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Click on any CAD/CAE term below to expand its definition.

- ALE: Arbitrary Lagrangian EularianALE is a mathematical model which simulates both fluids and solids in a single environment. It represents a combination of a mesh that deflects (using Lagrangian-based math) to simulate structural deformation and a mesh that is stationary (using Eularian-based math) to simulate fluid flow. When used in conjunction with Explicit FEA code, ALE accurately simulates very large deformations with very small time scales. It’s used in simulations such as metal forming/stamping/casting processes, bird strike simulations, car crashes, and other various Fluid Structure Interaction analyses.
- Bi: Biot NumberRatio of heat transfer at the surface of a body to heat conducted within the body. Bi determines if a certain volume will have a temperature gradient (Bi > 0.1) or a constant temperature (Bi < 0.1).
- CFD: Computational Fluid DynamicsGeneral term for software used to perform a fluid dynamics analysis. Typically the inputs are velocity (or flow rates) and pressures and outputs are full field visualization of velocities, pressures, and specific flow characteristics such as streamlines and iso-surfaces. Often, the fluid flow is coupled with conjugate heat transfer, which solves the temperature variable as well.
- DNS: Direct Numerical SimulationThis is a mathematical approach in CFD which directly solves the Navier-Stokes equations. This approach can be extremely accurate, however it needs a very fine mesh to characterize all of the detail (i.e. small turbulent eddies), and therefore is very computationally expensive!
- DOE: Design of ExperimentsThis is a methodical approach to testing a design by encompassing all of the necessary variables, and establishing their relationship with the overall design goals. DOE’s are especially easy to accomplish with FEA & CFD simulation software, since the underlying variables are already recognized by the software for solving the underlying equations of state.
- FEA: Finite Element AnalysisFEA is a general term for software which performs structural simulations. Typical inputs are constraints and pressure/force loads, and outputs are deflection (and therefore strain & stress). Additional variables may also be temperature (for a thermal analysis) and velocity & acceleration (for structural dynamics).
- FSI: Fluid Structure InteractionFSI is a general term for an analysis which includes both fluids and structures. In this case, a set of governing equations calculate internal deflections/strains within the structure, and also the velocity and pressure of the flow field. In most cases, this is a highly iterative approach, where the analysis begins by calculating the pressure which the fluid imparts onto the structure. This pressure thus deforms the structure, which in turn changes the flow field around the structure. The new deflection is then recalculated and the process continues until equilibrium is attained within the analysis.
- Gr: Grashof NumberRatio of fluid buoyancy stress to viscous stress. Gr is a Flow Property which determines when a natural convection-driven boundary layer transitions from laminar (Gr < 10^8) to turbulent (10^9 < Gr).
- k-ε: K-epsilon Turbulence ModelK-epsilon is a “two-equation” turbulence model which solves the Turbulent Kinetic Energy (k) and the rate of dissipation (ε) of Kinetic Energy of the fluid flow. It is the most commonly used turbulence model, as it is stable and widely applicable, however it is not the best model for curved or rotating flow, or high pressure gradients.
- k-ω: K-omega Turbulence ModelK-omega is a “two-equation” turbulence model which solves the Turbulent Kinetic Energy (k) and the specific rate of dissipation (ω) of Kinetic Energy of the fluid flow. Compared to the K-epsilon model, it is more accurate in predicting fluid flow through curved and internal flow (such as through a pipe bend), but is less stable.
- LBM: Lattice Boltzmann MethodLBM is a type of CFD which focuses on detailed particle physics, instead of the traditional “big picture” approach developed by Navier-Stokes. To do this, the LBM creates imaginary particles in the fluid, and then predicts the interaction of those particles with each other. These interactions, made up of “streams” & “collisions”, are then used to predict the fluid flow properties. LBM is very effective for highly turbulent and multi-phase flows (because of it’s attention to detail), and is currently being developed for high Mach number applications.
- LES: Large Eddy SimulationLES is a turbulence model which predicts the behavior of turbulent fluid flow in CFD Code. Eddies exist in varying sizes within turbulent flow. The LES model is a “low pass filter” of sorts, where it dismisses small eddies, and only calculations the large ones. LES assumes that large eddies primarily influence the overall fluid flow, and it is not worth the computational effort to calculate the flow field of the small eddies .
- M: Mach NumberRatio of the velocity of a fluid to the speed of sound. M determines when to take the incompressibility of air into account in a CFD simulation (1 < M). Due to local fluid velocities, incompressibility could impact the flow in the transonic region (0.7 < M < 1).
- NSE: Navier-Stokes EquationsThe Navier-Stokes equations are nonlinear partial differential equations which describe fluid flow. These equations solve for Velocity using the Conservation of Mass, Momentum, and Energy thus derived from Newton’s Second Law of Motion. They are the backbone of the popular “RANS” type of CFD software, and are most often coupled with a turbulence model such as k-ε, k-ω, or SST to predict fluid flow properties.
- Nu: Nusselt NumberRatio of heat transfer across a fluid boundary via convection to heat transfer via conduction. Nu determines the effectiveness of convection, due to the fluid flow. When Nu =1, the flow at the boundary is characteristically laminar, whereas the turbulent flow has a Nu ~ 10^2-10^3.
- Pr: Prandtl NumberRatio of fluid velocity boundary layer thickness to the fluid temperature boundary layer thickness. Pr is a Fluid Property which characterizes whether a certain fluid will transfer heat primarily via conduction (Pr << 1; such as mercury, some noble gases) or via convection (1 << Pr; such as engine oil). Pr (water) ~ 7, and Pr (air) ~ 0.75.
- Ra: Rayleigh NumberThe product of the Grashof number (Gr) and the Prandtl Number (Pr). Ra determines whether conduction or convection is the primary heat transfer for a buoyancy-driven flow (such as natural convection). It is a combination of the material properties (Gr) and the flow properties (Pr).
- RANS: Reynolds-Averaged Navier-StokesRANS equations allow the simplification of turbulent flow in CFD code. Turbulence is a highly transient and unpredictable phenomena, and as a result it is time-dependant and statistical in nature. RANS equations convert transient turbulence into a steady-state equivalence by averaging the flow variables over time. This makes the math easier to converge, and ultimately facilitates a quicker solution in a CFD analysis.
- Re: Reynolds NumberRatio of fluid inertia stress to viscous stress. Re is a Flow Property which determines when the fluid flow transitions from laminar to turbulent. Fluid flow in a pipe is laminar when Re < 2300, and turbulent when 4000 < Re, with transition in between. Fluid flow over a flat plate has a laminar boundary layer transition to turbulent at the point at which Re ~ 5 X 10^5.