Liam F1 Wind Turbine, ANSYS Fluent CFD Simulation Training

Introduction

Currently, the most-efficient wind turbine designs aren’t particularly suited for residential installation. They’re require enough height to catch the wind to be of any use, and then there are the noise complaints. Could bird strikes be a cause for concern, similar to large-scale wind farms. Scaling down wind turbines doesn’t help a whole lot with these problems, so residential systems remain an oddity. However, recently, an entirely new small-scale wind turbine design named as Liam-F1 Urban Wind Turbine is able to operate at approximately 80% of the Betz Limit, or 47.4% overall efficiency, which states that the theoretical maximum efficiency of any wind turbine is only 59.3%.

Commercial wind turbines max out at 50% of the Betz Limit, or just 29.7% efficiency. Due to these unique attributes, in this study, CFD has been employed to evaluate this type of turbine evaluation on an arbitrary wind tunnel situation.

Liam Project Description

This project is going to simulate an airflow field adjacent to Liam F1 wind turbine by ANSYS Fluent. The geometry included a rotary zone for the turbine walls and a stationary zone for the rest of the domain. The inlet is considered 3 m/s and the turbine zone is rotating with 300 RPM. The purpose of this project is to investigate the behavior of airflow and pressure distribution, as well as to study drag force.

Mathematical Modeling

To study a horizontal axis wind turbine (HAWT), one must solve the flow equations in the differential form. By assuming an isothermal, incompressible, and steady-state condition for the air around the blades, two forces known as the Coriolis and centripetal accelerations are the important source-terms that are exerting on the flow elements. Briefly, the governing mass and momentum equations are written as follows:

Liam Geometry and Mesh

As a numerical study, the initial step towards the modeling is production of the CAD geometry, which is depicted in figures inside the computational domain. The blue face is considered as the inlet of the domain while the red face on the other side is considered the outlet. In fact, the current computational domain is the representation of the wind turbine that we have evaluated the turbine. The modeling step would then continue by discretizing the computational domain in to finite number of elements. The noted procedure is called the mesh generation step and has a direct impact on the solution accuracy.

Afterwards, the mesh generation process has been carried out. For the current problem, a mesh count of 1,249,235 elements were created to represent the geometry. Regarding the quality of the mesh, the maximum skewness of 0.71 with the average of 0.21 has found to be a satisfactory mesh for the current problem. In addition, for an interested reader, the quality distribution of mesh is shown. Also 5 prism layers were also added adjacent to both wind tunnel walls and the turbines body in order to accurately calculate the boundary layer. The generated mesh is also presented in following figures:

As a final noted, due to having a turbomachinery simulation, a cylindrical zone has been separated from the whole computational geometry (green zone) and later represented as the rotary geometry.

Liam CFD Simulation Settings

By importing the mesh into the fluid solver, we start the calculation procedure. As discussed before, an incompressible, isothermal condition has found to be a valid assumption for the current simulation. However, gravity was not taken into account for two main reasons. First, the gravity source would produce equivalent force for the fluid cells if an isothermal condition is considered. Thus, it won’t affect the characteristic of the fluid flow.

Moreover, the flow field is fully turbulent. Thus, we select the k-w-SST turbulent model for the evaluation of eddies. The noted model has been more accurate than any other eddy-viscosity variation due to a hybrid formulation that takes care of both wall effects and the core flow strain rate. Details of the solution setup are as follows:

Solver settings: (Liam)
Type:	Pressure-based
Velocity formulation:	Absolute
Time setting:	Transient
Gravity:	Off
Energy:	Off
Model:	k-w-SST
Zone:	Static fluid zone: Rectangular Box: default Static fluid zone: Cylindrical: Frame-motion Axis: x-direction Axis point: (0,0,0) Rotational Speed: 300 RPM
Boundary conditions:	Turbine Walls: No-slip Inlet: velocity inlet: 3 m/s Outlet: pressure outlet Wind Tunnel walls: No-slip
Operating Condition:	Reference Pressure Point: 101325 Pa
Solver Properties: (Liam)
Solution methods:	Coupled Pseudo Transient
Pressure interpolation scheme:	Second-Order
Momentum:	Second-Order
Turbulence:	First-Order
Relaxation:	Default Time-scale factor: 1.00
Initialization:	Standard > from inlet
Material used: (Liam)
Fluid:	Air – constant properties Density: 1.225 kg/(m3) Viscosity: 1.7894×10-5 (Pa.s)
Monitor: (Liam)	Drag Value of Blade wall in x-direction

Results and Discussions

After the solution converges, we observe the results through post-processing. Meanwhile, as an assurance of an excellent convergence, we monitor the drag value during the solution iterations. In this study, the solution converged one when the drag force reached a constant rate, and the residuals were below 10^-4 values. As an initial check, we evaluate the contour of Yplus to decide the boundary layer mesh’s consistency. Fortunately for this case, the maximum plus value was nearly 8, not far from the laminar sublayer. Also, the majority of the facial elements Yplus values is below three, indicating that we resolve the boundary layer in most places rather than being modeled.

Afterward, we depicted the results regarding the pressure and the velocity field in Figures. As shown in Figure, the turbine wall’s leading-edge suffers from the highest-pressure gradient, which is entirely logical since the velocity has just met zero.

Results and Discussions

For the velocity field, we present both contour and streamlines to give much insight into the problem. Briefly, the velocity field adjacent to the turbine’s wall has the highest gradient, and the wake that arises from it stretches far behind the bird’s body. This could be, again, observed through the velocity vectors. Additionally, the streamlines vectors illustrate the quality of the flow streams resolved in the wake section, depicted in Figure, which is the core challenge of aerodynamic simulation.

Finally, we calculate the drag force  0.14 (N), which is accurate for a turbine with the noted specifications.

You can obtain Geometry & Mesh file and a comprehensive Training Movie that presents how to solve the problem and extract all desired results.