IHS

stickshrivelΜηχανική

24 Οκτ 2013 (πριν από 4 χρόνια και 20 μέρες)

104 εμφανίσεις

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

Experience in mathematical optimization

Automatic shape optimisation

parameterized geometry

Wells
-
Tool

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

Optimisation Methods


Directe optimisation


“Response Surface” method


Estimation of an continous approximate function by


Neuronal net


Polynomial approach


Spline


Search for the optimum of the approximate function


IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

Parameter

Qualitätsfunktion

berechnete Werte

Optimierung an der Response Surface

Response Surface Methode

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

1

2

3

assumed

optimum

search direction

cost function

relaxation


Gradient type algorithmus, with search direction


Opjective funktion is locally approximated and the minimum is
calculated along the search direction


EXTREME

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

Self Adaptive Evolution (SAE)


Start with a randomly chosen population


New population is obtained by


Mutation


Crossover


Survival of the fittest


Live time of each individual is exactly 1 generation
(Comma Strategie)



Evolution methode

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

Parallel
Optimisation

simultaneous simulation on different resources

each simulation is run in parallel

Research: Asynchronous, parallel optimisation

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

Parallel Optimisation

Grid Compting

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

Applied Algorithm

randomly chosen

initial parameter sets

CFD

CFD

CFD

CFD

CFD

survival of the fittest

new sets by discrete
operation, e. g. mirror

new sets randomly

with weighting

CFD

CFD

CFD

CFD

grid portal

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

Example Guide vane shape

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

Guide vane geometry

Inlet angle,

Outlet angle,

chamber line angle,

Weighting factor inlet,

Weighting factor outlet,

Overlapping,

Profile a,

Profile b,

Trailing edge thickness

Geometry Parameterisation

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

Automatic block structured mesh


Automatic Grid Generation

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

Simulation

Results:


Flow patterns (e. g pressure distribution)

Overall quantities (e. g. efficiency, losses)

Restrictions (e. g. cavitation)

Typical computational time for one geometry: 1
-
4 h

on a Cluster of HPC

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS






9 free parameters:


-


45 different designs (individuals)


per generation

-


8 generations

-


in total 360 calculations



Guide vane shape

optimized with evolution strategy

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

Convergence

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

Optimised Geometrie

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

Test example: Draft tube cone

Assumption:

Cone length

Optimisation:
Outlet diameter

L

D
in

D
out

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

0.4

0.5

0.6

0.7

0.8

0.9

1

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

2.4

2.6

Draft tube efficiency

D_out/D_in

Test example: Draft tube cone

randomly chosen starting points

Cone length
: 6 D_in

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

0.4

0.5

0.6

0.7

0.8

0.9

1

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

2.4

2.6

Draft tube efficiency

D_out/D_in

Test example: Draft tube cone

survivors of the first generation

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

0.4

0.5

0.6

0.7

0.8

0.9

1

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

2.4

2.6

Draft tube efficiency

D_out/D_in

Test example: Draft tube cone

survivors of the second generation

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

0.4

0.5

0.6

0.7

0.8

0.9

1

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

2.4

2.6

Draft tube efficiency

D_out/D_in

Test example: Draft tube cone

survivors of the third generation

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

0.4

0.5

0.6

0.7

0.8

0.9

1

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

2.4

2.6

Draft tube efficiency

D_out/D_in

Test example: Draft tube cone

computed points

survivors of the seventh generation

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

The draft tube contour can only
be changed slightly.

Optimization of the area
distribution

Draft tube area distribution

Application:
Refurbishment of an existing power plant

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

area distribution


Area distribution represented by B
-
Spline curves


Inlet and outlet kept constant


other cross sections scaled up

Draft tube area distribution

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

Draft tube area distribution

Investigated area distribution during the optimisation

Design point

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

Draft tube area distribution

Design point

Obtained area distribution

original draft tube

maximum efficiency

minimum efficiency

draft tube efficiency increase: 8%

overall efficiency increase: 0.4%

IHS
-
Präsentation, 2008

Ruprecht

University of Stuttgart

Institute of Fluid Mechanics and

Hydraulic Machinery, Germany

IHS

minimum efficiency

Overload

design point

part load

original draft tube

Draft tube area distribution