automatic shape optimisation in hydraulic machinery using...
TRANSCRIPT
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 1 | 27
Automatic shape optimisation in hydraulic
machinery using OpenFOAM®
5th OpenFOAM® Workshop, 21-24 June 2010, Gothenburg
Jakob Simader
Andreas Ruopp
Ralf Eisinger
Albert Ruprecht
Institut of Fluid Mechanics and Hydraulic Machinery
Universität Stuttgart
www.ihs.uni-stuttgart.de
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg 2 | 25
Contents
1. Motivation
2. Workflow:
1. Parameter check
2. Grid generation and Grid conversion
3. CFD and simulated boundaries
4. convergence check and evaluation
3. Optimisation results
4. Conclusions and outlook
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Motivation
• Automatic shape optimisation
reducing calculation time
• Robust calculation shemes
• Low costs
• Low manpower
• Multi design criterias (part load,
BEP, overload)
• Multi parameter setup
3 | 25
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Sequential workflow
Perl inte
rface
Optimiser
Parameter check
CFD simulation
Objective
function
optimised design
“Setup” configuration
design
parameters
Convergence check
Sequential workflow
Grid generation
Grid conversion
4 | 25
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Advantages:
• Massive parallel cluster nodes
available
• Fast design studies possible
• Calculation of many designs at the
same time
• No license costs using
OpenFOAM®
• Available node number on cluster
is the only limitation
Parameter check
Grid generation
Grid conversion
CFD simulation
Convergence check
Level 1
Level 2
Parallel workflow
Multilevel parallel run on cluster nodes
5 | 25
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Optimisation:
• Genetic algorithm (recombination)
• Simplex algorithm
• Stochastic algorithm
CFD and grid:
• OpenFOAM®
• Grid size between 80.000 and 100.000 nodes
• SST model
Used quality function:
• pressure recovery factor
Optimisation and CFD
2
in
inout
v
pp2c
p
6 | 25
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
First check
Second check
Parameter check
2 checks:
• Limited depth
• No intersection of cross sections:
– Determinate of the four bounding
vectors of each tube segment
must have same sign
Parameter check
)dc(
)cb()ba(
detsign
detsigndetsign
a
b
c
d
7 | 25
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Grid generation
Definition of cross sections
• Width
• Height
• Radius
Grid generation
Grid conversion
Width
Height
Radius
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Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Grid generation
Definition of position of cross sections
• Position of middle point of cut (x,y)
• Angle of normal vector
6 parameters for one cut
In total 48 parameters for 8
cross sections
Grid generator build for in house
CFD-code
converter needed for OpenFOAM®
data files
Grid generation
Grid conversion
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Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Inlet velocities
Draft tube flow high sensitive to
inlet flow field
CFD simulation
• Measured velocity profiles for francis turbine:
– part load
– BEP
– full load
• One run for uniform velocity distribution (c = 6 m/s) without any circumferential component
10 | 25
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Convergence check
Criteria:
• Number of max. Iterations
• cp(i = max) 1
• cp(i) cp(i+1)
• ĉp cp(i = max)
check for pressure quantities
therefore Runtime output of:
- Abs. mass flow ave. of p
- Abs. mass flow ave. of ptot
Ensuring a good convergence behaviour
Convergence check
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Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Optimisation setup
• 48 Parameter setup
• Parallel setup with up to 30 individuals
• CFD-Solver OpenFOAM®
• Calculation time approximately 24 hours
• Single design criteria:
– uniform velocity
– Part load, BEP and over load (8 segments)
– Detailed elbow discretisation (12 segments, but still 48 Parameter)
• Multi design criteria:
– Averaged cp of part load, optimum and over load (1/3 each)
– Weighted cp of part load, optimum and overload
(part load: 30%, optimum: 50%, over load: 20%
12 | 25
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Optimisation setup
• 48 Parameter setup
• Parallel setup with up to 30 individuals
• CFD-Solver OpenFOAM®
• Calculation time approximately 24 hours
• Single design criteria:
– uniform velocity
– Part load, BEP and over load (8 segments)
– Detailed elbow discretisation (12 segments, but still 48 Parameter)
• Multi design criteria:
– Averaged cp of part load, optimum and over load (1/3 each)
– Weighted cp of part load, optimum and overload
(part load: 30%, optimum: 50%, over load: 20%
13 | 25
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Single criteria results: uniform velocity
cp = 0.781
Optimised geometry:
• Area distribution fits common conventions
• smooth tube geometry, except bottom shape
→ detailed view of bottom shape
14 | 25
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Single criteria results: uniform velocity
cp = 0.736
Hand smoothed geometry:
• Smaller pressure recovery
• The contraction after the elbow has positive
effect on the secondary flow phenomena
15 | 25
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Single criteria results: uniform velocity
Cutting plane
Secondary flow fills
up separated region
16 | 25
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Single criteria results: optimum
cp = 0. 870
Optimised geometry:
• Similar shape to the one with uniform velocity
• Also: smooth tube geometry, except bottom
shape
17 | 25
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Single criteria results: optimum
• Evolution of cp along optimisation run
18 | 25
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Single criteria results: optimum detailed elbow
cp = 0. 892
Optimised geometry:
• smooth tube geometry, except bottom shape
→ “doing the right thing might be a bit wrong,
better than the wrong thing right”
19 | 25
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Single criteria results: optimum detailed elbow
20 | 25
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Single criteria results: comparison
cp (over load) = 0.757
cp (optimum) = 0.870
cp (part load) = 0.300
Optimised geometries:
• Very smooth shape for part load conditions
• Different shape for different inlet flow
→ optimising an averaged pressure recovery
cp (over load) = 0.757
cp (optimum) = 0.870
cp (part load) = 0.300
21 | 25
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Optimisation setup
• 48 Parameter setup
• Parallel setup with up to 30 individuals
• CFD-Solver OpenFOAM®
• Calculation time approximately 24 hours
• Single design criteria:
– uniform velocity
– Part load, BEP and over load (8 segments)
– Detailed elbow discretisation (12 segments, but still 48 Parameter)
• Multi design criteria:
– Averaged cp of part load, optimum and over load (1/3 each)
– Weighted cp of part load, optimum and overload
(part load: 30%, optimum: 50%, over load: 20%
22 | 25
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
weightedaveraged
cp (averaged) = 0.607
cp (over load) = 0.730
cp (optimum) = 0.850
cp (part load) = 0.240
cp (weighted) = 0.696
cp (over load) = 0.735
cp (optimum) = 0.855
cp (part load) = 0.241
23 | 25
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Optimisation effort summary
Single Weighted
Ttotal (<24 h) (<24h)
No.indiv. 2700 1902
No.of died indiv. 871 510
No.of calc. Indiv. 1829 1392
No.of best Indiv. 233 112
No.of nodes per Indiv 1 1
No.of cpu„s per node 4 4
• All runs on 24 nodes on xeon cluster / 2xQuadcore 2.8Ghz
• Time consumption not tuned yet
24 | 25
Universität Stuttgart
Institute of Fluid Mechanics andHydraulic Machinery
23.06.2010 5th OpenFOAM® Workshop, 21-25 June 2010, Gothenburg
Conclusions
• Introduced optimisation scheme is applicable for high numbers
of parameters
• Fast calculation time due to parallel setup
• Multi design criteria optimisation
Outlook• „Multi-generation‟ optimiser
• Faster parallel „perl‟ algorithm to reduce calculation time
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