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Using FLUENT in Design & Optimization
Devendra Ghate, Amitay Isaacs, K Sudhakar, A G Marathe, P M Mujumdar
Centre for Aerospace Systems Design and Engineering
Department of Aerospace Engineering, IIT Bombay
http://www.casde.iitb.ac.in/
FLUENT CFD Conference 2003 2
Outline
CFD in designProblem statementDuct parametrizationFlow solutionResultsConclusion
FLUENT CFD Conference 2003 3
Using CFD in DesignSimulation Time
CFD is takes huge amounts of time for real life problems Design requires repetitive runs of disciplinary analyses
Integration With optimizer With other disciplinary analyses (e.g. grid generator)
Automation No user interaction should be required for simulation
Gradient Information No commercial CFD solvers provide gradient information Computationally expensive and problematic
( ) to get gradient information for CFD solvers (finite difference, automatic differentiation)
FLUENT CFD Conference 2003 4
Methodology
Problem Specification
Parametrization
New parameters
Geometry Generation
Grid Generation
CFD problem setup
Flow Solution
Optimization usingSurrogate Models
(RSM, DACE)
FLUENT CFD Conference 2003 5
Methodology
Problem Specification
Parametrization
New parameters
Geometry Generation
Grid Generation
CFD problem setup
Flow Solution
Optimization usingSurrogate Models
(RSM, DACE)
FLUENT
FLUENT CFD Conference 2003 6
3-D Duct Design Problem
Entry Exit Location and shape known
Geometry of duct from Entry to Exit ?
Pressure Recovery• Distortion• Swirl
FLUENT CFD Conference 2003 7
Parametrization
Y
X
Z
XDuct
Centerline
A
X
Control / Design Variables
• Ym, Zm
• AL/3, A2L/3Cross Sectional Area
FLUENT CFD Conference 2003 8
Parametrization (contd.)
Y
X
Z
XDuct
Centerline
A
X
Control / Design Variables
• Ym, Zm
• AL/3, A2L/3Cross Sectional Area
FLUENT CFD Conference 2003 10
Grid Generation
Generation of entry and exit sections using GAMBIT
Clustering Parameters
Conversion of file format to CGNS using FLUENT
Mesh file
Generation of structured volume grid using parametrizationGrid parameters
Entry & Exit sections
Conversion of structured grid to unstructured format
Complete grid generation process is automated and does not require human intervention
Complete control over
• Distance of the first cell from the wall
• Clustering
• Number of grid points
FLUENT CFD Conference 2003 11
Turbulence ModelingRelevance: Time per SolutionFollowing aspects of the flow were of interest:
Boundary layer development Flow Separation (if any) Turbulence Development
Literature Survey Doyle Knight, Smith, Harloff, Loeffer
Circular cross-section S-shaped duct
Baldwin-Lomax model (Algebraic model) Computationally inexpensive than more sophisticated models Known to give non-accurate results for boundary layer separation etc.
k- realizable turbulence model Two equation model Study by Devaki Ravi Kumar & Sujata Bandyopadhyay (FLUENT
Inc.)
FLUENT CFD Conference 2003 12
Turbulence Modeling (contd.)
Standard k- model Turbulence Viscosity Ratio
exceeding 1,00,000 in 2/3 cells
Realizable k- model Shih et. al. (1994) Cμ is not assumed to be
constant A formulation suggested
for calculating values of C1 & Cμ
Computationally little more expensive than the standard k- model
Total Pressure profile at the exit section (Standard k- model)
FLUENT CFD Conference 2003 13
Distortion AnalysisDC60 = (PA0 – P60min) /qwhere,
PA0 - average total pressure at the section,
P60min- minimum total pressure in a 600 sector, q - dynamic pressure at the cross section.User Defined Functions (UDF) and scheme files were used to generate this information from the FLUENT case and data file.Iterations may be stopped when the distortion values stabilize at the exit section with reasonable convergence levels.
FLUENT CFD Conference 2003 14
Parallel Execution
Parallel mode of operation in FLUENT16-noded Linux clusterPortable Batch Systems for schedulingBatch mode operation of FLUENT (-g)Scale up depends on grid size
FLUENT CFD Conference 2003 16
Results (contd.)
Mass imbalance: 0.17%Energy imbalance: 0.06%Total pressure drop: 1.42%Various turbulence related quantities of interest at entry and exit sections:
Entry Exit
Turbulent Kinetic Energy
124.24 45.65
Turbulent Viscosity Ratio
5201.54 3288.45
y+ at the cell center of the cells adjacent to boundary throughout the domain is around 18.
FLUENT CFD Conference 2003 17
Slapping
These are huge benefits as compared to the efforts involved.
Methodology Store the solution in case & data files Open the new case (new grid) with the old data file Setup the problem Solution of (0.61 0.31 1 1) duct slapped on (0.1 0.31 0.1 0.1)
3-decade-fall 6-decade-fall
Without slapping 4996 9462
With slapping 1493 6588
Percentage time saving
70% 30%
FLUENT CFD Conference 2003 18
Conclusion
Time for simulation has been reduced to around 20% using parallel computation and slapping.
0 20 40 60 80 100
Time (hrs)
Time per CFD Run
Serial Run
Parallel Run
Slapping
Process of geometry & grid generation has been automated requiring no interactive user input
FLUENT has been customized for easy integration into an optimization cycle
CFD analysis module ready for inclusion in optimization for a real life problem
FLUENT CFD Conference 2003 19
Future Work
Further exploration and improvement of slapping methodologyIdentification and assessment of optimum optimization algorithm
FLUENT CFD Conference 2003 22
Problem Statement
• A diffusing S-shaped duct• Ambient conditions: 11Km altitude• Inlet Boundary Conditions
• Total Pressure: 34500 Pa• Total Temperature: 261.4o K• Hydraulic Diameter: 0.394m• Turbulence Intensity: 5%
• Outlet Boundary Conditions• Static Pressure: 31051 Pa (Calculated for the desired mass flow rate)• Hydraulic Diameter: 0.4702m• Turbulence Intensity: 5%
FLUENT CFD Conference 2003 23
Duct Parameterization Geometry of the duct is derived from the Mean Flow Line (MFL) MFL is the line joining centroids of
cross-sections along the duct Any cross-section along length of the
duct is normal to MFL
Cross-section area is varied parametrically Cross-section shape in merging area is same as the exit section
FLUENT CFD Conference 2003 24
MFL Design Variables - 1
Mean flow line (MFL) is considered as a piecewise cubic curve along the length of the duct between the entry section and merging section
x
y(x), z(x)
0 LmLm/2
y(Lm/2), z(Lm/2) specified
Centry
Cmerger
y1, z1
y2, z2
Lm : x-distance between the entry and merger section
y1, y2, z1, z2 : cubic polynomials for y(x) and z(x)
FLUENT CFD Conference 2003 25
MFL Design Variables - 2• y1(x) = A0 + A1x + A2x2 + A3x3, y2(x) = B0 + B1x + B2x2 + B3x3
• z1(x) = C0 + C1x + C2x2 + C3x3, z2(x) = D0 + D1x + D2x2 + D3x3
• y1(Lm) = y2 (Lm), y1’ (Lm) = y2’ (Lm), y1” (Lm) = y2” (Lm)
• z1(Lm) = z2 (Lm), z1’ (Lm) = z2’ (Lm), z1” (Lm) = z2” (Lm)
• y1’ (Centry) = y2’ (Cmerger) = z1’ (Centry) = z2’ (Cmerger) = 0
• The shape of the MFL is controlled by 2 parameters which control the y and z coordinate of centroid at Lm/2
• y(Lm/2) = y(0) + (y(L) – y(0)) αy 0 < αy < 1
• z(Lm/2) = z(0) + (z(L) – z(0)) αz 0 < αz < 1
FLUENT CFD Conference 2003 26
Area Design Variables – 1
Cross-section area at any station is interpolated from the entry and exit cross-sections
•A(x) = A(0) + (A(Lm) – A(0)) * β(x)
• corresponding points on entry and exit sections are linearly interpolated to obtain the shape of the intermediate sections and scaled appropriately
• Psection = Pentry + (Pexit - Pentry) * β