Optimization of a Highly Stressed Radial Compressor Impeller Optislang

8/11/2019 Optimization of a Highly Stressed Radial Compressor Impeller Optislang

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Main Research Team Computersimulation im Maschinenbau

FachhochschuleDortmund

University ofApplied Sciences and Arts

Wost 2011 Prof. Dr.-Ing. M. Geller

Optimization of a highly stressed

radial compressor impeller

with regard to CFD- and FEM-relevant aspects in

ANSYS Workbench and in optiSLang

Prof. Dr.-Ing. M. GellerB.Eng. A. RybackiDipl.-Ing. M.Eng. Ch. Schemmann


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We turn science into solutions

Presented by

the Main Research Team

Computersimulation imMaschinenbau

partner of


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Optimization in the Main Research Team Computersimulation im Maschinenbau

More than 10 years experience in optimizationof turbo machines

Presentations inter alia in Stuttgart, Bonn, Aachen, ...

Since ~2.5 years use of modern methods foroptimizations

In today s paper:

ANSYS DesignXplorer


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ontents

Use of Turbo Machines

The Model

Optimization

Optimization in DesignXplorerOptimization in optiSLang

Future Works


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The turbo machine is almostalways significantly involvedin the implementation ofseveral energy sources intoelectrical energy.



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Examples of turbo machines

Axial Turbine Multistage Radial Compressor



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Single Stage Radial Compressor(dimensioning, construction, computation: FH Dortmund)

Compressor model of FH Dortmund



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Examples for cases of damage

Source: http://audizine.comSource: http://ssl.gtusers.com







Damaged impeller from the formerarea of activity from Prof. Geller


Examples for cases of damage






ontents


The ModelOptimization


Future Works






The Model

Typical approach in TurboMachinery business areas:

Rotationally symmetrical sectorinstead of a completely360 -geometry

Representation of a sector






The Modeling of the impeller geometry

The CAD-Model und parameterization were

completely performed in the Design Modelerof the ANSYS Workbench.

At first the flow channel was modeled.

The solid geometry is derived from the

fluid geometry.

Lastly the sector of the impeller was generatedwith a complex shaped cutting part.

The Model






The Geometry Parameters

Overall 29(!) geometry parametersdefine the impeller.

The geometry parameters aredifferentiated between main dimensionsand shape parameters.

Herewith we can model almost everyarbitrary impeller geometry.

GeometryParameters

MainDimensions

ShapeParameters

The Model






The rounding radii at the blade roothave a considerable impact on themaximum stresses.

The Model

Examples for the Geometry Variants


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F hh h h l






A larger axial length reduces flow deflection losses.

The Model


F hh h h l


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Large volume flows require at the optimum large blade surfaces.Certainly they produce significantly larger stresses.

The Model


F hh h h l


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ontents


The ModelOptimization


Future Works

F hh h h l


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ANSYS DesignXplorer

Based on an arbitrary

start geometry: Efficiency: 78% Pressure Ratio: ~1.7 max. Stress: 670MPa

Objectives for optimization: Efficiency = Maximum Pressure Ratio = 2.5 max. Stress 500MPa

Based on a pre-optimized start geometry in

regard to CFD-relevant aspects: Efficiency: 89% Pressure Ratio: ~2.5 max. Stress: 800MPa

Objectives for optimization: Efficiency = Maximum Pressure Ratio = 2.5 max. Stress 500MPa

Optimization


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Fachhochschule


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Optimization in DesignXplorer

Objectives for the optimization in the DesignXplorer

Maximize the Efficiency

given Pressure Ratio as goal

Maximum Stress as given constraint

Fachhochschule


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Implicit Approach

CFD & FEMFine-Optimization

CFD & FEMPre-Optimization

CFD & FEMFinal-Optimization

Geometry generationand parameterization in

the Design Modeler

Correlation Matrix

Goal DrivenOptimization

OptimumGeometry

This process in notfeasible in the

DesignXplorer!!!

FEM-Pre-Optimization

FEM-

Final-Optimization

CFD-Pre-Optimization

CFD-Final-Optimization

Serial Approach

We developed a seriallyapproach as an

alternative solution


Fachhochschule


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Serially Approach

FEM-Final-Optimization

CFD-Pre-Optimization

FEM-Pre-Optimization

CFD-Final-Optimization

Parameterswith maximum

sensitivity

FEM-Pre-Opt 1

FEM-Pre-Opt 2

Parameterswith median

sensitivity

Parameterswith minimum

sensitivity

FEM-Pre-Opt 3

ArbitraryStart Geometry

Parameterswith maximum

sensitivity

CFD-

Pre-Opt 1Optimized

Geometry afterFEM-Pre-Opt

CFD-Pre-Opt 2

Parameterswith median

sensitivity

High effort!!!Many manual interventions

were necessary!!!

(FEM-Final- and CFD-Final-Optimizationanalogous)

etc.



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Fachhochschule fO i i i i D i X l


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Start Geometrie

Optimum Geometry

Results

It was possible to avoidall flow separations.


Fachhochschule U i i fO ti i ti i D i X l


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0%

20%40%60%80%

100%

120%140%

Start Geometry Optimum

Pressure Ratio

0%

20%

40%

60%

80%

100%


Derived Efficiency

The optimization was successful:The wanted pressure ratio was reached while simultaneously optimizationof the efficiency.

Results

wanted pressure ratio


Fachhochschule U i it f

O ti i ti i D i X l


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Lessons learned

The coupled optimization of CFD and FEM of complexmodels is not possible.(Limitation of the amount of parameters)

serial alternative solution is necessary

Concerning the computing and working time the seriallyoptimization is very expensive.

Intervene in the running optimization process is notpossible. (low flexibility)

Parallelization is not possible.

The restriction on systematic sampling methods quicklyinduce a high number of designs for a high-quality

sensitivity analysis.



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Fachhochschule University ofOptimization in optiSLang


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DortmundUniversity ofApplied Sciences and Arts


Optimization in optiSLang

Initial situation of the optimization in optiSLang

Starting point for the optimization was a pre-optimized impeller

with regard to CFD-relevant aspect with a high efficiency.

The structural mechanics was excluded in the pre-optimization.

critical stress peaks at the outlet of the impeller



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Objectives for the optimization in optiSLang

Maximize the Efficiency

given Pressure Ratio as goal

Maximum Stress as given constraint

IOW: The goal of this optimization is keeping the goodmechanical flow properties while simultaneouslycompliance with the permissible stress.



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The Setup

CFX was externalparallelized at a cluster



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Dortmundy

Applied Sciences and Arts


Results - Sensitivity Analysis

Input parameters were reduced from 29 to 14!!!




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Dortmundy

Applied Sciences and Arts


Results - Equivalent Stress

Start Geometry

It was possible to avoid critical

stress peaks at the outlet of theimpeller.


Optimum Geometry



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Dortmund Applied Sciences and Arts


Results - Fluid Flow

Start Geometry

Optimum GeometryFlow properties are almost the same

Reduction of stress has no negative

influence on the fluid flow!




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Results

0%

20%

40%

60%

80%

100%


Maximum Stress

0%

20%

40%

60%

80%

100%


Derived Efficiency

Permissible Maximum

almost keep constant

The optimization was successful:The stress was reduced by more than 40% while simultaneously keepingthe efficiency!!!


Fachhochschule University of



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Lessons learned

The coupled optimization of CFD and FEM is possible.The amount of parameters is unlimited.

Intervention in the running optimization process is

possible. (high flexibility) The possibility of parallelization leads to a

significant saving in time.(Independent of the used software!)

In contrast to other sampling methods, Latin Hypercubesampling enables a sensitivity analysis with little effort andhigh-quality results.


Fachhochschule University of


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Conclusion 1/2

DesignXplorer

The amount of parameters is limited

implicit optimization of complexmodels is not possible

serial optimization is veryexpensive

Intervention in the runningoptimization process is not possible

low flexibility

optiSLang

The amount of parameters is unlimited

implicit optimization of complexmodels is possible

serial optimization is notnecessary

Intervention in the running optimizationprocess is possible

high flexibility

Fachhochschule University ofl d d


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Conclusion 2/2

DesignXplorer

Restriction on systematic samplingmethods

The parallelization of the process isnot possible

Objectives of the optimizationare reached(overall 1300 samples were necessary)

optiSLang

Stochastic sampling methods exist(especially the Latin Hypercubesampling)

It is possible to parallelize theworkflow

Objectives of the optimizationare reached(overall 560 samples were necessary)

Fachhochschuled

University ofA li d S i d A


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ontents


The Model

Optimization

Optimization in DesignXplorer Optimization in optiSLang

Future Works

FachhochschuleD d

University ofA li d S i d A t

Future Works


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Consideration of machine performance(so-called Off - Design)

Inclusion of additional machine components for thesimulations

The objective: Development of a meta model for acomplete turbo compressor

IOW: The Cordier-diagram is to be completed by a meta

model of a radial turbo machine.

Planned activities for the next 4 years

Optimization of a Highly Stressed Radial Compressor Impeller Optislang

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