Fuel Tank Design Optimization in Extrusion Blow...

Fuel Tank Design Optimization in Extrusion Blow Moulding

F. Thibault

RTS 2009

March, 11th 2009

Competitiveness and quality of life of Canadians through research and innovation

• 21 institutes and facilities across Canada

• 4,150 full-time employees

• 1,200 guest workers

NRC Research FacilitiesIRAP Office

Overview:National Research Council

Overview:National Research Council

OverviewExpertise: Simulation of Deformable Materials

Forming processes– Blow moulding, thermoforming, micro-forming

Modelling of deformable structures – Finite elements, geometric modelling, material

deformations

– Coupled with mechanical, chemical, electrical, biological behaviour

Integration and interaction with hardware platforms– Control, imaging and haptics

Industrial Materials Forming

Development of in-house simulation software

with 20 industrial users worldwide

Industrial material forming and characterization lab Industrial material forming and characterization lab Industrial material forming and characterization lab Industrial material forming and characterization lab

Automotive Blow Moulded

Parts

Seat back

WindShield Washerreservoir Fuel tank accessories

Air ducts

Air ducts

Cooling liquidreservoir

Different Types of Automotive

Fuel Tanks

Outlook

• Die Technology Overview for Plastic Fuel Tank (PFT) Manufacturing

• PFT Simulation Capabilities

• Design Optimization– Parison length optimization

– Die geometry optimization

– VWDS optimization

– Barrier layer optimization

• Illustration of some Case Studies

• Concluding Remarks

Parison Programming(Vertical Wall Distribution System-VWDS)

Programmedparisonshowingheavier

wallthickness

for greatestexpansion

area

1

2

3

4

5

6

7

8

% Gap Opening (θθθθ)

Programming Points or Extrusion Time (sec)

1 2 3 4 5 6 7 8

20%

0%

40%

60%

80%

100%

0% open 100% openDie

Mandrel

Illustration of VWDS for PFT

Die Shaping

(Static Flexible Deformable Ring-

SFDR)

• Non-symmetric parts• Avoid mandrel retooling (flexibility)• Geometry constant along extrusion

Adjusting SFDR-Screws

Exit Die Cross Section

Partial Wall Distribution

System (PWDS)

Actuator Movements:Deformable Bushing

Pull (+)

Push (-)

Pull (+)

Push (-)

Illustration of

VWDS-SFDR-PWDS

Technology

IMI Simulation Capabilities

for PFT

• Fluid mechanics inside the die• Solid mechanic outside the die• Phenomenological model for

• Diameter swell• Thickness swell• High Wessenberg number

Extrusion

Parison Inflation

• Multilayer viscoelastic nonlinear deformation using membrane finite elements• K-BKZ material model used for stress-strain deformation curve

6 layers of polymers

Typical Simulation of

PFT Process

• Parison extrusion with VWDS/SFDR/PWDS

• Pinch plates at the top

• Stretching pins at the bottom

• Pinch plates at the bottom

• Pre-blow pressure

• Mold clamping

• High pressure to get final PFT shape

Process Steps

Optimization Formulation

s)constraint(equality,10)(

)sconstraintinequality(NCON1,0)(

)variablesdesign(NDV1,

function)(objective)(

max,min,

NEQUkkh

iiG

tosubject

jXXX

ngmanipulatiby

XFMin

jjj

==

=≤

=≤≤

r

boundsupperX

boundslowerX

→

→

max

min

:SpaceDesign

r

r

BlowDesign Optimization

Scheme

Initial Design Simulate Process

Evaluate

objective function &

constraints

Update

design variables

Stop

Converge?no

yes

Optimization Loop

Constraints

: Design variables vector

: Search direction

: Step length

: iteration number

X

α

S

qq

j

q

j SXX ⋅+=+ α1

The standard line search algorithm is used to update design variables as the following

Updating Design Variables

where α is the optimal step length found along the direction Sq so that

)(min qqj

SXF ⋅+αα

q

BlowDesign Optimization

Flowchart

Parison Length Optimization

Die Shaping Optimization

VWDS Optimization

+PWDS Optimization

SFDR ?

Yes

VWDS ?

Yes

Parison Length

is OK?

No

Stop

No

Yes

No

Die shaping

Die Programming profile

Parison Length Optimization

sconstrainton

tosubject

XXX

variabledesignnextthengmanipulatiby

TargetPLn)(simulatio PLF(X)Min

max,11min,1 <<

−=

Remark:

The simulated parison length takes into account the sag and/or swell

effects

Targeted

parison length

(PL)

)(),( exttTimeExtrusionQFlowrateX =r

Die Shaping Optimization(SFDR)

Extruded Parison

270o205o 235o220o

270o

235o220o205o

Inflated Parison

(Gmin, Gmax)i

Inflation

mandrel

bushing

Average inflated parison thickness

for each die point ( )iT ,pointdie

( )

sconstraintno

tosubject

NDiePjGapGapGap

variablesdesignnextthengmanipulatiby

NDieP

TT

XFMin

jjj

NDieP

i

podieipodie

,1,

)(

max,min,

1

intint,2

=<<

−

==∑

=σ

Die Shaping Optimization

where is the mean of the average inflated parison thicknessintpodieT

Remark:The algorithm manipulates the maximum die gap (mandrel shaping) to get a uniform material distribution on each die point around the inflated parison

Programming ProfileOptimization (VWDS)

Mandrel Opening (%)

Extr

usio

n T

ime (

t)

1

2

3

4

5

6

Q (kg/m3)T (°C)

D

∆L1

∆L2

∆L3

∆L4

∆L5

∆L6

Parison length segment

T1

T2

T3

T4

T5

T6

Inflation

Average programming

point thickness

T1,min

T2,min

T3,min

T4,min

T5,min

T6,min

Minimum programming

point thickness

Manipulate the mandrel opening (%) to target1. A uniform inflated parison thickness (algorithm #1)2. A minimum inflated parison thickness (algorithm #2)taking into account the sag and/or swell during the parison extrusion

Design Objective Function

1

)( 2

arg

−

−=∑

n

TTMin

etti

thicknesspartσ

By manipulating

Gap opening limits

Uniform part thickness

Constant parison length

Subject to constraints

Ti = Ttarget

Plength = PL

θmin < θ < θmax

Parison Programming (text, θ)

Stroke Positions (S1, S2)

Flowrate (Q)

Fix Angle & Prog. Points S1 S2

text, θ

Q

Programming ProfileOptimization (algorithm #1)

Programming ProfileOptimization (algorithm #2)

Design Objective Function

Gap opening limits

Minimum inflated parison thickness (j=1,NProgP)

Constant parison length

∫Ω

Ω= dSTWeightPartMin ρ)(

Subject to constraints

Tj,min > Tmin

Plength = PL

θmin,i < θi < θmax,i

By manipulating

Parison Programming (text, θ)

Stroke Positions (S1, S2)

Flowrate (Q)

Fix Angle & Prog. Points S1 S2

text, θ

Q

Case Study #1 (Jerry Can)

Problem Description:• Objective: Target a uniform part thickness = 3.0 mm

• Design Variables: Gap opening, die gap (Gmax), flowrate (Q),

PWDS stroke motions (S1, S2)

• Material : PP Pro-Fax SV152 (Montell)

• Parison length : 430 mm

• Fix extrusion time : 30 sec

• Number of prog. points: 10

• Initial gap opening : 60%

• Die Geometry : Gmin = 2 mm, Gmax = 10 mm (circular)

• Initial PWDS : S1 = 0.0 (0º), S2 = 0.0 (180º)

• Four Optimizations will be performed:

• VWDS, VWDS+PWDS, VWDS+SFDR, VWDS+SFDR+PWDS

σ T

2.5 mm

9.4 mm

VWDS

0.63

3.02

VWDS+PWDS

2.6 mm

9.7 mm

0.51

3.03

VWDS+SFDR

2.4 mm

12.3 mm

0.45

3.06

VWDS+SFDR+PWDS

2.8 mm

12.0 mm

0.4

3.1

0.5 5.0 mm

Target value

Initial Design

6.8 mm

0.83

3.38

Optimization Results

3.0

• PFT of Vitec (Detroit area)

• Material: HDPE/LDPE

• Parison length: 1405 mm

• Extrusion time: 120 sec

• Minimum PFT thickness: 3.4 mm(before shrinkage)

• Die technology (VWDS, no PWDS)

Case Study #2

(optimization of VWDS)

Objective Function &

Parison Length History

1.02E+04

1.03E+04

1.04E+04

1.05E+04

1.06E+04

1.07E+04

1.08E+04

1.09E+04

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Optimization Iteration [-]

Pari

so

n W

eig

ht

[g]

1.30E+03

1.32E+03

1.34E+03

1.36E+03

1.38E+03

1.40E+03

1.42E+03

1.44E+03

1.46E+03

1.48E+03

1.50E+03

Pari

so

n L

en

gth

[m

m]

Parison Weight

Parison Length

VWDS Optimization

Results

0

10

20

30

40

50

60

70

0 20 40 60 80 100 120

Extrusion Time [s]

Die

Gap

Op

en

ing

[%

]

Initial Design

Iter. #1

Iter. #5

Iter. #10

Iter #15

Final Design

Parison & Inflated Parison

Thickness History

Initial

Design Iter #2 Iter #5 Iter #10 Iter #15 Iter #20 Iter #30

Tmin

3.52

21.99 mm

3.4

15.0 mm

3.4

15.0 mm

Targeting Non-Uniform Inflated

Parison Thickness on Specific Area

(ZONING)

Inflated Parison Thickness = 3.4 mmFitting Component Area = 6.0 mm

Targets:

# Target ID, Prog1 -> Prog2, Die1 -> Die2, Thickness

Target, 1, 1, 5, 1, 17, 3.4

Target, 2, 6, 7, 15, 16, 6.0

Target, 3, 8, 12, 1, 17, 3.4

Thickness Target Definition

for the Case Study

Inflated Parison Thickness


Thick

(mm)

Initial Design Iter #3 Iter #6 Iter #9 Iter #11

VWDS or

Programming Profile


0

20

40

60

80

100

0 20 40 60 80 100 120 140

Extrusion Time (s)

Die

gap

Op

enin

g (

%)

Initial Design

Iter #3

Iter #6

Iter #11

Permeability Analysis Capability

Mathematical Model

Henry’s Solubility Law

pSC ⋅=

Solubility Coefficient

2

2

x

CD

t

C

∂

∂=

∂

∂

Fick’s Law of diffusion

000 =<<= Chxt

sCCxt ==> 00

00 ==> Chxt

Initial Condition

Boundary Condition

Diffusion Coefficient

Fick’s second Law of diffusion

2

2

x

pSD

t

pS

∂

∂⋅=

∂

∂

Initial Condition

000 =<<= phxt

Boundary Condition

sppxt ==> 00

00 ==> phxt

Permeability Coefficient

Adhesive LLDPE

Virgin HDPE

EvOH barrier

Regrind HDPE

Virgin HDPE

h0

C=Cs

C=0 C=0

inside

Parting lineon the part

Contact on the inflated parison Pinch-Off Zone

• If a parting line node is within a distance tolerance to inflated parison node located in the flash, then this node is located in the pinch-off zone

top

bottom

Automatic Pinch-Off

Zone Detection

Barrier Layer Optimization

Barrier Layer Optimization

Case Study

• Material: HDPE virgin & recycled, EvOHLLDPE adhesive




• Hydrocarbon emission constraint: 10 mg/day

• Die Shaping, VWDS, PDWS

(Courtesy of Kautex)

Diffusion Parameters of

PFT Layers

20

50

2.5

0.3

2.5

24.7

Layer

Percentage

[%]

6.8e-2

6.8e-2

1.49e-1

5.0e-4

1.49e-1

6.8e-2

Solubility

Coefficient

[g/g]

5.5e-12Regind HDPE

5.0e-13EvOH Barrier

5.5e-12Virgin HDPE

5.5e-12LLDPE adhesive

8.2e-12LLDPE adhesive

5.5e-12Virgin HDPE

Diffusion

Coefficient

[m2/s]

PFT Layers of

Initial Design

Permeation Results for

the Initial Design

Thickness[mm]

Thickness profile after deflashing

21.7 kg

Daily Emission: = 90.8 mg/day i

NElem

i

i SFlux ⋅∑=1

PermeationFlux

[mg/day/m2]

0.3% EvOH

EBM Process Optimization withDaily Permeation Constraint

[10 mg/day]

Thic

kness [m

m]

19.9 kg

Iteration #1

18.7 kg

Iteration #3

17.6 kg

Iteration #6

2.98

13.16

Initial Design

21.7 kg

Hydro

carb

on E

mis

sio

n

[mg/d

ay/ m

2]

3.30% EvOH10.2 mg/day




3.21

12.0

Adaptative Remeshing during Optimization

Case Study of TI-Automotive

• Material: HDPE



• Initial die opening: 50%


• VWDS (No Die Shaping), PWDS

Thickness Profile HistoryThickness Profile History

Initial design #iter 1 #iter 3 #iter 5

1952 nodes

3840 elements5322 nodes

10580 elements

14445 nodes

28826 elements

34286 nodes

68508 elements

5.1

Thick

(mm)

20.5

3.4

Thick

(mm)

25

7.6 min 17.8 min 53.4 min 130.1 min

Refinement Details at

last Iteration


last Iteration

Front View

Bottom Top


last Iteration


last Iteration

Middle

Front View

Middle

Concluding RemarksConcluding Remarks

• Efficient simulation technology to model and mimic PFT manufacturing

• Adequate optimization tools to get the optimal design

• Recently working on TSBM fuel tank optimization (new technology to reduce fuel emission)

Fuel Tank Design Optimization in Extrusion Blow...

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