The Dance of the Fluid: Simulating Von Kármán Vortex Shedding
In the world of fluid dynamics, few phenomena are as visually arresting—and engineeringly significant—as the Von Kármán Vortex Street. Whether it’s the swaying of a skyscraper, the “singing” of power lines, or the swirling patterns in clouds captured by satellites, this phenomenon is a masterclass in how fluids interact with solid structures.
But if you’ve ever tried to simulate this in 3D using Computational Fluid Dynamics (CFD), you know the “sting” in the tail: it is computationally expensive. Today, we’ll break down the physics and show you how to set up this simulation using OpenFOAM, while leveraging the power of CloudHPC.cloud to bypass hardware limitations.
What is Von Kármán Vortex Shedding?
When a fluid flows past a blunt object (like a cylinder), the boundary layer separates from the surface. At specific speeds, these separated layers roll up into alternating vortices that shed periodically from the top and bottom of the object.
The Magic Number: Reynolds (Re)
The behavior of the flow is dictated by the Reynolds number, a dimensionless value representing the ratio of inertial forces to viscous forces:
Re = U d / ν
Where:
- U = Flow velocity
- d = Characteristic length (diameter of the cylinder)
- ν = Kinematic viscosity
The Sweet Spot: For a circular cylinder, steady laminar flow transitions into the beautiful, periodic shedding of the Von Kármán street when Re is roughly between 47 and 180. Above this, the wake becomes increasingly turbulent and chaotic.
Simulating the Street in OpenFOAM
To capture the periodic nature of the shedding, a transient (time-dependent) analysis is required. Using a steady-state solver like simpleFoam won’t work here; you need pimpleFoam or pisoFoam.
Suggested Simulation Parameters
The Sweet Spot: For a circular cylinder, steady laminar flow transitions into the beautiful, periodic shedding of the Von Kármán street when Re is roughly between 47 and 180. Above this, the wake becomes increasingly turbulent and chaotic.
| Parameter | Value | Description |
| Diameter (d) | 0.1 m | Cylinder size |
| Velocity (U) | 1.0 m/s | Inlet flow speed |
| Viscosity (ν) | 0.001 m^2/s | Kinematic viscosity |
| Resulting Re | 100 | Perfect for periodic shedding |
The Mesh and Time-Step
Because the vortices are shed over time, your mesh must be fine enough in the wake region to capture the pressure gradients. Furthermore, your time-step (Δt) must be small enough to keep the Courant Number (Co) below 1.0, ensuring numerical stability.
The Hardware Bottleneck: Why CloudHPC?
Here is the reality check: Transient simulations are resource hogs.
While a steady-state simulation might take 10 minutes on your laptop, a high-fidelity transient run with millions of cells can take hours or even days. You are effectively asking your CPU to solve a massive matrix of equations for every millisecond of “physical” time.
This is where CloudHPC.cloud changes the game.
- Scale on Demand: Don’t let your 4-core laptop struggle. Access 64, 128, or more cores instantly.
- Pre-configured OpenFOAM: No need to spend hours compiling libraries or troubleshooting installations.
- Cost-Efficient: You only pay for the time you use. It’s often cheaper to run a 1-hour job on a supercomputer than to keep your workstation pinned at 100% for two days.
By offloading the heavy lifting to the cloud, you can run finer meshes and longer physical time durations, capturing the full evolution of the vortex street without turning your office into a sauna.
Conclusion
Von Kármán vortex shedding is more than just a pretty pattern; it’s a critical factor in structural integrity and fluid efficiency. By setting your Reynolds number to 100 and utilizing the transient solvers in OpenFOAM, you can visualize these dynamics with incredible precision.
Ready to start shedding?
If you have your OpenFOAM case files ready but your local machine is already sweating, head over to CloudHPC.cloud to run your first transient simulation in the cloud.
CloudHPC is a HPC provider to run engineering simulations on the cloud. CloudHPC provides from 1 to 224 vCPUs for each process in several configuration of HPC infrastructure - both multi-thread and multi-core. Current software ranges includes several CAE, CFD, FEA, FEM software among which OpenFOAM, FDS, Blender and several others.
New users benefit of a FREE trial of 300 vCPU/Hours to be used on the platform in order to test the platform, all each features and verify if it is suitable for their needs
