Therefore we use the element size as 1 mm.

The named selection is done as Inlet, Outlet, Symmetry walls, and Golf Wall

Results

The residual Plot

The velocity Magnitude Contour

Static Pressure Contour

Pathlines contour representing the flow direction.

The area-weighted average of pressure

Conclusion :

• We can identify the direction of the ball by looking at the velocity vectors and claim it's moving down.
• The golf ball's dimples serve to minimize drag by minimizing the wake region (recirculation).
• It also aids in the attachment of the flow and attempts to detach the flow from the golf ball. Therefore The velocity of the flow beneath the golf ball is high, resulting in low pressure and the formation of a wake following the rough surface. The air velocity on the rough surface is lower, whereas the air velocity on the smooth surface is higher. This causes a pressure differential, which accounts for the ball's downward swing.

Various turbulence models in modern engineering applications.

Spalart–Allmaras (S–A)
The Spalart–Allmaras model is a one-equation model that solves a modeled transport equation for the kinematic eddy turbulent viscosity. The Spalart–Allmaras model was designed specifically for aerospace applications involving wall-bounded flows and has been shown to give good results for boundary layers subjected to adverse pressure gradients. It is also gaining popularity in turbomachinery applications.[citation needed]

k–ε (k–epsilon)
K-epsilon (k-ε) turbulence model is the most common model used in computational fluid dynamics (CFD) to simulate mean flow characteristics for turbulent flow conditions. It is a two-equation model which gives a general description of turbulence by means of two transport equations (PDEs). The original impetus for the K-epsilon model was to improve the mixing-length model, as well as to find an alternative to algebraically prescribing turbulent length scales in moderate to high complexity flows.

k–ω (k–omega)
In computational fluid dynamics, the k–omega (k–ω) turbulence modelis a common two-equation turbulence model that is used as a closure for the Reynolds-averaged Navier–Stokes equations (RANS equations). The model attempts to predict turbulence by two partial differential equations for two variables, k and ω, with the first variable being the turbulence kinetic energy (k) while the second (ω) is the specific rate of dissipation (of the turbulence kinetic energy k into internal thermal energy).

SST (Menter’s Shear Stress Transport)
SST (Menter's shear stress transport) turbulence model is a widely used and robust two-equation eddy-viscosity turbulence model used in computational fluid dynamics. The model combines the k-omega turbulence model and K-epsilon turbulence model such that the k-omega is used in the inner region of the boundary layer and switches to the k-epsilon in the free shear flow.

Reynolds stress equation model
The Reynolds stress equation model (RSM), also referred to as second moment closure model, is the most complete classical turbulence modelling approach. Popular eddy-viscosity based models like the k–ε (k–epsilon) model and the k–ω (k–omega) models have significant shortcomings in complex engineering flows. This arises due to the use of the eddy-viscosity hypothesis in their formulation. For instance, in flows with high degrees of anisotropy, significant streamline curvature, flow separation, zones of recirculating flow or flows influenced by rotational effects, the performance of such models is unsatisfactory. In such flows, Reynolds stress equation models offer much better accuracy.

Eddy viscosity based closures cannot account for the return to isotropy of turbulence, observed in decaying turbulent flows. Eddy-viscosity based models cannot replicate the behaviour of turbulent flows in the Rapid Distortion limit,where the turbulent flow essentially behaves like an elastic medium.

We cannot use DNS is because it generates a mesh which is very fine and tries to capture all anomalies, so as the mesh cells increase the time taken to solve will increase. Due to this industries dont prefer this method.