What is Computational Fluid Dynamics?ApplicationsCFD - How It WorksCFD - How It Works (2)An Example: Water flow over a tube bankMesh GenerationUsing the SolverPost-processingAdvantages of CFDAdvantages of CFD (2)Limitations of CFDLimitations of CFD (2)Summary© Fluent Inc. 01/14/19A1Fluids ReviewTRN-1998-004What is Computational Fluid Dynamics?Computational Fluid Dynamics (CFD) is the science of predicting fluid flow, heat transfer, mass transfer, chemical reactions, and related phenomena by solving the mathematical equations which govern these processes using a numerical process (that is, on a computer).The result of CFD analyses is relevant engineering data used in:conceptual studies of new designsdetailed product developmenttroubleshootingredesignCFD analysis complements testing and experimentation.Reduces the total effort required in the laboratory.© Fluent Inc. 01/14/19A2Fluids ReviewTRN-1998-004ApplicationsApplications of CFD are numerous!flow and heat transfer in industrial processes (boilers, heat exchangers, combustion equipment, pumps, blowers, piping, etc.)aerodynamics of ground vehicles, aircraft, missilesfilm coating, thermoforming in material processing applicationsflow and heat transfer in propulsion and power generation systemsventilation, heating, and cooling flows in buildingschemical vapor deposition (CVD) for integrated circuit manufacturingheat transfer for electronics packaging applicationsand many, many more...© Fluent Inc. 01/14/19A3Fluids ReviewTRN-1998-004CFD - How It WorksAnalysis begins with a mathematical model of a physical problem.Conservation of matter, momentum, and energy must be satisfied throughout the region of interest.Fluid properties are modeled empirically.Simplifying assumptions are made in order to make the problem tractable (e.g., steady-state, incompressible, inviscid, two-dimensional).Provide appropriate initial and/or boundary conditions for the problem.Domain for bottle filling problem.Filling NozzleBottle© Fluent Inc. 01/14/19A4Fluids ReviewTRN-1998-004CFD - How It Works (2)CFD applies numerical methods (called discretization) to develop approximations of the governing equations of fluid mechanics and the fluid region to be studied.Governing differential equations  algebraicThe collection of cells is called the grid or mesh.The set of approximating equations are solved numerically (on a computer) for the flow field variables at each node or cell.System of equations are solved simultaneously to provide solution.The solution is post-processed to extract quantities of interest (e.g. lift, drag, heat transfer, separation points, pressure loss, etc.). Mesh for bottle filling problem.© Fluent Inc. 01/14/19A5Fluids ReviewTRN-1998-004An Example: Water flow over a tube bankGoalcompute average pressure drop, heat transfer per tube rowAssumptionsflow is two-dimensional, laminar, incompressibleflow approaching tube bank is steady with a known velocitybody forces due to gravity are negligibleflow is translationally periodic (i.e. geometry repeats itself)Physical System can be modeled with repeating geometry.© Fluent Inc. 01/14/19A6Fluids ReviewTRN-1998-004Mesh GenerationGeometry created or imported into preprocessor for meshing.Mesh is generated for the fluid region (and/or solid region for conduction).A fine structured mesh is placed around cylinders to help resolve boundary layer flow.Unstructured mesh is used for remaining fluid areas.Identify interfaces to which boundary conditions will be applied.cylindrical wallsinlet and outletssymmetry and periodic facesSection of mesh for tube bank problem© Fluent Inc. 01/14/19A7Fluids ReviewTRN-1998-004Using the SolverImport mesh.Select solver methodology.Define operating and boundary conditions.e.g., no-slip, qw or Tw at walls.Initialize field and iterate for solution.Adjust solver parameters and/or mesh for convergence problems.© Fluent Inc. 01/14/19A8Fluids ReviewTRN-1998-004Post-processingExtract relevant engineering data from solution in the form of:x-y plotscontour plotsvector plotssurface/volume integrationforcesfluxesparticle trajectoriesTemperature contours within the fluid region.© Fluent Inc. 01/14/19A9Fluids ReviewTRN-1998-004Advantages 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 a short period of time.Quick turnaround means engineering data can be introduced early in the 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© Fluent Inc. 01/14/19A10Fluids ReviewTRN-1998-004Advantages of CFD (2)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 be 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.© Fluent Inc. 01/14/19A11Fluids ReviewTRN-1998-004Limitations of CFDPhysical Models CFD solutions rely upon physical models of real world processes (e.g. turbulence, compressibility, chemistry, 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 approximations 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.©