CFD (Computational Fluid Dynamics) Basics

Definition & Context

Computational Fluid Dynamics (CFD) numerically solves the Navier–Stokes equations (conservation of mass, momentum, and energy) over a discretised fluid domain using the finite-volume method. For most engineering flows the Reynolds-Averaged Navier–Stokes (RANS) approach is used with a turbulence closure model — k-ε, k-ω SST, or Spalart–Allmaras.

A CFD study requires a watertight flow volume, a mesh with resolved boundary layers, boundary conditions (inlet velocity/pressure, outlet, walls, symmetry), a fluid material model, and solver settings (steady vs transient, discretisation scheme). Convergence is judged by residuals plus monitored quantities such as drag, mass-flow imbalance, or outlet temperature.

Why It Matters

CFD predicts pressure drop, drag, lift, heat transfer, and mixing without wind-tunnel or flow-loop testing, informing everything from electronics cooling to aerodynamics. Because turbulence is modelled (not resolved) in RANS, understanding the assumptions behind each model is essential to trust the numbers.

Trustworthy CFD is mostly about matching model choices to the physics: k-ω SST resolves adverse-pressure-gradient and separated flows better than k-ε, but only if the near-wall mesh meets the y+ that model assumes. A converged solution is necessary but not sufficient — residuals can flatten on a steady solve of a flow that is genuinely transient, so monitored quantities (drag, mass-flow imbalance, outlet temperature) and, where needed, a transient or scale-resolving (LES/DES) run are what separate a plausible picture from a validated prediction.

Best Practices

• Resolve the near-wall region correctly: use y+ ≈ 1 with wall-resolved models, or 30–300 with wall functions.
• Run a mesh-independence study on an integral quantity (drag, ΔP) before believing the result.
• Choose the turbulence model for the physics: k-ω SST for adverse pressure gradients/separation, k-ε for free shear flows.
• Monitor a physical quantity, not just residuals — residuals can flatline while the solution still drifts.
• Check global mass and energy balance across the domain as a conservation sanity check.

Common Pitfalls

• Under-resolved boundary layers giving wrong wall shear stress and heat transfer.
• Declaring convergence on residuals alone while monitored forces are still changing.
• Using a steady solver on an inherently unsteady flow (vortex shedding, large separation).
• Poor-quality cells at walls producing non-physical local velocities.

Sources & Further Reading

• NASA — Turbulence modeling resource
• SimScale — CFD fundamentals

Related Concepts

• Mesh Generation — boundary-layer meshing and y+
• Thermal Analysis — conjugate heat transfer couples CFD and conduction
• Finite Element Analysis — the structural counterpart

Enterprise Production Implementation & GstarCAD 2027 Workflow

• Database Serialization & Binary Fidelity: Ensure all entities and symbol table records associated with CFD (Computational Fluid Dynamics) Basics are authored on standardized ISO 13567 layers rather than Layer 0 or Defpoints, and verify lossless round-trip persistence in native DWG (AC1032) format.