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Improved Quality Prediction of Injection Molded Fiber Reinforced Components by Considering Fiber Orientations Sascha Pazour PART Engineering GmbH [email protected] 0049 2204 30677 26 © PART Engineering GmbH, www.part-gmbh.de

Improved Quality Prediction of Injection Molded Fiber Reinforced Components by Considering Fiber Orientations

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Page 1: Improved Quality Prediction of Injection Molded Fiber Reinforced Components by Considering Fiber Orientations

Improved Quality Prediction of Injection Molded Fiber Reinforced

Components by Considering Fiber Orientations

Sascha Pazour

PART Engineering GmbH

[email protected]

0049 2204 30677 26

© PART Engineering GmbH, www.part-gmbh.de

Page 2: Improved Quality Prediction of Injection Molded Fiber Reinforced Components by Considering Fiber Orientations

Plastics

CAE Services & Software

Technical Simulation Contract Simulation Services

in FEA

CAE Staffing Resident Engineers at

customers‘ sites

CAE Software - Process-Structure-Interaction

- Strength & Fatigue Assessment

Metals

S-Life

Elastomers

Page 3: Improved Quality Prediction of Injection Molded Fiber Reinforced Components by Considering Fiber Orientations

Mechanical Solver Injection Moulding

Solver

- Moldflow

- Cadmould

- Sigma

- Moldex

- Fluent

- Simpoe

- 3D Timon

- Abaqus

- Ansys

- Radioss

- Nastran

- Marc

- FEMFat

- Ncode

Orientations

Pressures

Temperatures

Wall Thicknesses

Residual Stresses

Shrinkage & Warpage

Fig. 2

Page 4: Improved Quality Prediction of Injection Molded Fiber Reinforced Components by Considering Fiber Orientations

material:

PA6+GF30

perpendicular

parallel

Influence of Fiber Orientation onto Material Properties Fig. 3

Page 5: Improved Quality Prediction of Injection Molded Fiber Reinforced Components by Considering Fiber Orientations

Fiber Orientations in Short-Fiber-Reinforced Plastics

S1 Shear layer: Fibers oriented parallel to flow direction

S2 Mid layer: Fibers oriented perpendicular to flow direction

Fig. 4

Flow Direction X

X

Cut View X

Flow Direction

S1

S2

S1

Page 6: Improved Quality Prediction of Injection Molded Fiber Reinforced Components by Considering Fiber Orientations

Isotropic and Orthotropic Material Models

for Multiaxial Loading

s11

s33

s22

t32

t13

t12

t23 t21

t31

Isotropic Material Model

Orthotropic Material Model

Fig. 5

2*

3* 1*

local system

(orthotropic system)

needs 2 material properties: Tensile Modulus E and Poisson ratio

needs 9 material properties:

Tensile modulii the 3 orthotropic axes E1, E2, E3

Shear modulii the 3 orthotropic planes G12, G13, G23

Poisson ratios 12, 13, 23

Further the position of the orthotropic axes (local element coordinate sytem)

with reference to the global coordinate system is needed

1

3 2 global system

(part coordinate system)

Page 7: Improved Quality Prediction of Injection Molded Fiber Reinforced Components by Considering Fiber Orientations

Influence of Weld Lines

weld line

isotropic orthotropic

injection molding simulation simulated fiber directions in

the weld area

radial

displacement

Fig. 6

Page 8: Improved Quality Prediction of Injection Molded Fiber Reinforced Components by Considering Fiber Orientations

Fiber Orientation and Anisotropic Material

Fig. 7

Page 9: Improved Quality Prediction of Injection Molded Fiber Reinforced Components by Considering Fiber Orientations

Orientations and Degree of Orientations

from Injection Molding Simulation

shear layer mid layer

Fig. 8

Page 10: Improved Quality Prediction of Injection Molded Fiber Reinforced Components by Considering Fiber Orientations

Mesh Topology Fig. 9

Converse IM solver mechanical solver

shell (mid-plane/surface) => shell (tria, quad)

shell (mid-plane/surface) => solid (tet, hex)

solid => solid (tet, hex)

unequal meshes

possible

Page 11: Improved Quality Prediction of Injection Molded Fiber Reinforced Components by Considering Fiber Orientations

Material Dialog Fig.10

Page 12: Improved Quality Prediction of Injection Molded Fiber Reinforced Components by Considering Fiber Orientations

0

200

400

600

800

1000

1200

1400

0 1 2 3 4 5 6

Kra

ft [N

]

Verschiebung [mm]

Messung 1

Messung 2

isotrop

orthotrop

Rotary Valve

material: Grivory HTV 3H1

forc

e [N

]

displacement [mm]

test 1

test 2

FEA isotropic

FEA anisotropic

Fig. 11

Page 13: Improved Quality Prediction of Injection Molded Fiber Reinforced Components by Considering Fiber Orientations

Example: Air Intake Manifold

material: Ultramid A3WG6

shear layer mid layer

Fig. 12

Page 14: Improved Quality Prediction of Injection Molded Fiber Reinforced Components by Considering Fiber Orientations

Comparison of Eigenfrequencies and Eigenmodes

for Isotropic and Orthotropic Analysis

0

100

200

300

400

500

600

700

800

900

1000

250,00 270,00 290,00 310,00 330,00 350,00 370,00 390,00

eff

ektive M

asse

[g]

Frequenz [Hz]

x-Richtung - isotrop y-Richtung - isotrop z-Richtung - isotrop

x-Richtung - orthotrop y-Richtung - orthotrop z-Richtung - orthotrop

x-direction-isotropic

x-direction-anisotropic

y-direction-isotropic

y-direction-anisotropic

z-direction-isotropic

z-direction-anisotropic

frequency [Hz]

effe

ctive

ma

ss [kg

]

Fig. 13

Page 15: Improved Quality Prediction of Injection Molded Fiber Reinforced Components by Considering Fiber Orientations

Benefit of Anisotropic lin.-elast. FEA

• determination of initial part stiffnesses Stiffness

• application in the scope of strength assessments Strength

• unrestricted application in the scope of eigenfrequency extraction and response behavior analyses (due to linearization and small displacements/ amplitudes)

Frequency

• Significantly improved estimation of design limits Design

Fig. 14

Page 16: Improved Quality Prediction of Injection Molded Fiber Reinforced Components by Considering Fiber Orientations

Fig. 15

www.part-gmbh.de What´s New?

Page 17: Improved Quality Prediction of Injection Molded Fiber Reinforced Components by Considering Fiber Orientations

consider the real part properties

get better predictions of

strength & deformation

by using data already

available

integrates smoothly into

your day-to-day CAE routines

straigthforward easy-to-use

Fig. 16