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NOTE #012DAY WED CFD기법DATE 2026.03.25READ 3 min readWORDS 551#시각화#Reynolds#유동천이#유체역학

Reynolds Number and Flow Transition, Through Visualization

Understand Reynolds number and laminar–turbulent transition through interactive visualization

What Is the Reynolds Number?#

One of the most important dimensionless numbers in fluid flow is the Reynolds number (Re). It expresses the ratio of inertial to viscous forces.

Re=ρULμ=ULνRe = \frac{\rho U L}{\mu} = \frac{U L}{\nu}

Where:

  • ρ\rho: fluid density [kg/m3][\text{kg/m}^3]
  • UU: characteristic velocity [m/s][\text{m/s}]
  • LL: characteristic length [m][\text{m}]
  • μ\mu: dynamic viscosity [Pa\cdotps][\text{Pa·s}]
  • ν=μ/ρ\nu = \mu/\rho: kinematic viscosity [m2/s][\text{m}^2/\text{s}]

Flow Regimes#

Reynolds rangeFlow regimeCharacter
Re1Re \ll 1Creeping (Stokes) flowViscosity-dominated, fully laminar
Re<2300Re < 2300 (pipe flow)LaminarOrderly layered flow
2300<Re<40002300 < Re < 4000TransitionalUnstable, intermittent turbulence
Re>4000Re > 4000TurbulentIrregular mixing, high energy dissipation

The Physics of Transition#

The path from laminar to turbulent flow begins with the Kelvin–Helmholtz instability. At a boundary with a velocity gradient, small disturbances grow and roll into vortices, which cascade energy down the scales.

The governing equation:

ut+(u)u=1ρp+ν2u\frac{\partial \mathbf{u}}{\partial t} + (\mathbf{u} \cdot \nabla)\mathbf{u} = -\frac{1}{\rho}\nabla p + \nu \nabla^2 \mathbf{u}

In the Navier–Stokes equations, the nonlinear term (u)u(\mathbf{u} \cdot \nabla)\mathbf{u} on the left carries inertia, while ν2u\nu \nabla^2 \mathbf{u} on the right damps via viscosity. The Reynolds number measures the relative size of these two.

Velocity-Field Visualization: How Flow Changes with Re#

Try the simulation below to see velocity fields shift as Reynolds number changes:

속도장 시각화

What to look for:

  • Low Re (Re ≈ 1–50): vectors smooth and orderly — viscosity damps disturbances immediately
  • Mid Re (Re ≈ 100–500): asymmetry appears in obstacle wakes — inertia rivals viscosity
  • High Re (Re > 1000): vector directions become irregular and vortex structures develop

Streamlines Past a Cylinder: the Kármán Vortex Street#

For flow past a cylinder, increasing Reynolds number produces a periodic vortex shedding called the Kármán vortex street.

The shedding frequency is normalized by the Strouhal number StSt:

St=fDUSt = \frac{f D}{U_\infty}

Where ff is shedding frequency, DD is cylinder diameter, UU_\infty is freestream velocity. For a cylinder, St0.2St \approx 0.2 stays roughly constant over 100<Re<105100 < Re < 10^5.

Check the streamline pattern in the cylinder wake below:

유선 시각화

What to look for:

  • The stagnation point at the front of the cylinder, where streamlines split
  • Symmetry breaking in the wake region as periodic vortex shedding starts
  • Increasing speed (higher freestream) intensifies wake instability

Reynolds Number in Numerics: Grid Requirements#

Direct numerical simulation (DNS) of turbulence must resolve down to the smallest scale, the Kolmogorov microscale:

η=(ν3ε)1/4\eta = \left(\frac{\nu^3}{\varepsilon}\right)^{1/4}

Total grid count scales with Reynolds number as:

NRe9/4N \sim Re^{9/4}

So a 10× increase in ReRe demands roughly 178× more grid points. This is why practical turbulence simulations rely on RANS or LES models.

Summary#

  • The Reynolds number is the inertial-to-viscous ratio—the key dimensionless number for flow behavior
  • Above critical Re, flow follows laminar → transitional → turbulent
  • Cylinder wakes develop the Kármán vortex street, characterized by Strouhal number
  • DNS grid cost scales as Re9/4Re^{9/4}, so high-Re flows need turbulence models

Next week we cover how to discretize these Navier–Stokes equations with the finite volume method (FVM) and compare upwind vs. central-difference schemes for accuracy.

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