Computational Fluid Dynamics is the science of predicting fluid flow , heat transfer , mass transfer , chemical reaction and related phenomena by solving mathematical equations which govern these processes using numerical methods (i.e. on a computer ). Why CFD…?? Growth in complexity of unsolved engineering problem. Need for quick solutions of moderate accuracy. Absence of analytical solutions. The prohibitive cost involved in performing even scaled laboratory experiments. Efficient solution algorithms. Developments in computers in terms of speed and storage. Serial/parallel/web computing. Sophisticated pre and post processing facilities.
Inside the CFD Process : CFD Process Flow : Pre-processing Geometry Creation Geometry Clean-up Mesh Generation Boundary conditions Solver Problem Specification Additional Models Numerical Computations Post-processing Understanding flow with color, contour etc. plots. Line and Contour Data Average Values (Drag, lift, heat transfer coefficient) Report Generation Pre-processing Solver Post-processing
Inside the CFD process … Analysis Begins with the mathematical model of a physical problem . Conservation of Mass, momentum and energy conservation must be satisfied throughout the region of interest. Simplifying assumptions are made to make the problem more tractable (e.g. steady state, incompressible, inviscid, two-dimensional etc.) Provide appropriate boundary and initial conditions for the problem. Domain of interest : Area between two fins Half thickness of fin First Thing First … Commercial Fin-tube Heat Exchanger CFD applies Numerical methods (called discretization) to develop algebraic equations to approximate the governing differential equations of fluid mechanics in the domain to be studied. Entire domain should be divided into small cells or volume. The collection of cells is called the grid or mesh. Meshing your way into it … Inside the CFD process … Mesh Generation
Inside the CFD process … Solver … Inside the CFD process … System of algebraic equations are solved numerically (on a computer) for the flow field variables at each node or cell. The final solution is post-processed to extract quantities of interest (e.g. lift, drag, heat transfer, separation points, pressure loss, etc.) What will I do with all this data …? Temperature Contours Discretization
Governing Equations: Conservation Of Mass Momentum Conservation Energy Conservation Two different forms of equations: Conservation form Non-Conservation form Inviscid & Viscid Equations Navier-Stokes Equation Euler Equations
Advantages of CFD: Low Cost: Using physical experiments and tests to get essential engineering data for design can be expensive. Computational simulations are relatively inexpensive, and costs are likely to decrease as computers become more powerful. Speed : CFD simulations can be executed in short period of time. Quick turnaround means engineering data be introduced early in design process. Ability to Simulate Real Conditions: Many flow and heat transfer processes can not be (easily) tested. E.g. hypersonic flow at Mach 20. CFD provides the ability to theoretically simulate any physical condition. Ability to Simulate Ideal Conditions : CFD allows great control over the physical process, and provides the ability to isolate specific phenomena for study. Example: a heat transfer process can be idealized with adiabatic, constant heat flux, or constant temperature boundaries . Comprehensive Information : Experiments only permit data to extracted at a limited number of locations in the system(e.g. pressure and temperature probes, heat flux gauges, LDV, etc.) CFD allows the analyst to examine a large number of locations in the region of interest, and yields a comprehensive set of flow parameters for examination.
Limitations of CFD : Physical Models: CFD solutions rely upon physical models of real processes (e.g. turbulence, compressibility, c hemistry, multiphase flow etc.) The solutions that are obtained through CFD can only be as accurate as the physical models on which they are based. Numerical Errors: Solving equations on a computer invariably introduces numerical errors. Round-off error - errors due to finite word size available on the computer. Truncation error - error due to approximates in the numerical models. Round-off errors will always exist( though they should be small in most cases). Truncation errors will go to zero as the grid is refined – so mesh refinement is one way to deal with truncation error. Boundary conditions: As with physical models, the accuracy of the CFD solution is only as good as the initial/boundary conditions provided to the numerical model Example : flow in a duct with sudden expansion. If flow is supplied to domain by a pipe, you should use a fully-developed profile for velocity rather than assume uniform conditions