• Fluid dynamics is the science of fluid motion.
• Fluid flow is commonly studied in one of three ways:
– Experimental fluid dynamics.
– Theoretical fluid dynamics.
– Numerically: computational fluid dynamics (CFD).
• During this course we will focus on obtaining the knowledge required to be able to solve practical fluid flow problems using CFD.
• Topics covered today include:
– A brief review of the history of fluid dynamics.
– An introductory overview of CFD.
Advantages of CFD
• Relatively low cost.
– Using physical experiments and tests to get essential engineering data for design can be expensive.
– CFD simulations are relatively inexpensive, and costs are likely to decrease as computers become more powerful.
– 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,
eg. hypersonic flow.
– 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 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.
Limitations of CFD
• Physical models.
– CFD solutions rely upon physical models of real world processes (e.g. turbulence, compressibility, chemistry, multiphase flow, etc.).
– The CFD solutions 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: due to finite word size available on the computer. Round-off errors will always exist (though they can be small in most cases).
– Truncation error: due to approximations in the numerical models. Truncation errors will go to zero as the grid is refined. 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.