Page 22 - Introduction to Computational Fluid Dynamics

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1 Introduction May 20, 2005 12:20

1.1 CFD Activity

Computational fluid dynamics (CFD) is concerned with numerical solution of dif-
ferential equations governing transport of mass, momentum, and energy in moving
fluids. CFD activity emerged and gained prominence with availability of com-
puters in the early 1960s. Today, CFD finds extensive usage in basic and applied
research, in design of engineering equipment, and in calculation of environmental
and geophysical phenomena. Since the early 1970s, commercial software packages
(or computer codes) became available, making CFD an important component of
engineering practise in industrial, defence, and environmental organizations.
For a long time, design (as it relates to sizing, economic operation, and safety) of
engineering equipment such as heat exchangers, furnaces, cooling towers, internal
combustion engines, gas turbine engines, hydraulic pumps and turbines, aircraft
bodies, sea-going vessels, and rockets depended on painstakingly generated empir-
ical information. The same was the case with numerous industrial processes such
as casting, welding, alloying, mixing, drying, air-conditioning, spraying, environ-
mental discharging of pollutants, and so on. The empirical information is typically
displayed in the form of correlations or tables and nomograms among the main
influencing variables. Such information is extensively availed by designers and
consultants from handbooks [55].
The main difficulty with empirical information is that it is applicable only to
the limited range of scales of fluid velocity, temperature, time, or length for which
it is generated. Thus, to take advantage of economies of scale, for example, when
engineers were called upon to design a higher capacity power plant, boiler furnaces,
condensers, and turbines of ever higher dimensions had to be designed for which
new empirical information had to be generated all over again. The generation of
this new information was by no means an easy task. This was because the informa-
tion applicable to bigger scales had to be, after all, generated via laboratory-scale
models. This required establishment of scaling laws to ensure geometric, kinematic,
and dynamic similarities between models and the full-scale equipment. This activity

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