Prerequisites: calculus (gradients, divergence), basic thermodynamics (pressure, temperature), classical mechanics (Newton’s second law). This post follows naturally from Learning #35 (Electromagnetism & Maxwell’s Equations) — many mathematical structures (vector fields, flux, potential theory) carry over directly.
Continuum Hypothesis & Fluid Properties
At macroscopic scales (length scales ≫ molecular spacing ∼ 0.3 nm), a fluid can be treated as a continuous medium characterised by field quantities: density ρ(r,t), velocity u(r,t), pressure p(r,t), and temperature T(r,t). This is the continuum hypothesis, valid when the Knudsen number Kn = λ/L ≪ 1 (λ = mean free path, L = characteristic flow length).
Dynamic viscosity μ quantifies a fluid’s resistance to shearing. Newtonian fluids (water, air, most simple liquids) obey Newton’s viscosity law: shear stress is proportional to shear rate.
τ = shear stress [Pa] μ = dynamic viscosity [Pa·s]
&partial;u/&partial;y = velocity gradient perpendicular to flow
Kinematic viscosity: ν = μ/ρ [m²/s]
Water at 20°C: μ ≈ 1.0 × 10-3 Pa·s
Air at 20°C: μ ≈ 1.8 × 10-5 Pa·s
Non-Newtonian fluids (blood, polymer melts, ketchup) have viscosity depending on shear rate. Shear-thinning (pseudoplastic) fluids become less viscous under high shear. Shear-thickening (dilatant) fluids become more viscous. Bingham plastics require a yield stress before flowing at all.
Continuity Equation & Mass Conservation
Mass cannot be created or destroyed. In differential form, this gives the continuity equation:
Incompressible flow (ρ = const):
∇·u = 0 (divergence-free velocity field)
Mass flux through a surface: ˙m = ∫∫ ρu·n dA
Integral form: d/dt ∫∫∫ ρ dV + ∮ ρu·dA = 0
The incompressibility condition ∇·u = 0 greatly simplifies the equations of motion and is an excellent approximation for liquids and for gas flows with Mach number Ma < 0.3.
Navier-Stokes Equations & Momentum Conservation
Applying Newton’s second law to a fluid parcel in the continuum limit — accounting for pressure gradients, viscous stress, and body forces — yields the Navier-Stokes equations. For incompressible flow:
Left side: inertial terms (rate of change + convective acceleration)
−∇p : pressure gradient force
μ∇²u : viscous diffusion of momentum
ρg : body force (gravity; can include Coriolis etc.)
These are a set of 3 equations (x, y, z components) + 1 continuity equation, giving 4 equations for 4 unknowns (u, v, w, p).
Solving the Navier-Stokes equations in full generality is one of the Millennium Prize Problems in mathematics — the existence and smoothness of solutions in 3D is not proven. In practice, engineers use DNS (direct numerical simulation), RANS (Reynolds-averaged), or LES (large-eddy simulation) at different scales of resolution.
Bénard Convection Simulator solves the 2D Boussinesq Navier-Stokes equations with a buoyancy term. Watch convection cells self-organise as the Rayleigh number Ra crosses the critical value of 1708.
Reynolds Number & the Laminar-Turbulent Transition
The Reynolds number Re is the most important dimensionless group in fluid mechanics. It is the ratio of inertial forces to viscous forces:
U = characteristic velocity L = characteristic length scale
Re < ~2300: laminar pipe flow (parallel streamlines, Re<∼1 for creeping)
2300 < Re < 4000: transitional (intermittent turbulence)
Re > ~4000: turbulent pipe flow (chaotic mixing, eddy cascade)
Flat-plate boundary layer transition: Rex ≈ 5×105
Turbulence involves a cascade of kinetic energy from large eddies (injected at scale L by mean flow shear) down to small Kolmogorov eddies (scale η = (ν³/ε)1/4) where viscosity dissipates energy as heat. The ratio L/η scales as Re3/4, which is why DNS of high-Re flows is computationally crushing.
Bernoulli’s Equation
For steady, incompressible, inviscid flow along a streamline, the Navier-Stokes equations reduce to Bernoulli’s equation:
p = static pressure ½ρu² = dynamic pressure
ρgz = hydrostatic pressure ptotal = p + ½ρu² = stagnation pressure
Venturi effect: A1u1 = A2u2 (continuity)
⇒ p1 − p2 = ½ρ(u2² − u1²)
Bernoulli’s equation explains aircraft lift (pressure difference between upper and lower wing surfaces), the operation of carburettors, aerofoil stall, and the Coandă effect. It fails where viscosity matters (boundary layers, pipe friction) or where there is significant flow unsteadiness.
Aerofoil Simulator computes potential flow around a symmetric or cambered aerofoil using conformal mapping (Joukowski transform), plotting pressure distribution and the lift coefficient CL as a function of angle of attack.
Darcy’s Law & Flow in Porous Media
At small Reynolds numbers (Re < 1 based on grain size), viscosity completely dominates inertial forces. Flow through porous media (sand, gravel, rock) at these conditions obeys Darcy’s empirical law (1856):
q = −K ∇h (saturated flow, K absorbs μ and ρg)
q = Darcy flux (specific discharge, m/s)
K = hydraulic conductivity (m/s) h = hydraulic head (m)
Average pore velocity: v = q / n n = porosity
Intrinsic permeability: k = Kμ/(ρg) [m²]
Hydraulic head h = z + p/(ρg) combines elevation head and pressure head. Flow always goes from high head to low head, regardless of whether this corresponds to high or low elevation. Hydraulic conductivity K spans 13 orders of magnitude: from 10-13 m/s in intact granite to 100 m/s in coarse gravel.
Groundwater Flow Equations
Combining Darcy’s law with the continuity equation gives the groundwater flow equation:
Ss = specific storage (m-1)
K = hydraulic conductivity tensor (m/s)
Q = source/sink term (pumping wells, recharge)
Steady-state: ∇·(K ∇h) = 0 (Laplace equation when K uniform)
Dupuit-Theis pumping well drawdown:
s(r,t) = (Q/4πT) · W(u) u = r²S/(4Tt)
T = hydraulic transmissivity = K ċ b b = aquifer thickness
W(u) = −Ei(−u) = Theis well function
The Theis solution assumes a uniform, isotropic, infinite confined aquifer. Real aquifers show anisotropy (Kx ≠ Ky), heterogeneity, unconfined conditions (free surface moves with pumping), and complex boundary conditions. Numerical models (MODFLOW, FEFLOW) are used for practical wellfield design.
Groundwater Flow Simulator solves the 2D steady-state groundwater flow equation on a 100×60 grid using successive over-relaxation. Inject pumping or injection wells, adjust hydraulic conductivity zones, and watch head contours and Darcy flux arrows update in real time.
Advection-Diffusion & the Péclet Number
Once we know the velocity field, we can calculate how a dissolved contaminant or tracer spreads. Transport is governed by two competing processes:
- Advection: transport by the mean flow velocity (directional, conserves mass).
- Diffusion/Dispersion: spreading by molecular diffusion + mechanical dispersion from pore-scale velocity variability.
C = concentration D = dispersion tensor R = reaction term
Péclet number: Pe = uL/D
Pe ≪ 1: diffusion-dominated (spreading isotropic)
Pe ≫ 1: advection-dominated (sharp fronts)
1D breakthrough curve (solute arriving at depth L):
C(t)/C0 = ½ erfc[(L/v − t)/(2√(Dt/v²L0))]
Mechanical dispersion Dm = αL v (longitudinal dispersivity αL ∼ 0.1–100 m depending on heterogeneity scale). In aquifer remediation, advection-diffusion modelling predicts contaminant plume extent and pump-and-treat efficiency.
Boundary Layer Theory & Internal Flows
Near a solid surface, viscosity matters even at high Re: the boundary layer is a thin region where the flow transitions from zero velocity at the wall (no-slip condition) to the free-stream velocity U∞. The boundary layer thickness δ grows along the plate:
δ/x ≈ 5.0 / √Rex Rex = U∞x/ν
Drag coefficient: CD = 1.328 / √ReL (laminar)
CD ≈ 0.074 ReL-1/5 (turbulent, ReL up to 107)
Skin friction: τw = μ (&partial;u/&partial;y)|y=0 = 0.332 μ U∞ √(U∞/(νx))
Hagen-Poiseuille (laminar pipe flow, Re < 2300):
Q = πR4Δp / (8μL) u(r) = (R²−r²)Δp/(4μL) (parabolic profile)
The Hagen-Poiseuille result shows that flow resistance scales as R4 — halving a pipe’s radius increases resistance 16-fold. This has profound implications for blood flow in the cardiovascular system: small arterioles contribute most of the total vascular resistance despite carrying little of the total volume.
Blood Flow Simulator visualises Hagen-Poiseuille flow in a network of vessels. Adjust vessel diameter to see how resistance and flow rates rebalance throughout the network. Includes Fahraeus-Lindqvist effect for red blood cell margination.
Connecting the Concepts
The threads of fluid mechanics tie together across the platform:
- Bénard Convection — natural convection driven by buoyancy; Rayleigh-Bénard instability; rolls and hexagonal cells
- Aerofoil — Bernoulli lift; potential flow; Joukowski transform; stall
- Groundwater Flow — Darcy flow; aquifer simulation; pumping well drawdown
- Blood Flow — Hagen-Poiseuille; vascular resistance; Fahraeus-Lindqvist
- Bath Waves — shallow water equations; surface gravity waves; dispersion
- Thermohaline Circulation — density-driven ocean currents; AMOC; double-diffusive convection
Summary: Key Dimensionless Groups
Fluid mechanics dimensionless numbers
Re = UL/ν — Reynolds: inertia/viscosity; laminar vs turbulentFr = U/√(gL) — Froude: inertia/gravity; sub- vs supercritical
Ma = U/c — Mach: flow speed/sound speed; compressibility
Pe = UL/D — Péclet: advection/diffusion; sharp vs diffuse fronts
Pr = ν/κ — Prandtl: momentum/thermal diffusivity
Ra = gβΔTL³/(νκ) — Rayleigh: buoyancy/viscous-diffusive; convection onset
Kn = λ/L — Knudsen: molecular/continuum regime boundary