Fluid-based Topology Optimization of an EGR...

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1 3DS.COM © Dassault Systèmes | Confidential Information | 4/7/2014 | ref.: 3DS_Document_2013 3DS.COM © Dassault Systèmes | Confidential Information | 4/7/2014 | ref.: 3DS_Document_2013 Fluid-based Topology Optimization of an EGR Flowsplitter

Transcript of Fluid-based Topology Optimization of an EGR...

Page 1: Fluid-based Topology Optimization of an EGR Flowsplittermdx2.plm.automation.siemens.com/sites/default/files/Presentation/SGC... · Tosca Fluid design Morphed design Total pressure

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Fluid-based Topology

Optimization of an

EGR Flowsplitter

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1 Problem Description

2 Method Description

3 Optimization Setup

4 Optimization Results

5 STAR-CCM+ Adjoint Solver

Overview

6 Summary

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Objective

Consideration of massflow balancing

+ reduction of total pressure loss

Topology optimizer is used to consider

the named objectives starting from the

available design space

Constraint: Obtained geometry may

no violate the design space

boundaries

Flowsplitter geometry

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Both groups have their strengths → The right method depends on the given optimization task

Optimization methods

Non-Parametric

Methods

Parametric

Methods

Combination of

both Groups

Sizing &

par. Shape

DOE &

RSM Robustness

Reliability

Geometric

Parameter

MDO

Structural

Topology

Structural

Shape

Bead

Fluid

Topology

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Tosca Products inside of 3DEXPERIENCE platform

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Topology optimization for CFD problems (1) Optimization problem is based on the

(meshed) available design space

initi

al d

esig

n

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Topology optimization for CFD problems (2) Optimization problem is based on the

(meshed) available design space

Geometric variation is achieved by

sedimenting individual cells

initi

al d

esig

n po

ssib

le v

aria

nts

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Topology optimization for CFD problems (3) Optimization problem is based on the

(meshed) available design space

Geometric variation is achieved by

sedimenting individual cells

An individual design proposal can be

derived based on the collectivity of all free

(= non-sedimented) cells

Optimization represents a co-simulation.

New design available after 1 single CFD

run

initi

al d

esig

n po

ssib

le v

aria

nts

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Tosca Fluid – Convergence behaviour

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Tosca Fluid setup

Optimization Setup

Co-simulation with STAR-CCM+ V 8.06.005 +

TOSCA Fluid 2.3

Defined iteration number: 25000

Optimility criteria with backflow tolerance: 0.5

Simulation time: 24.0 hrs with 2CPU

Result Extraction

Sedimentation + Unsedimented

Smoothing of the extracted geometry Designspace geometry

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Tosca Fluid „raw“-result Obtained geometry after usage of STAR-CCM+ Surface Wrapper

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Tosca Fluid „raw“-result - Streamlines Results

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Basedesign - Streamlines Results

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Comparison of outlet velocity field

Tosca Fluid design Basedesign

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Comparison basedesign vs. Tosca Fluid design Tosca Fluid result = blue geometry

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Comparison basedesign vs. Tosca Fluid design Total pressure loss + massflow split ratio + uniformity

Basedesign Tosca Fluid

Result

Total pressure

loss

1820 Pa 610 Pa

Split ratio 45.9 : 54.1 49.1 : 50.9

Uniformity 0.832 : 0.841 0.946 : 0.940

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Redesign with CAD tool

Designspace

Smoothed TOSCA Fluid result

CAD-based Redesign

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Redesign workflow

1. Wrapped TOSCA result

4. Automatic Surface

2. Delete needless features

3. Fill hole + smooth

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Tosca Fluid „raw“-result - Streamlines Results

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Redesign - Streamlines Results

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Comparison of outlet velocity field

Tosca Fluid design Basedesign

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Comparison basedesign vs. Tosca Fluid design Total pressure loss + massflow split ratio + uniformity

Basedesign Tosca Fluid

Result

Total pressure

loss

1820 Pa 541 Pa

Split ratio 45.9 : 54.1 48.6 : 51.4

Uniformity 0.832 : 0.841 0.931 : 0.932

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Further improvement with STAR-CCM+ sensitivities

• Geometrie: Redesigned Tosca Fluid result

• Primal solution + ajoint flow analysis with coupled solver • Coupled solver: CFL = 200, Grid sequencing and Expert Driver

• Objective function: Pressure drop

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Pressure drop based sensitivities

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Subdivision of surface + morphing • Subdivision of surface into

• Two surfaces modified by morpher

• Remaining part, that will not be changed

• Definition of two lines with the design

points

• Calculation of the design points‘

displacements on the basis of the mesh

sensitivities

• Mesh deformation based on the mesh

sensitivities

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Sensitivity based morphing

Original surface Morphed surface

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Original surface

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Morphed surface

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Loss behaviour of morphed Tosca Fluid result

Tosca Fluid

Result

Morphed

Geometry

Total pressure

loss

541 Pa 521 Pa

0

200

400

600

800

1000

1200

1400

1600

1800

2000

Basedesign Tosca Fluid design Morphed design

Basedesign

Tosca Fluid design

Morphed design

Total pressure loss (Pa)

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Summary Objective: Balanced mass flow at the 2 outlets and reduction of total pressure

loss

TOSCA Fluid optimization based on available design space (24 hrs.)

Simulation results of design proposal reveal significant reduction of total

pressure loss + improvement of flow balancing

Final redesign shows a nearly balanced flow distribution + significant total

pressure loss reduction + increased uniformity

With the STAR-CCM+ adjoint solver, a further reduction (-4%) of the total

pressure loss can be achieved by a sensitivity based morphing

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CFD setup Topology-Optimization

Solver: STAR-CCM+ 8.06.005

Physics:

Incompressible

Steady

k-ε turbulence, All y+

Boundary conditions:

Inlet: Massflow inlet

Outlet: Flow-Split Outlet

Verification

Solver: STAR-CCM+ 8.06.005

Physics:

Incompressible

Steady

k-ε turbulence, All y+

Boundary conditions:

Inlet: Massflow inlet

Outlet: Pressure outlet