cfd report (introduction to cfd)

7/24/2019 CFD Report (Introduction to CFD)

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Computational Fluid Dynamics (CFD) and Its Applications

Definition of Computational Fluid Dynamics (CFD)

Computational Fluid Dynamics or CFD is the analysis involving fluid flow, heat transfer and

associated phenomena such as chemical reactions by means of computer-based simulation.

Computers provide solutions to the problem of external airflow over a wide variety of shapes.

Computational fluid dynamics (CFD) uses numerical methods and algorithms to solve and

analye problems that involve fluid flows, computers are used to perform the millions of

calculations re!uired to simulate the interaction of li!uids and gases with surfaces defined by

boundary conditions.

"ven with high-speed supercomputers only approximate solutions can be achieved in many

cases. #ngoing research, however, may yield software that improves the accuracy and speed of

complex simulation scenarios such as transonic or turbulent flows. $nitial validation of such

software is often performed using a wind tunnel or by other experimental means.

CFD is divided into three steps%

&. 're-processor (rid generation). *olver (+umerical simulation). 'ost-process analysis.

he body of the configuration and the space surrounding it are represented by clusters of

points, lines and surfaces e!uations are solved at these points.

Application areas and advantages

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he techni!ue is very powerful and spans a wide range of industrial and non-industrial

application areas. *ome example are%

/erodynamics of aircraft and vehicles% lift and drag

0ydrodynamics of ships

'ower plant% combustion in $C engines and gas turbines

urbomachinery% flows inside rotating passages, diffusers, etc.

"lectrical and electronic engineering% cooling e!uipment including micro-circuits.

Chemical process engineering% mixing and separation, polymer molding

"xternal and internal environment of buildings% wind loading and heating 1 ventilation

2arine engineering% loads on off-shore structures

"nvironmental engineering% distribution of pollutants and effluents

0ydrology and oceanography% flows in rivers, estuaries, oceans 2eteorology% weather prediction

3iomedical engineering% blood flows through arteries and veins.

From the &4567s onwards the aerospace industry has integrated CFD techni!ues into the

design, 89D and manufacture of aircraft and :et engines. 2ore recently the methods have been

applied to the design of internal combustion engines, combustion chambers of gas turbines and

furnaces. Furthermore, motor vehicle manufacturers now routinely predict drag forces, under-

bonnet air flows and the in-car environment with CFD. $ncreasingly CFD is becoming vital

component in the design of industrial products and processes.

he ultimate aim of developments in the CFD field is to provide a capability comparable to other

C/" (Computer-/ided "ngineering) tools such as stress analysis codes. he main reason why

CFD has lagged behind the tremendous complexity of the underlying behavior, with precludes a

description of fluid flows that is at the same time economical and sufficiently complete. he

availability of affordable high performance computing hardware and the introduction of user

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friendly interfaces have led to a recent upsurge of interest and CFD is poised to ma;e an entry

into the wider industrial community in the years to come.

2oreover, there are several uni!ue advantages of CFD over experiment-based approaches to

fluid systems design%

*ubstantial reduction of lead times and cost of new designs.

/bility to study systems where controlled experiments are difficult or impossible to

perform (e.g. very large systems)

/bility to study systems under haardous conditions at and beyond their normal

performance limits (e.g. safety studies and accident scenarios).

'ractically unlimited level of detail of results.

he variable cost of an experiment, in terms of facility hire and1or man-hour costs, is

proportional to the number of data points and the number of configurations tested. $n contrast to

CFD codes can produce extremely large volumes of results at virtually no added expense and it

is very cheap to perform parametric studies, for instance to optimie e!uipment performance.

Computational Fluid Dynamics Code

CFD codes are structured around the numerical algorithmsthat can tac;le fluid flow problems.

$n order o provide easy access to their solving power all commercial CFD pac;ages include

sophisticated user interfaces to input problem parameters and to examine the results. /s stated

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before, all codes contain three main elements% a pre-processor, a solver and a post-

processor.

Pre-processor

're-processing consist of the input of a flow problem to a CFD program by means of an

operator-friendly interface an the subse!uent transformation of this input into a form suitable for

use by the solver. he user activities at the pre-processing stage involve%

Definition of the geometry of the region of interest% the computational domain.

rid generation the subdivision of the domain into a number of smaller, non-overlapping

sub-domains% a grid (or a mesh) of cells (or control volumes or elements). *election of the physical and chemical phenomena that need to be modeled.

*pecification of appropriate boundary conditions at cells which coincide with or touch the

domain boundary.

he solution of a flow problem is defined at nodes inside each cell. he accuracy of a CFD

solution is governed by the number of cells in the grid. $n general, the larger the number of cells,

the better the solution accuracy.

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*olution of the algebraic e!uations.

he main differences between the three separate streams are associated with the way in which

the flow variables are approximated and with the discretisation processes.

Finite difference methods. hese describe the un;nowns of the flow problems by means of

point samples at the node points of a grid of co-ordinate lines. runcated aylor series

expansions are often used to generate finite difference approximations of derivatives of in

terms of point samples of at each grid point and its immediate neighbors. hose derivatives

appearing in the governing e!uation are replaced by finite differences yielding an algebraic

e!uation for the values of at each grid points.

Finite element method. Finite element methods use simple piecewise functions (e.g. linear or

!uadratic) valid on elements to describe the local variations of un;nown flow variables . he

governing e!uation is precisely satisfied by the exact solution . $f the piecewise approximating

functions for are substituted into the e!uation it will not hold exactly and a residual is defined

to measure errors. +ext the residuals (and hence the errors) are minimied in some sense by

multiplying them by a set of weighting functions and integrating. /s a result we obtain a set of

algebraic e!uations for the un;nown coefficients of the approximation functions.

Spectral methods.*pectral methods approximate the un;nowns by means of truncated Fourier

series or series of Chebyshev polynomials. >nli;e the finite difference or finite element

approach the approximations are not local but valid throughout the entire computational domain.

/gain we replace the un;nowns in the governing e!uation by the truncated series. he

constraint that leads to the algebraic e!uations for the coefficients of the Fourier or Chebyshev

series is provided by weighted residuals concept similar to the finite element method or by

ma;ing the approximate function coincides with the exact solution at a number of grid points.

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Post-processor

/s in pre-processing a huege amount of development wor; has recently ta;en place in the post-

processing field. #wing to the increased popularity of engineering wor;stations, many of which

have outstanding graphics capabilities, the leading CFD pac;ages are now e!uipped with

versatile data visualiation tools. hese include%

Domain geometry and grid display.

?ector plots

@ine and shaded contour plots

D and D surface plots

'article trac;ing

?iew manipulation (translation, rotation, scaling, etc.)

Color postscript output

2ore recently these facilities may also include animation for dynamic result display and in

addition to graphics all codes produce trusty alphanumeric output and have data export facilities

for further manipulation external to the code. /s in many other branches of C/" the graphics

output capabilities of CFD codes have revolutionied the communication of ideas to the non-

specialist.

Solving problems with CFD

$n solving fluid problems we need to be aware that the underlying physics is complex and the

results generated by a CFD code are at best as good as the physics (and chemistry) embedded

in it and at worst as good as its operator. 'rior to setting up and running a CFD simulation there

is a stage of identification and formulation of the flow problem in terms of the physical anc

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chemical phenomena that need to be considered. ypical decisions that might be needed are

whether to model a problem un two or three dimensions, to exclude the effects of ambient

temperature or pressure variations on the density of an air flow, to choose to solve the turbulent

flow e!uations or to neglect the effects of small air bubbles dissolved in tap water.

/ good understanding of the numerical solution algorithm is also crucial. hree mathematical

concepts are useful in determining the success or otherwise of such algorithms% convergence,

consistency and stability.

Convergence. $s the property of a numerical method to produce a solution which approaches

the exact solution as the grid spacing, control volume sie or element sie is reduced to ero.

Consistency.Consistent numerical shemes produce systems of algebraic e!uations which can

be demonstrated to be e!uivalent to the original governing e!uation as the grid spacing tends to

ero.

Stability. his is associated with damping of errors as the numerical method proceeds. $f a

techni!ue is not stable even round off errors in the initial data can cause wild oscillations or

divergence.

CFD Computation involves the cration of a set of numbers that (hopefully) constitutes a realistic

approximation of a real-life system. #ne of the advantages of CFD is that the user has an

almost unlimited choice of the level of detail of the results, but in the prescient words of

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guarantees with regard to the accuracy of a simulation, we need to validate our results

fre!uently and stringently.

$t is clear that there are guidelines for good operating practice which can assist the user of a

CFD code and repeated validation plays a ;ey role as the final !uality control mechanism.

0owever, the main ingredients for success in CFD are experience and a thorough

understanding of the physics of fluids flows and the fundamentals of the numerical algorithms.

Eamples of CFD simulations

!) / thin elastic bar immersed in incompressible fluid develops self-induced time-periodic

oscillations of different amplitude depending on the material properties assumed

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") hese pictures illustrates the simulation of a valve. he valve begins in the < degree

open position, moves to fully opened, then finally to the fully closed position.

#) his picture shows the simulation of a F& race car. he stream ribbons demonstrate

airflow movement around tires and along body.

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$) 'ressure Distribution and ?elocity on $mpeller

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cfd report (introduction to cfd)

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