fluent training 26oct06
TRANSCRIPT
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What is CFD
CFD is the science of predicting fluid flow, heat and mass transfer,chemical reactions and related phenomenon by solving numericallythe set of governing mathematical equations
Conservation of mass, momentum, energy, species.
The results of CFD analysis are relevant in:
conceptual studies of new designs
detailed product development
troubleshooting
redesign
CFD analysis complements testing and experimentation Reduces the total effort required in the experiment design
and data acquisition
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FLUENT 6.3
Applications
External/Internal automotive flows and
in-cylinder flows
High speed aerodynamics
Rocket Flows
Turbo machinery
Reactor Vessels
Cyclones
Mixing Tanks Flow-induced noise prediction
Surface pressure distribution in anautomotive engine cooling jacket
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Pre- p r oc e sso r: GAMBIT
A singl e int e g r at ed p re- p r oc e sso r fo r
CFD analysis Geometry creation
Mesh generation
Mesh quality examination
Boundary zone assignment
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Int r o du ction to CFD Analysis
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H ow Do e s CFD wo rk ?
FLUENT solv er s a re b as ed on th e finit e vol ume me tho d
Domain is discretized into a finite set of controls volumes General conservation (transport) equation for mass,
momentum, energy, etc:
Partial differential equations are discretized into a systemof algebraic equations.
All algebraic equations are then solved numerically to
render the solution field.
+!
x
xV A A V
dV S dAdAV dV
t J J VJ VJ ..
U nsteady Generationdiffusionconvection
Contin u o u s Do m ain
Disc re tiz ed Do m ain
Illu st r ation of C e llsEquation
Continuity 1
x-mom. u
y-mom. v
Energy h
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CFD Mo de ling Ov er vie w
SolidModeler
Mesh
Generator
Pre-Pr oc e ssing
Solver Settings
Physical Models
Turbulence
Combustion
Radiation
Multiphase Phase Change
Moving Zones
Moving Mesh
Transport Equations
mass species mass fraction
phasic volume fraction
momentum
energy
Equation of State
Supporting Physical Models
Material Properties
Boundary Conditions
Initial Conditions Post- Processing
Equations solved on mesh
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CFD Analysis : Basic St e ps
Pr o b lem Ide ntification an d Pre-Pr oc e ssing
1. Define your modeling goals.
2. Identify the domain you will model.
3. Design and create the grid.
Solv er Ex e c u tion
4. Set up the numerical model.
5. Compute and monitor the solution.
P ost Pr oc e ssing
6. Examine the results.
7. Consider revisions to the model.
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De fin e Yo ur Mo de ling Goals
What results are you looking for, and how will they be used
What are your modeling options?
What physical models will need to be included in your analysis
What simplifying assumptions do you have to make?
What simplifying assumptions do can you make?
Do you require a unique modeling capability?
U DFs
What degree of accuracy is required?
How quickly do you need the results?
Problem Identification and Pre-Processing1. Define your modeling goals.
2. Identify the domain you willmodel.3. Design and create the grid.
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Ide ntify th e Do m ain Yo u Will Mo de l
How will you isolate a piece of the complete physical system?
Where will the computational domain begin and end? Do you have boundary condition information at these boundaries?
Can the boundary condition types accommodate that information?
Can you extend the domain to a point where reasonable data exists
What degree of accuracy is required?
Can it be simplified or approximated as a 2D of axisymmetric problem?
Problem Identification and Pre-Processing1. Define your modeling goals.
2. Identify the domain you willmodel.3. Design and create the grid.
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De sign an d C re at e th e G r id
Can you benefit from Mixsim, Icepak or Airpak
Can you use a quad/hex grid or should you use a tri / tet gridor hybrid grid
How complex is the geometry and flow?
Will you need a non-conformal interface?
What degree of grid resolution is required in each region of the domain?
Is the resolution sufficient for the geometry?
Can you predict regions with high gradients?
Will you use adaption to add resolution?
Do you have sufficient computer memory?
How many cells are required?
How many models will be used?
Problem Identification and Pre-Processing1. Define your modeling goals.
2. Identify the domain you willmodel.3. Design and create the grid.
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Tr i/Te t vs. Q u a d /H e x M e sh e s
For simple geometries, quad/hexmeshes can provide higher qualitysolutions with fewer cells than acomparable tri/tet mesh.
For complex geometries, quad/hexmeshes show no numericaladvantage, and you can save meshingeffort by using a tri/tet mesh
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H ybr id Me sh Exa m pl e
Valv e po r t g r id
Specific regions can be meshedwith different cell types
Both efficiency and accuracy are
enhanced relative to a hexahedralor tetrahedral mesh alone
Tools for hybrid mesh generationare available in GAMBIT andTGrid.
H ybr id me sh fo r an IC Engin e
Te t Me sh
H e x Me sh
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Non -Confo rm al M e sh Exa m pl e
Nonconformal mesh: Mesh in which gridnodes do not match up along an interface
U seful for parts swapping for design study, etc.
Helpful for meshing complexgeometries.
Example:
3D film cooling problem
Coolant is injected into aduct from plenum
Plenum part can be replaced with
new geometry with reduced meshing effort
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S e t Up th e Numer ical Mo de l
Fo r a giv e n p r o b lem, yo u will n eed to :
Select appropriate physical models. Turbulence, combustion, multiphase, etc.
Define material properties
Fluid
Solid Mixture
Prescribe operating conditions.
Prescribe boundary conditions at all boundaryzones.
Provide an initial solution.
Set up solver controls.
Set up convergence monitors.
Solver Execution4. Set up the numericalmodel.5. Compute and monitor the solution.
Sol ving initia lly in 2D wi ll
pro vide va luab l e ex pe r iencewith the m ode ls and sol ve r s etting s for your pro b l em in as hor t am ou nt of time
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Co m p u te th e Sol u tionTh e d isc re tiz ed cons er vation equ ations a re
solv ed iteratively :
A number of iterations are usually requiredto reach a converged solution
Conv er g e nc e is re ach ed wh e n :
Changes in solution variables from oneiteration to the next is negligible.
Residuals provide a mechanism to helpmonitor this trend.
Overall Property conservation is achieved.
Th e acc ur acy of a conv er g ed sol u tion isde p e n de nt u pon :
Appropriateness and accuracy of physicalmodels.
Grid resolution and independence.
Problem setup.
A c onve r ged and g r id-
inde pendent solu ti on on awe ll - pos ed pro b l em wi ll pro vide us e ful enginee r ing r e sul t s
Solver Execution4. Set up the numericalmodel.5. Compute and monitor the solution.
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Exa m in e th e Re s u ltsExa m in e th e re s u lts to re vie w sol u tion an d
e xt r act u s e f u l d ata.
Visualization Tools can be used to answer such questions as:
What is the overall flow pattern?
Is there separation?
Where do shocks, shear layers, etc.form?
Are key flow features being resolved?
Numer ically R e po r ting Tools can be u s ed tocalc u lat e qu antitativ e re s u lts :
Forces and MomentumsAverage heat transfer coefficients
Surface and Volume integrated quantities
Flux Balances.
Post Processing6. Examine the results.7. Consider revisions tothe model.
E xamine r e sul t s t o en sur e prop e r t y c ons e r vati on and c orr ect phys ica l behavi or.H igh r e s id ua ls ma y beatt r ibu tab l e t o o nly a f ew ce llsof poor qu a l it y.
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Consi der Re visions to th e Mo de lAre physical m o de ls app r op r iat e ?
Is flow turbulent?
Is flow unsteady?
Are there compressibility effects?
Are there 3D effects?
Are b o u n d a r y con d itions co rre ct?
Is the computational domain large enough?
Are boundary conditions appropriate?
Are boundary values reasonable?
Is g r id a dequ at e ?
Can grid be adequate to improve results?
Does solution change significantly withadaption, or is the solution grid independent?
Does boundary resolution need to beimproved?
Post Processing6. Examine the results.7. Consider revisions tothe model.
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Op er ating Pre ss ure
Specification of Operating Pressure affects calculation in different ways
for different flow regimes OP is significant for Incompressible flows because it determines
density.
For low mach compressible flows, OP avoids numerical round off error.
Since pressure drop is very small.
are related to dynamic head,
This gives simple relation , so that as
FLU ENT avoids round off error by subtracting operatingpressure (generally a large pressure roughly equal to avg. abspressure in the flow) from the absolute pressure, and using theresult (termed gauge pressure).
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OP is less significant for higher Mach-number compressible flows,since pressure drops are very high. Hence there is no problem of round off errors.
In fact it is common convention to use absolute pressure insuch calculations.
Since FL U ENT always uses gauge pressure, therefore the OPis simply set to zero.