Advanced Analysis of Composites

September 25th 2014, Montréal
Advanced Composite Simulation
Benoît Magneville – [email protected]
LMS Engineering
Project Manager, Composite Expert
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Smarter decisions, better products.
Advanced Composite Simulation
Engineering challenges
Manufacturing
OPTIMIZATION to
minimize weight
Many potential
DAMAGE
mechanisms
Stiffness
reduction
and failure
due to
FATIGUE
Resistance to
Lightning (in
development)
Temperature
affects behavior
Manage acoustic
performance with
reduced weight
Unknown
vibrational
behavior
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2014-09-25
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Advanced Composite Simulation
LMS Engineering, composite development partner
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Agenda
• Application of material identification methodology for advanced
damage analysis of Composites
• Composites structure optimization under Sizing and Design
constraints
• Fatigue of Continuous Fiber Composites for Variable amplitude loads:
a new methodology
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Which composites are considered here?
• High performance structured composites (low weight, high stiffness and
strength)
Continuous fibers,
structured laminated
composite
Unidirectional ply
(UD)
Multi-axial plies NCF
(Non Crimp Fabric)
Woven fabric
• Load carrying structural parts
Aerospace application
Automotive application
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2014-09-25
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Benoît Magneville – [email protected]
Application of material identification
methodology for advanced damage
analysis of Composites
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Smarter decisions, better products.
Damage in Composites:
LMS Samtech solutions based on Continuum
Damage Mechanics (CDM)
• Damage evolution law by Ladeveze and Allix
• Damage modeling of the elementary ply for laminated composites, Composites Science and Technology 43, 1992
Intra-laminar failure
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Native damage
models in LMS
Samcef
Inter-laminar failure
Non-local
Model with
coupling
Siemens PLM Software
Damage in Composites:
LMS Samtech solutions based on Continuum
Damage Mechanics (CDM)
• Intra-laminar failure of the unidirectional plies
• The approach is based on the Continuum Damage Mechanics
ALONG THE FIBERS
IN THE MATRIX
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Damage in Composites:
LMS Samtech solutions based on Continuum
Damage Mechanics (CDM)
• Inter-laminar failure: Delamination
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Damage in Composites:
LMS Samtech solutions based on Continuum
Damage Mechanics (CDM)
Availability at all stages of end-to-end testing process
•
From composite materials identification at coupon level
•
To composite structures sizing at components & full scale level
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Damage material properties identification with
coupon analyses
Coupon level
 Challenges:


Identify the non linear material properties at the coupon level
Have accurate material models for the progressive damage
modeling, easy to use
 Solution:


Native damage models for inter and intra-laminar failures
(Cachan models)
LMS Engineering knowledge for parameter identification
 Transfer of technology
 Benefits:



Virtual material testing, with the non-linearities
Determine allowables in a damage tolerant approach
Input for detailed sizing
ed 
2
11
2(1  d11 ) E10

 22
2

2(1  d 22 ) E20

2

 22
2 E20

 33
2 E30
2


 33
2

2(1  d 22 ) E30



 120 11 22  130 11 33  23
 22 33
E1
E1
E20
0

0
2
12
0
2
2
13
23


0
0
0
2(1  d12 )G12
2(1  d12 )G13
2(1  d 22 )G23
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Damage material properties identification with
coupon analyses
• Parameter identification procedure: a comprehensive test protocol exists
• Technology-transfer projects are proposed for parameters identification
•
•
•
•
Tests needed
Number of tests
Associated standards
Test output requested
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Honda R&D Co., Ltd.
Innovative Methodology for Progressive Damage
Analysis in Composite Design
Challenges
• Weight saving requirements instigate adoption of light weight laminated
composite materials in body design
• Use of new materials necessitates the development of new design
performance evaluation methodology
• The reliability & strength behaviour of composites under complex loading is
non-linear
• Need for development of predictive models and related material
characterization procedures for progressive damage analysis and body
performance evaluation
Composite Delamination
Solution
• LMS Samcef Mecano non-linear finite element solver
• LMS Engineering Services for composite damage model identification
Results
• Sophisticated material models comprehensively implemented for:
• Progressive ply damage (strength, non-linearities, plasticity, coupling
effects in the matrix)
• Delamination (possibly coupled to damage in the plies)
• Development of the parameter identification procedure, based on a limited
amount of physical tests on coupons
• Predictive damage models at the coupon level and at composite subsystem
design concept level
Progressive ply damage
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Honda R&D Co., Ltd.
Innovative Methodology for Progressive Damage
Analysis in Composite Design
Exploitation of the methodology
• Validation of damage models at coupon level
Starting from identified material parameters, the damage model is used to predict
the mechanical behavior at the coupon level for evaluation of the behaviour for
other stacking sequences and hence replacing physical tests.
•
Application of damage models for predictive
delamination behavior at component level
The damage models are supporting the prediction of the progressive damage
and delamination inside the plies and at their interface at component level
Progressive ply damage
Progressive delamination
Source : “Strength Calculation of Composite Material considering multiple progress of failure by
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Ladaveze model”, Y.Urushiyama, T. Naito, JSAE Spring Conference, 2014 52 05
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Honda R&D Co., Ltd.
Innovative Methodology for Progressive Damage
Analysis in Composite Design
•
Application of damage tolerant approach for composite design
•
•
•
•
Barely visible impact damage
Damage induced by a low energy impact
Delamination appears at the interfaces between the plies
Agreement between simulation and C-scan test results
The stains represent the level of delamination
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LATECOERE
Delamination of a pre-cracked stiffener
Component level
 Challenges:
Imposed displacement

Flange- left part (4 plies)
[-45/90/0/45]
Cap (4 plies)
[45/90/0/-45]
Existing crack
Existing cracks



Clamp
Investigate the damage propagation at the interfaces of
plies in a composite structure
Multi-delaminated composite material
Many contact conditions between initial defects
Fast solution procedure
 Solution:

Skin (9 plies)
[0/90/45/0/-45/90/0/45/-45]

LMS Samcef with a specific approach for modeling
delamination
LMS Samcef solution with efficient solvers
 Benefits:


Better knowledge of the composite structure, with a
damage tolerant approach
Decrease the safety margins for the composite design
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DAHER
Test Prediction on stiffened panel
Component level
Challenge:
• Evaluate the quality of the test facilities
Solutions:
• LMS Samcef Field for the pre/ post processing
• LMS Samcef non linear solver
• Interlaminar + Intralaminar damage
Benefits:
• Very accurate results
• New design for the test facilities
proposed
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DLR
Composite panel with de-bonding stringer
Sub-system level
 Challenges:


Non linear analysis of thin-walled damaged stiffened
composite panels: buckling, post-buckling and collapse
Accurate results and fast solution procedure
 Solution:


SAMCEF non linear solver
Use of advance progressive damage laws at the detailed
sizing level
 Benefits:


Better knowledge of the non linear structural behavior
Virtual prototype of stiffened panels
Test
Simulation
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AIRBUS GROUP INNOVATIONS
AIRBUS HELICOPTERS
Damage analysis on composite Helicopter Blade
Sub-system level
 Challenges:


Investigate the composite damage in a pre-cracked helicopter
blade.
Check the simulation capabilities to predict the damage evolution
 Solution:


SAMCEF modeling tools and non linear solver
Use of advance progressive damage laws at the detailed sizing
level
 Benefits:


Prediction of final load and prediction of the damage evolution
was performed with success
Better knowledge of the non linear structural behavior
DIC results
Elastic behaviour
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Damage mesomodel
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CEA
Engineering Service: Burst Test Simulations Using
Advanced composite modeling
Sub-system level
Challenges:
• Hydrogen storage is a key issue for the high
scale deployment of fuel cell applications
• Necessary to reach a significant cost
reduction of these storage systems
• Optimization of the composite structure can be
reached thanks to numerical simulation
Solution:
• Parametric Finite Element model
• Use of complex damage modeling for burst
mode type identification
• Use LMS Samcef Mecano solver
Benefit :
• Good correlations with reference tests
• Optimization results – Mass decreased by >30%
• Development of adapted method and tools
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2014-09-25
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Benoît Magneville – [email protected]
Composites structure optimization under
Sizing and Design constraints
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Smarter decisions, better products.
Optimization
Brief overview of LMS Samtech Samcef capabilities
•
Local optimization (thickness, fiber orientation)
•
Stacking sequence optimization with manufacturing constraint
•
Vary large scale optimization (preliminary design of full structures)
Local optimization
Optimization with
geometric non linearites
(buckling, post-buckling,
collapse)
Local optimization
Local/global optimization
Global Optimization
Optimization wrt ply
thickness & fibers
orientation
Stacking Sequence
Optimization (design
rules + inter-regional ply
continuity)
Very Large scale
optimization problems
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Optimization methods
• Genetic Algorithms
• Response Surface Methods
•
•
based on an imported data base
based on a DOE created with our tool (Taguchi tables, D-optimal, …)
• Surrogate Based Optimization
•
•
•
based on a response surface with NN
based on GA
enriched data base at each iteration
• Specific integer programming
•
For stacking sequence optimization of composite structures
• Gradient based methods
•
•
MP: SQP, Multiplier, CG
SCP: Conlin, MMA, GCM, …LARGE SCALE OPTIMIZATON
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AIRBUS
Geometric NL behavior of stiffened panels, up to final
collapse
• 1st step: Local optimization
• Minimize the weight while keeping buckling and collapse load above
prescribed values
Stiffened composite panels
Buckling  Post-buckling  Collapse
Thin walled structures
Linear analysis
K   j SΦ j  0
Buckling
Non linear analysis
F(q,  )  Fext ( )  Fint (q)  0
Post-buckling
d
d

 = load factor
d = transverse displacement
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Decrease the weight and
put those points to
prescribed values
Collapse
Unstable path
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AIRBUS
Geometric NL behavior of stiffened panels, up to final
collapse
• 1st step: Local optimization
• Preliminary study: Total thickness of each UD orientation is a continuous variable
? 0°
? 90°
? 45°
? -45°
? 0°
? 90°
? 45°
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? -45°
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Panel: 3 d.v. t0°, t90°, t45°
Hat:
3 d.v. t0°, t90°, t45°
Total: 36
d.v. PLM Software
Siemens
AIRBUS
Geometric NL behavior of stiffened panels, up to final
collapse
Initial Assumption: Buckling optimization: Linear stability analysis in the optimization loop
Weight = 0.69
Weight = 1.
1 = 1.2
1 = 2.7
min Weight
RFbuckling  bound1
collapse = 1.05 < 1.2

collapse
Non conservative
solution !
3
1
2.5
Design functions
•
Due to geometric non-linearities
2
1.5
1
0.5
Relative weight
0
0
2
4
6
8
10
12
14
Non linear analysis
must be included into
the optimization loop
Iterations
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AIRBUS
Geometric NL behavior of stiffened panels, up to final
collapse
Correct Assumption: Buckling, post-buckling and collapse optimization (NL analyses)
Weight = 1.
Weight = 0.61
1 = 2.7
1 = 0.8
collapse = 2.1
collapse = 1.2
min Weight
RFbuckling  bound1
RFcollapse  bound2
2.5
2
1.4
1.2
3
1
Design functions
1.5
1
1
Load factor
2.5
Load factor
•
2
collapse
1.5
0.8
0.6
0.4
1
0.2
0.5
0.5
Relative weight
0
0
0
0
10
20
30
40
0
Transversal displacement (mm)
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2
4
6
Iterations
8
10
0
10
20
30
displacement (mm)
We can tune Transversal
the shape
of the
load-displacement curve
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AIRBUS
Geometric NL behavior of stiffened panels, up to final
collapse
• 1st step: Local optimization: Conclusion
Initial design
Bad thicknesses and
fibers proportions
Optimal design
Weight = 0.61
Weight = 1.
1 = 2.7
Global buckling mode
1 = 0.8
collapse = 2.1
Heavy structure
collapse = 1.2
Good thicknesses and
fibers proportions
Local buckling modes,
before the collapse
Safer and lighter
structure
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Local-global optimization
Stacking sequence optimization over a structure
• 2nd step: Local/Global optimization (Stacking sequences optimization)
In each zone, optimal stacking sequence
(plies at 0°, 90°, 45°, -45°)
Design rules
Across the zones, manufacturing
constraint (ply continuity)
OK
KO
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Local-global optimization
Stacking sequence optimization over a structure
Backtracking algorithm  optimal stacking sequence table generator
Data from step 1  Nb of plies
Number of plies
For a given number of
plies, optimal stacking
sequence
Ply drops between the
zones: ply continuity
OK
KO
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Local-global optimization
Stacking sequence optimization over a structure
Local and Local-Global optimization  Conclusion
Step 1: optimization of ply
thickness for 0, 90, 45 and -45
Step 2: backtracking (plies shuffling)
Min weight
- Design rules OK
- Manufacturing constraint OK
- Buckling / Collapse OK
Stability constranits
Possibly with NL
analysis
0°
0°
90°
45°
90°
45°
-45°
-45°
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Optimal preliminary sizing of the A350
Large-scale optimization
Wings
1000 DV’s
250000 Constraints
Central Wing Box
250 DV’s
160000 Constraints
Vertical Tail Plane
100 DV’s
100000 Constraints
Horizontal Tail Plane
100 DV’s
100000 Constraints
Vertical Tail
Plane
Outer Wing Centre Wing
Box
Box
Horizontal Tail
Planes
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Optimal preliminary sizing of the A350
Large-scale optimization
PX
•
NXg
Super-stringers
NYg
NXYd
NXYg
NYd
NXd
•
Panel design variables
Design Variables:
t – Skin Thickness
p0 – Percentage 0-degree
p90 – Percentage 90-degree
•
Stiffener design variables
Design Variables:
ba - Stringer foot width
h - Stringer height
ta – Stringer angle thickness
tb – Stringer core thickness
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Optimal preliminary sizing of the A350
Large-scale optimization
•
Sizing criteria taken into account in the optimization
• Mass
• Reparability
• Buckling
• Damage tolerance
• Design rules
• Micro-strains
•…
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Benoît Magneville – [email protected]
Fatigue of Composites for Variable
amplitude loads: a new methodology
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Smarter decisions, better products.
Fatigue of continuous fiber composites
Advantage and challenge
Unidirection
al ply
•
•
•
Light weight advantage
Woven
fabric
Multi-axial
plies NCF
Composites typically show good fatigue
behavior (many load cycles till failure)
But: Fatigue onset is very early 
Macroscopic stiffness change
Therefore: Designing for fatigue vs. no
damage means:
• Benefit from good fatigue behavior
• Extra weight reduction
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Fatigue of continuous fiber composites
Progressive Stiffness Degradation Modeling
Typical stiffness degradation curve
 3 phases
Continuum Damage Mechanics framework
with damage growth rate equation dD/dN
𝜕𝑑𝐼
= 𝑐1 ∙ Σ𝐼 ∙ 𝑒
𝜕𝑁
−𝑐2
𝑑𝐼
Σ𝐼
+ 𝑐3 ∙ 𝑑𝐼 ∙ Σ𝐼2 1 + 𝑒
𝑐5 Σ𝐼 −𝑐4
(W.V.Paepegem, 2001)
• Intra-laminar failure for the UD (same approach as Cachan static damage model)

ed 
E0
E0(1-d)  0
12

e

 112
2(1  d11 ) E10
 11 22 
0

 22
2

2(1  d 22 ) E20
 130
 230
E1
E20
E1
 122
2(1  d12 )G120
 11 33 
0


 22
2 E20
2


 33
2 E30
2

 33 

2(1  d 22 ) E30
 22 33
 132
 232

0
2(1  d12 )G130 2(1  d 22 )G23
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2
Fatigue of continuous fiber composites
Constant amplitude loading (Past experience)
Work with an university partner, expert in fatigue of composites:
Ghent University (Belgium) – Prof. Wim Van Paepegem
1. Static cycle
2. Fatigue law
d
 ...
N
3. Increase of the damage variable (Dd), for the
Gauss point on all elements
4. Determine DN (= NJUMP « global »)
5. Update the damage level Ddi (loop on the elements)
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Fatigue of continuous fiber composites
Variable amplitude loading
Improved Cycle Jump algorithm
• Tests and calculation on ply level
• Possible lay-up optimization
• No new tests for variable amplitude
• Stiffness degradation and stress redistribution
Proven hysteresis operator approach
• Only efficient approach to cover continuous loss
in stiffness and fatigue resistance
Allows simulation of full structures
Van Paepegem, W ; Degrieck, J; “Fatigue Degradation modelling
of plain woven glass/epoxy composites”, Composites: Part A
32:1433-1441, 2001
Van Paepegem, W.; “Development and finite element
implementation of a damage model for fatigue of fiber reinforced
polymers” Ph. D. thesis, Department of Material Science and
Engineering, Ghent university, 2002.
Xu, J., Lomov, S.V., Verpoest, I. Daggumati, I., Paepegem, W.
Van and Degrieck. J., “Meso-scale modeling of static and fatigue
damage in woven composite materials with finite element method.”
presented in 17th International Conference on Composite Materials
(ICCM-17). 2009. Edinburgh: IOM Communications Ltd.
Xu, J; “Meso Finite Element Fatigue Modelling of Textile
Composites” Ph. D. thesis, Dept MTM, Katholieke Universiteit
Leuven, Belgium, 2011
Brokate, M; Dressler, K; Krejci, P: Rainflow counting and energy
dissipation in elastoplasticity, Eur. J. Mech. A/Solids 15, . 705-737,
1996
Nagode, M., Hack, M. & Fajida, M. “High cycle thermo-mechanical
fatigue: Damage operator approach”, Fatigue Fract Engng Mater
Struct 32(6), 505-514, Wiley & Son, 2009
Nagode, M., Hack, M. & Fajida, M., “Low cycle thermo-mechanical
fatigue: Damage operator approach”, Fatigue Fract Engng Mater
Struct 33(3), 149-160, Wiley & Son, 2010
Nagode, M. & Hack, M.: “The damage operator approach, creep
fatigue and visco-plastic modeling in thermo-mechanical fatigue”,
SAE International Journal of Materials & Manufacturing, 4(1), 632637. doi:10.4271/2011-01-0485, 2011.
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Fatigue of continuous fiber composites
Conclusion
Fatigue behaviour of Metals
& Composites
Exploit full advantage of
the gradual stiffness
degradation characteristics
of composite in design
Fatigue material
properties at ply level
Technology for
composite durability
evaluation based on
progressive stiffness
degradation model
Efficiency
Fiber orientation & Ply
stacking
Include dynamic loading in the
design process
Accuracy
FE Composite
Modelling
Complex cyclic loading
scenarios
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Fatigue of continuous fiber composites
Conclusion
Engagement model
• Engineering Services & Transfer of Technology
Assistance for test
design and set-up
Material
characterization
Fatigue calculation
• Workshops
• Tests specifications
Test set up
Material
Characterization
• Characterize Material
• Tools based on standard software
• Lead through process
• User defined damage models
FE Composite
Modelling
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Thank you
Benoît Magneville – [email protected]
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20XX-XX-XX
Smarter decisions, better products.
Siemens PLM Software

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