nn

1. Process Simulation
of Composites
Dr. Roland Hinterhölzl

2. Process Simulation – Why?
From hand lay up to (partly) automated serial production
 Automation
 Shorter cycle times
 Process reliability
 Short design and development time
Aviation industry
approx. 50% of the structure are made out of
composite: fuselage, frames, stringers, skins,…
 High volume, bigger parts
 Need for process optimization, for automation
Automotive industry
Serial production with very high volume, short cycle
time, robust processes
new developments and optimization
of manufacturing processes
[BMW]
[Airbus]
15.5.2014 Process Simulation of Composites 2

3. Manufacturing in Aerospace and Automotive Industry
Aerospace
Hours, Days
Automotive
Seconds, Minute(s)
[BMW]
[FACC]
15.5.2014 Process Simulation of Composites 3

4. • Motivation
• Introduction of LCC
• Forming Simulation
• Draping Simulation
• Automated Fiber Placement (AFP) Process Simulation
• Braiding Process Simulation
• Simulation of Liquid Composite Moulding (LCM) processes
• Determination of Process Induced Deformations
(PID) & Curing Simulation
• Simulation Platform
• Conclusion - Outlook
Overview
15.5.2014 Process Simulation of Composites 4

5. • Founded in Mai 2009 financially supported by
the SGL Carbon Group
• Professor Dr.-Ing. Klaus Drechsler
• ~60 Researchers
• 1 Team Assistant
• 5 Technical Employees
• 2 Office locations in Garching
• 3 lab locations in Garching and Ottobrunn
Institute for Carbon Composites
15.5.2014 Process Simulation of Composites 5

6. Research Groups
Process Technology
for Fibers + Textiles
Automated Fiber Placement
Braiding
Tailored Textiles
Simulation
Preform + Flow Process
Simulation
Compaction, Curing and
Deformation
Material Modeling and Structural
Analysis
Process Technology
for Matrix Materials
Hybrid Materials +Structures
Tooling Systems
Production Systems
Material Behavior
and Testing
Composite Testing Lab
Test Method Development
High Strain Rate Behavior
15.5.2014 Process Simulation of Composites 6

7. semi-finished part
preforming (here: draping)
curing
matrix-injection
component
Simulation of composites
Semi-finished part structure:
micro-/mesomechanics
FE draping simulation
LCM simulation:
flow front
Structural component
simulation
Curing- and distortion
simulation
[FACC AG]
15.5.2014 Process Simulation of Composites 7

8. Preform Process Simulation
15.5.2014 Process Simulation of Composites Kap.-8

9. • Motivation for Process Simulation:
• Analyze the influence of process parameters on produced preforms
 increase knowledge of the process
• Optimization of the process and of produced geometry
• Generate input for further analysis (LCM, Curing/PID, Material Modeling)
• Main research activities
• Draping Simulation
• Automated Fiber Placement
• Braiding Process Simulation
Overview
15.5.2014 Process Simulation of Composites 9

10. Draping Process Simulation
15.5.2014 Process Simulation of Composites Kap.-10

11. • Process development / optimization
• Geometry and alignment of the flat preform
• Drapeability (feasibility study)
• Prediction of draping defects
• …
• Part design (design to process)
• Prediction of fiber alignment
• Prediction of fiber volume fraction
• …
• Embedding in process simulation platform:
• LCM simulation
• Curing and PID simulation
• Structural simulation
Goals of Draping Simulation
lay-up of the preform
tool preform
Forming (draping)
in required shape
Airbus A380 – Pressure Bulkhead
BMW i3 – fully automated draping process [BMW]
15.5.2014 Process Simulation of Composites 11

12. • Textiles
• woven, Non-Crimp Fabrics (NCF), UD, etc.
• dry or pre-impregnated
• Deformation modes
• Defects
Requirements for Draping Simulation
plain weave twill weave NCF
Shear Intra-ply Motion
Wrinkling / Folds
Inter-ply Motion
Elongation
Bending
Loops Gaps / Voids Fiber Pull-Out Damage of Stitching
15.5.2014 Process Simulation of Composites 12

13. Finite Element Approach
•modeling of the preform on ply-level with shell elements
•simulation of the draping process and the tools
•consideration of forces, friction, velocities, etc.
•prediction of deformation modes and defects in the preforms
Kinematic Approach
•pin-joint method [Mack 1950]
•purely geometrical approach
•computation of the fiber direction
•direct cut geometry generation
Numerical Approaches for Draping Simulation
level
of
detail
L1
L2
P
shear
bending
elongation
15.5.2014 Process Simulation of Composites 13

14. Kinematic Approach
+ fast & easy to use
+ many software available
+ good interface to structural analysis
- no material behavior
- no process influence
- poor results for complex shapes
Comparison of the Different Approaches
Finite Element Approach
+ accurate results even for complex shapes
+ accounts for material and process influence
+ prediction of draping defects possible
(wrinkles, gaps, etc.)
- higher computational effort
- material testing required
Catia CPD
(Kinematic Simulation)
Experiment PAM-FORM
(FE Simulation)
15.5.2014 Process Simulation of Composites 14

15. Meso-FE Approach
•modeling of the preform on yarn-level with 2D/3D elements
•simulation of Unit Cells deformations
•consideration of friction between yarns, weaving structure,…
•prediction of deformation modes and behavior of units cells
•Not yet suitable for forming simulation (computational cost)
on part scale
Finite Element Approaches for Draping Simulation
Macro-FE Approach
•modeling of the preform on ply-level with shell elements
•simulation of the draping process and the tools
•consideration of forces, friction, velocities, etc.
•prediction of deformation modes and defects in the preforms
shear
bending
elongation
[Voith]
15.5.2014 Process Simulation of Composites 15

16. Simulation Procedure
Validation
Process
Simulation
Parameter
Determination
Material characterization (simulation of the material
behavior)
•Picture Frame Test
•…
Validation on test geometry
•Hemisphere
•Double Dome
•…
Process simulation (design and optimization)
•Diaphragm draping
•Drape forming
•Hand lay-up
•…
Saertex
ECD
15.5.2014 Process Simulation of Composites 16

17. Picture Frame Test
Friction Test
Cantilever Test
Tensile Test
Bias Extension Test
Material Characterization Devices at LCC
15.5.2014 Process Simulation of Composites 17

18. Material card has to be validated before applying the simulation on actual processes
1. Set up of validation process
2. Simulation of validation process
3. Measurement method to compare simulation and test results
Validation
Validation Process (INSA Lyon) Simulation Measurement
15.5.2014 Process Simulation of Composites 18

19. Example:
FE Simulation of Diaphragm Process
15.5.2014 Process Simulation of Composites Kap.-19

20. Example – Simulation of Single Diaphragm Process
Principle:
Draping of a textile with a silicone membrane (diaphragm)
Applying a vacuum
between tool and
membrane
Thermal binder
activation
Demoulding
Placing the fabric over
the tool
Lowering the edges of
the membrane
[AHD]
Membrane Textile
Tool
Table
15.5.2014 Process Simulation of Composites 20

21. Simulation of the Diaphragm Process
Modeling
– Macro-scale simulation with PAM-Form (ESI Group)
– Material 140 – „biphase shell element material with thermo-
visco-elastic matrix and elastic fibers“
Setup
– Draping of a biaxial NCF over a generic helicopter frame
– Modeling of membrane, fabric, tool and table
– Same sequence as in experiment
Components of MAT 140 (ESI)
initial model
lowering edges
applying vacuum
15.5.2014 Process Simulation of Composites 21

22. Characteristics of the Diaphragm Process
• Relative movement between membrane and textile
--> Results in high friction forces
• Anisotropic friction between membrane and textile
--> Orthotropic friction coefficient needs to be defined
x-displacement y-displacement
Fiber
dirc1
Fiber
dirc2
Fiber
dirc2
Fiber
dirc1
high friction
low friction
15.5.2014 Process Simulation of Composites 22

23. Simulation Results for Single Ply Draping
+/-45 NCF
-/+45 NCF
Simulation
Experiment
(Eurocopter DE)
15.5.2014 Process Simulation of Composites 23

24. Example:
FE Simulation of locally stitched NCF Forming
15.5.2014 Process Simulation of Composites 24

25. NCF preform stacks are locally stitched together for better handling
Stitching can influence the draping result
Influence of the local stitching needs to be investigated
Local Stitching
Sewing of Preform Stack
Lay-up on Tool
Draping of Stitched Preform Stack
Final Part: Pitch Horn
15.5.2014 Process Simulation of Composites 25

26. Purpose of test
• Investigation of initial state:
pretensed stitch <> slack in stitch
• Influence of the stitching on the textile
• Stress-Strain behavior of the textile
in the stitching vicinity
Single-Lap Shear Test
Test Setup of Lap Shear Test
Lap Shear Test Setup
Tensile Force applied on Lap Shear Test
Local stitching
Clamping areas
15.5.2014 Process Simulation of Composites 26

27. • Only normal stress are applied on PLINKS
• Definition of a Load-Displacement curve for PLINKS elements
Modeling the Stress-Strain behavior of the Stitching
Phase I:
Slack phase -> Lap Shear Test
Phase II:
Fibers deformation -> Lap Shear Test
Phase III:
Stitching thread elongation -> Bias Extension Test
Fmax:
Maximum bearable force -> Lap Shear Test
Load-Displacement Curve for PLINKS elements
III
II
I
Fmax
15.5.2014 Process Simulation of Composites 27

28. Simulation of double diaphragm forming process
Stitching shape
Cut-out line
Overview of the simulation model
Stitching and cut-out lines
• Comparison on a real forming process : generic double curved helicopter frame
• FE meshing automatically created from CAD data
15.5.2014 Process Simulation of Composites 28

29. Comparison
Region a
Region b
Region c
Margossian et al, Comp. Part A, 2014
Layup Region
Average angle
difference
Standard deviation
[0/90 // -/+45]
a 1,89° 1,07
b 4,7° 5,28
c 13,15° 6,85
15.5.2014 Process Simulation of Composites 29

30. Automated Fiber Placement (AFP) Process Simulation
15.5.2014 Process Simulation of Composites Kap.-30

31. Overview – Simulation of the AFP – Process
Placement – scenario
Therm. and mech. material
models
Simulation Model
Validation
[LCC]
15.5.2014 Process Simulation of Composites 31

32. Research Activities at the LCC
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
ε
[Δl
/
l]
Zeit [s]
1D – Simulation:
• Calculation of the time-dependent
mech. compaction behaviour
• Simulation of the transient heat
transfer
2D – Simulation:
• Prediction of the mech. and therm. behaviour
of the process
• Simulation of bridging of the tape
• Modeling of tack
3D – Simulation:
• Mech. placement on complex geometry
possible
• Prediction of the complete thermal history
of the placement process
15.5.2014 Process Simulation of Composites 32

33. • Gap- / Overlap detection
• Compaction / Debulking
• Bridging
• Temperature distribution
 Define reliable
process window
AFP – Process Simulation: Example
Fig. 1: Gap in Simulation
Fig. 4: Surface temperature distribution
Fig. 2: Compaction behaviour of a Slit-Tape
Fig. 3: Sim. Bridging
15.5.2014 Process Simulation of Composites 33

34. Braiding Process Simulation
15.5.2014 Process Simulation of Composites Kap.-34

35. • Goals of braiding process simulation
• Process parameters have a strong influence on
braided structure
• Mandrel shape defines contour of structure
• Modeling the real manufacturing process using
an explicit FE-Solver (e.g. Abaqus/Explicit,
PAM-Crash) to analyze correlation between
process parameters and braided structure
• Rovings are represented by truss- or beam-
elements
• Consideration of friction between
• roving-roving
• rovings-guide ring
• rovings-mandrel
Braiding Process Simulation
regular/ full triaxial
diamond/ half
15.5.2014 Process Simulation of Composites 35

36. Simulation of Liquid Composite Moulding (LCM)
processes
15.5.2014 Process Simulation of Composites Kap.-36

37. Goals
• Prediction of process parameters
• Tool pressure
• Flow front velocity
• Fill time
• Prediction of defects (dry spots, pores)
• Cure kinetics / Heat transport
• Optimization of injection schemes
• Tool design
• Design of robust processes
Challenges
• Material characterization
• Preform
• Resin
• Capturing influences of preceding
process steps (such as textile handling, preforming)
Motivation
Fig.1: Sportscar Monocoque
Fig.2: Filling simulation (flow front plot) of a Sportscar Monocoque
15.5.2014 Process Simulation of Composites 37

38. • Flow processes in porous media
can be described by the Navier-Stokes equation
𝜌
𝜕𝑣
𝜕𝑡
= −𝛻𝑃 + 𝛻 ∙ 𝑇 + 𝑓
• By homogenization of the media (e.g. by volume averaging)
and introducing some assumptions
the flow can be described by Darcy‘s law
𝑣 =
𝐾
𝜇
𝛻𝑃 − 𝜌𝑔 ≈
𝐾
𝜇
𝛻𝑃
• Darcy‘s law relates the flow front velocity 𝑣
to the applied pressure gradient 𝛻𝑃
with the proportionality constants permeability 𝐾
and viscosity 𝜇.
• Permeabiliy is a material parameter of the fiber preform
• Material
• Layup
• Fiber orientation
• Compaction state
Physics of LCM Processes
Fig.1: Illustration of flow fronts (Real vs. Darcy) within an textile preform
Tab.1: Summary of assumptions for validity of Darcy’s law
• Newtonian Fluid
• Constant Viscosity
• Homogeneous, Inelastic Porous Medium
• Neglecting of Gravity and Capillary Forces
• Low Flow Velocity (𝑅𝑒 < 1)
• Saturated Flow
• Neglecting Intra Yarn Flow
15.5.2014 Process Simulation of Composites 38

39. 𝐾∗
=
𝐾11 0 0
0 𝐾22 0
0 0 𝐾33
(lat.: permeare = ‚to pass‘)
Description
In the 3D case the permeability can be noted as a 2nd order tensor.
The tensor can be diagonalized with a rotation
of the global coordinate system
to a coordinate system spanned
by the major permeabilities (cf. Eq.1).
Determination
• Experimental
• 1D-flow method
• Radial-flow method (2D)
• 3D-flow method
• Numerical (Multi-scale approach)
• CFD-calculation on meso-level
based on representative volume elements (RVE)
• Abstraction of the results to the
macro level as permeability tensor
Permeability Testing for LCM Processes
Fig.3: Off-plane test setup
Fig.2: In-plane test setup
Fig.1: 3D permeability tensor
ln-Plane components /
2D tensor
Off-Plane component/
through thickness perm.
15.5.2014 Process Simulation of Composites 39

40. Numerical Method - Overview
„Grey Box“
Software Tool
(Matlab)
RTM Process Simulation
(PAM-RTM)
Fabric Scan
Info
Material Card
Draping Simulation
Process Parameter
CAD
• Image Analysis
• Textile Modeling
• Permeability Calculation
• Material Data
Fig.1: Fabric Scan Fig.2: Image Analysis Fig.3: Textile Model [WiseTex, KU Leuven]
15.5.2014 Process Simulation of Composites 40

41. Determination of Process Induced Deformations
(PID) & Curing Simulation
15.5.2014 Process Simulation of Composites Kap.-41

42. • Geometrical deviations on stiff structures result in
 Additional rework effort and / or high mounting forces required,
 Expensive iterative tooling adaption.
Motivation: Dimensional Control on Stiff Structures
Picture: DLR
Deformed frame after curing
Magnification factor: 30
Deformed frame section
Magnification factor: 30
15.5.2014 Process Simulation of Composites 42

43. • Primary:
• Determination of process induced deformations (dimensional accuracy)
• Evaluation of the effects of residual stress (dimensioning)
• Secondary:
• process optimization (cycle time)
• process control (interaction between parallel simulation of physical curing process)
Curing simulation - goals
Shrinkage
Spring-In / Spring -
Back
Warpage
PID
Fernlund et al, 2003
Svanberg, 2002 Twigg, 2001
15.5.2014 Process Simulation of Composites 43

44. Analytical:
Estimation of
deformation for
simple
geometries
Experimental:
Iterative
optimization of final
part shape
Phenomenological:
Summarization of
different
mechanisms with
one actuating
variable (enhanced
CTE)
Curing simulation:
Simulation of all
relevant
mechanisms (e.g.
reaction kinetics,
modulus
development,…)
Methodologies for determination of process induced
deformations (PID)
PID Quantification (Dimensional Control)
Evaluation of Residual
Stresses, Optimization of
Process Control
Increasing level
of detail and
modeling effort
15.5.2014 Process Simulation of Composites 44

45. Simplified Approaches for PID Determination
Utilization of simplified approaches for strain anisotropy
chem
therm
eq m
m
m 

 

Cure
Fig. 3: Verification of αm,eq on linear-
elastic FEA of cool down step
Fig. 4: Application of αm,eq for particular material
and process on a frame structure
Fig. 1: Thermal and effective chemical shrinkage are
projected on the matrix coefficient of thermal expansion
z
z
x









1
0
eq
m

→
Fig. 2: Experimental Spring-In
data presents target variable
for determination of αM,eq
1.000
1.050
1.100
1.150
1.200
1.250
1.300
1.350
Position1 Position2 Position3 Position4 Position5

[°deg]
"Reiner" Spring-In, MS1-17, MS1-18, MS1-19
15.5.2014 Process Simulation of Composites 45

46. Process simulation including curing: application flow on the
example COMPRO
Thermo-chemical module
• reaction kinetics
• heat conduction
Stress module
• modulus development related to
resin degree of cure, temperature
• resin cure shrinkage and thermal expansion coefficients
Figure: Time-Temperature-Transition-(TTT) Diagram
Figure: modulus development
Figure: Experimental determination of effective HTC
Virtual autoclave
• heat transfer autoclave gas → part-tooling-assembly
• feedback control autoclave
control routine – status
variables (,T)
Flow Module
• resin flow due to laminate compaction (viscosity, permeability)
→ variations in wall thickness and fiber volume content
Figure: Force-Displacement-Diagram Fiber Bed Compaction
COMPRO is a commercial composite
processing software: Convergent
Manufacturing Technologies, Canada
Johnston A., Hubert P.,
1996
15.5.2014 Process Simulation of Composites 46

47. Karkanas, Partridge: Cure Modeling and Monitoring of Epoxy/Amine Resin
Systems. II. Network Formation and Chemoviscosity Modeling
Cure
Shrinkage
Characterization for Process Simulation
0 50 100 150 200 250
-7
-6
-5
-4
-3
-2
-1
0
1
2
3
x 10
-5
time [min]
Residual
dalpha
/
dt
[1/s]
residual dalpha / dt of the model solution
0 50 100 150 200 250
0
1
2
3
4
5
6
7
8
x 10
-4
time [min]
dalpha
/
dt
[1/s]
dalpha / dt of the model solution
0 50 100 150 200 250
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
time [min]
alpha
[1]
alpha of the model solution
Resin Cure
Kinetics
Modulus
Development
Database
Viscosity
Development
15.5.2014 Process Simulation of Composites 47

48. • Quantities:
• Deformations
• Residual stress
• Spatial distribution of fiber volume fraction
• Time history of temperature evolution on the part
• Final degree of cure distribution
• Glass transition temperatures
• Assessment a priori concerning:
• Mounting tolerances, dimensions of tooling
• Load bearing capacity
• Part’s quality (sufficient degree of cure,
glass transition temperatures,
hot spots (resin degradation))
• Optimization via variation of
• Geometry
• Material selection
• Lay-up
• Process cycle
Curing / PID simulation - results
Deformed frame section
Magnification factor: 30
Fig. 1: Spring-In of a generic C-frame after
curing
Fig. 2: Temperature Distribution on a Frame Section at the End of 2nd Ramp
[simulated utilizing Compro2D and Raven, Convergent Manufacturing
Technologies, Vancouver, Canada]
15.5.2014 Process Simulation of Composites 48

49. Simulation Platform
15.5.2014 Process Simulation of Composites Kap.-49

50. Simulation Platform
Material Modeling
Flow Process Simulation
Compaction,
Curing and Consolidation
Structural Analysis
[FACC AG]
Forming Simulation
15.5.2014 Process Simulation of Composites 50

51. Process Simulation Platform - Example
Preforming
• Draping, Braiding, Filament winding, …
• Simulation of the preform process
Preform Characterization
• Experimental
• Numerical
LCM-Simulation
• Tool design, Process time prediction
(Flow front velocity, pressure distribution)
• Process optimization
• Curing simulation (for PID investigations)
15.5.2014 Process Simulation of Composites 51

52. Conclusion - Outlook
15.5.2014 Process Simulation of Composites Kap.-52

53. Manufacturing
Geometry, Quality
(Waviness, Porosity, etc.)
In-service,
Recycling
Allowable Damages
Repair
Product Development
Design, Process Simulation,
Structural Analysis, Testing,
Quality Assurance,…
Geometry
Effects
Material
Robust Design
via Simulation as Built
Thank you
for your attention!
15.5.2014 Process Simulation of Composites 53