Flow around a cylinder

Category: Fluid Analysis (CFD) | Integrated 2026-04-06
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Flow around a cylinder

Flow around a cylinder: Theoretical Foundations

Overview

🧑‍🎓

Professor, is flow around a cylinder just about wind hitting a pole?


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It looks simple, but the flow structure changes dramatically depending on the Reynolds number. It's a classic and fundamental problem in fluid mechanics textbooks, ranging from steady symmetric separation to Kármán vortex streets and even turbulent transition.


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The Kármán vortex street is that thing where vortices shed alternately, right? Why do they alternate?


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When Re exceeds about 47, the symmetry of the wake becomes absolutely unstable. A feedback loop is created as the separating shear layer on one side entrains vorticity from the opposite side, causing vortices to shed alternately from the top and bottom. This is the Benard-von Kármán vortex street.


Flow Classification by Reynolds Number

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How much does it change with the Reynolds number?


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It can be summarized as follows.


Re RangeFlow StateCharacteristics
Re < 5Creeping FlowFore-aft symmetric, no separation
5 < Re < 47Steady Twin VorticesSymmetric recirculation zone forms
47 < Re < 1902D Kármán Vortex StreetPeriodic vortex shedding, Laminar Flow
190 < Re < 2603D Transition (Mode A/B)Spanwise instabilities appear
260 < Re < 1000Transition to TurbulenceWake becomes turbulent, separation point remains laminar
$10^3$ < Re < $3 \times 10^5$Subcritical RegimeLaminar separation, $C_D \approx 1.2$
$3 \times 10^5$ < Re < $10^6$Critical Regime (Drag Crisis)Transition occurs before separation, $C_D$ drops sharply
Re > $10^6$Supercritical RegimeTurbulent boundary layer separation
🧑‍🎓

The vortex street appears at Re = 47? That's surprisingly low.


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Yes. This threshold corresponds to a Hopf bifurcation. Linear stability analysis yields a precise critical Re value of $Re_{cr} \approx 46.7$.


Governing Equations

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Then, please tell me the governing equations.


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The Incompressible Navier-Stokes equations.


$$ \nabla \cdot \mathbf{u} = 0 $$

$$ \frac{\partial \mathbf{u}}{\partial t} + (\mathbf{u} \cdot \nabla)\mathbf{u} = -\frac{1}{\rho}\nabla p + \nu \nabla^2 \mathbf{u} $$

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Here, $\nu = \mu / \rho$ is the kinematic viscosity, $\mathbf{u}$ is the velocity vector, and $p$ is pressure. Non-dimensionalization yields the Reynolds number $Re = U_\infty D / \nu$ as the sole governing parameter.


Strouhal Number and Vortex Shedding Frequency

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Can the vortex shedding frequency be predicted?


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It is organized using the Strouhal number.


$$ \mathrm{St} = \frac{f D}{U_\infty} $$

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In the subcritical regime ($300 < Re < 3 \times 10^5$), $\mathrm{St} \approx 0.2$ remains nearly constant. This is a famous result confirmed by Roshko's experiments. On the low Re side, the following empirical formula is often used as a function of Re.


$$ \mathrm{St} = 0.198 \left(1 - \frac{19.7}{Re}\right), \quad 250 < Re < 2 \times 10^5 $$

Drag and Lift Coefficient

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Let me also confirm the definition of the drag coefficient.


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The definition per unit span length is as follows.


$$ C_D = \frac{F_D}{\frac{1}{2}\rho U_\infty^2 D}, \quad C_L = \frac{F_L}{\frac{1}{2}\rho U_\infty^2 D} $$

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The steady flow $C_D$ varies greatly with Re. In the Stokes regime, $C_D \propto Re^{-1}$; in the subcritical regime, $C_D \approx 1.0 \text{--} 1.2$; in the critical regime, it drops to about $C_D \approx 0.3$; and in the supercritical regime, it recovers to about $C_D \approx 0.6 \text{--} 0.7$.


🧑‍🎓

Does the lift fluctuate at the same frequency as the vortex shedding?


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The lift fluctuation frequency is exactly the vortex shedding frequency $f$. On the other hand, the drag fluctuation frequency is $2f$. This is because drag increases and decreases with each vortex shed alternately, while lift changes sign with the shedding from one side.


🧑‍🎓

Drag being $2f$ is interesting. Now that you mention it, it makes sense.

Coffee Break Trivia

Kármán Vortices and Chimney Collapse—How the Strouhal Number Protects Buildings

The Kármán vortex street generated in the wake of a cylinder can sometimes cause serious engineering problems. When the vortex shedding frequency ($f = St \cdot U/D$) matches the natural frequency of a structure, resonance occurs, amplifying vibrations. The 1965 collapse of three cooling towers in a row at the Ferrybridge Power Station in the UK was also determined to be caused by vortex-induced vibration from Kármán vortices. Whether CFD can accurately calculate the Strouhal number directly impacts cost (or safety) in the design of chimneys, bridge girders, and marine riser pipes. "Kármán vortices appear even in 2D laminar CFD at Re≈100" serves as a useful benchmark for verifying the dynamic behavior of code.

Computational Methods for Flow around a cylinder

Selection of Numerical Method

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When solving flow around a cylinder with CFD, which method should I use?


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The optimal method changes depending on the Reynolds number. It can be summarized as follows.


Re RangeRecommended MethodReason
Re < 200DNS (Direct Numerical Simulation)2D calculation is sufficient; all scales can be resolved
200 < Re < 1000DNS (3D)3D instabilities need to be resolved
$10^3$ < Re < $10^4$LESDirectly resolves turbulent structures in the wake
$10^4$ < Re < $10^6$URANS / DES / DDESWall resolution cost for LES becomes prohibitive
Re > $10^6$RANS (SST $k$-$\omega$)Sufficient for engineering accuracy in many cases
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Wouldn't it be best to solve everything with DNS?


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High Re DNS scales with grid points as $Re^{9/4}$. For Re=$10^6$, over $10^{13}$ points are needed, which is unrealistic even with current supercomputers.


Pressure-Velocity Coupling

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For incompressible cases, how is pressure solved?


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In incompressible Navier-Stokes, the pressure Poisson equation must be solved. Representative methods are as follows.


  • SIMPLE Method: Patankar's semi-implicit method. Suitable for steady calculations. Pressure correction is found iteratively.
  • PISO Method: Suitable for unsteady calculations. Performs two pressure corrections within one time step.
  • Coupled Solver: Solves velocity and pressure simultaneously. Fast convergence but high memory consumption.
  • Fractional Step Method: Finds an intermediate velocity, then corrects via pressure Poisson. Widely used in DNS.

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