CIVIL ENGINEERING AND MATERIALS ENGINEERING
COMPOSITES GROUP
MULTI-SCALE MODELING OF STRAND-BASED WOOD COMPOSITES
FPS 65th International ConventionJune 19-21, 2011, Portland, OR, USA
T. Gereke, S. Malekmohammadi, C. Nadot-Martin, C. Dai, F. Ellyin, and R. Vaziri
2
UBC Composites Group
• 2 Departments: Civil Engineering & Materials Engineering
• Group exists since the early 1980‘s
• Projects:
– Processing for Dimensional Control
– Development of an Integrated Process Model for Composite
Structures
– Tool-part interaction - Experiments and modeling
– Viscoelaticity and residual stress generation
– Characterization of damage in impact of composite structures
– Damage and strain-softening characterization
– Observation of fracture in-situ inside an SEM: aerospace and
biomaterial applications
– Multi-scale modelling of wood composite products
www.composites.ubc.ca
3
Outline
• Motivation
• Multi-Scale Approach
• Partial Resin Coverage
• Results
– Mesoscale
– Macroscale
• Conclusions
4
Motivation
• Strand-based wood composites frequently used as
construction materials in residential and other buildings
• Certain requirements on their mechanical properties
such as stiffness and strength
• Realistic modeling as a viable alternative to time
consuming and costly experiments
• Goal: development of a numerical model that can serve
as a tool to control the properties of the constituents in
order to optimize the macroscopic material behavior
5
Multi-Scale Approach
Macroscale
PSL beam
Mesoscale
Resin covered strand
MicroscaleWood cells
x1
x2
x3
Strand
Resin
x3x1
x2
Courtesy of Hass et
al., Wood Sc Tech,
2011
ResinInterfaceWood
Void
6
x3x1
x2
Real Mesostructure
Macroscale
PSL beam
Mesoscale
Resin covered strand
Structure
Idealized Mesostructure
Multi-Scale Approach (cont.)
Resin
Wood
Unit Cell
y3
y1
y2
Macroscopic Element
Effective composite properties
q
7
Multi-Scale Approach (cont.)
Dimensions:
• X1 = 380 mm
• X2 = 39 mm + 6tR
• X3 = 40 mm + 16tR
• Y1 = 600 mm + 2tR
• Y2 = 13 mm + 2tR
• Y3 = 5 mm + 2tR
Macroscale
PSL beam
Mesoscale
Resin covered strand
PSL
x3
x1
x2
X2
X1
X3
Unit Cell
y3
y1
y2
Y2
Y3
Y1
Wood
Resin
tR, resin thickness
8
Multi-Scale Approach (cont.)
Loadq=0°
q=5°
q=10°
q=20°
Macroscale
PSL beam
Mesoscale
Resin covered strand
• Randomly distributing
maximum grain angle
(distribution according
to Clouston, 2007*)
• Calculation of effective
elastic properties by
applying periodic
boundary conditions to
the unit cell
403340
1301
116
0
500
1000
1500
0 5 10 20Maximum grain angle, q (°)
Fre
qu
en
cy
*Clouston, P., Holzforschung 61:394-399, 2007
PSL
Unit Cell
x3
x1
x2
y3
y1
y2
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Partial Resin Coverage
Why not a full resin coverage?
• In manufacturing process of strand-based composites, strands
are not fully covered by the resin.
• Resin distribution should be considered in the modeling
approach.
• Voids are distributed randomly through a typical wood
composite (PSL).
10 cm × 10 cm 0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60
Void size (%)
Rela
tive f
req
uen
cy Micro-
voidsMacro-voids
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Partial Resin Coverage (cont.)
Full resin coverage
• Linear relation between resin content (RC) and resin thickness (tR)
• No resin penetration
• No voids in the microstructure
Partial resin coverage
• Resin area coverage (RA) increases as more resin is used in the manufacturing process
• No resin penetration
• Two scenarios considered:
A. RA increases with RC
uniformly at a constant tR
B. Both RA and tR increase with RC (Dai’s model*)
*Dai, C. et al., Wood and Fiber Science 39:56-70, 2007
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0% 2% 4% 6% 8%
0%
20%
40%
60%
80%
100%
Resin content by volume, RC
Resin
area c
overag
e, RA
Resin
th
ickn
ess, t R
(m
m)
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Partial Resin Coverage (cont.)
Scenario ARA increases with RC
uniformly at a constant tR
Scenario BBoth, RA and tR increase with resin content
solidsrr
CsA
RMC
RR
12exp1
0%
20%
40%
60%
80%
100%
0% 1% 2% 3% 4% 5% 6% 7% 8%
0.00
0.05
0.10
0.15
0.20
0.25
0.30
Resin content by volume, RC
Resin
area c
overag
e, RA
Resin
th
ickn
ess, t R
(m
m)
0%
20%
40%
60%
80%
100%
0% 1% 2% 3% 4% 5% 6% 7% 8%
0.00
0.05
0.10
0.15
0.20
0.25
0.30
Resin content by volume, RC
Resin
area c
overag
e, RA
Resin
th
ickn
ess, t R
(m
m)
Dai et al. (2007):
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Partial Resin Coverage (cont.)
• Introducing void elements for partial coverage simulations
Void elements are distributed by replacing some resin
elements in the original full coverage discretized FE
model
RA = 60%.
Discretized Full Coverage FE model
Discretized Partial Coverage FE model
Void Elements
Wood Elements
Resin Elements
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Results (Mesoscale)
Full coverage Partial coverage
E1 = 12.64 GPa
RA = 100%
E1 = 12.41 GPa
RA = 60%
12
3
S23 S23
• Comparison with full coverage case
14
11.40
11.60
11.80
12.00
12.20
12.40
12.60
12.80
13.00
0% 20% 40% 60% 80% 100%
tR = 0.08 mm
tR = 0.28 mm
tR variable
Resin area coverage, RA
E1
(G
Pa)
0%
20%
40%
60%
80%
100%
0% 2% 4% 6% 8%
Resin content by volume, RC
Resin
area c
overag
e, RA
tR = 0.08 mm
tR = 0.28 mm
tR variable
Results (Mesoscale)
Scenario A
Scenario B
n=10 n=1011.40
11.60
11.80
12.00
12.20
12.40
12.60
12.80
13.00
0% 2% 4% 6% 8%
tR = 0.08 mm
tR = 0.28 mm
tR variable
Resin content by volume, RC
E1
(G
Pa)
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Results (Mesoscale)
• Scenario A
– For a constant resin area coverage, as the resin thickness
decreases, resin content decreases while E1 increases
– E1 increases with resin area coverage
• Scenario B
– By adding more resin, E1 increases until RA ≈ 80% then it
drops, since E of the resin is lower than EL of the wood
• Resin thickness and resin area coverage could
significantly alter the properties of the unit cell.
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Results (Macroscale)
• Prediction of bending MOEScenario B
MOE highly depends on resin thickness and then resin area coverage
as the resin thickness increases.
Scenario A
7
8
9
10
11
0% 2% 4% 6% 8%
Resin content by volume, RC
Ben
din
g M
OE (
GP
a)
tR = 0.08 mm
tR = 0.28 mm
7
8
9
10
11
0% 20% 40% 60% 80% 100%
Resin area coverage, RAB
en
din
g M
OE (
GP
a)
tR = 0.08 mm
tR = 0.28 mm
7
8
9
10
11
0% 20% 40% 60% 80% 100%
Resin area coverage, RAB
en
din
g M
OE (
GP
a)
tR variable
7
8
9
10
11
0% 2% 4% 6% 8%
Resin content by volume, RC
Ben
din
g M
OE (
GP
a)
tR variable
n=250 n=250
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Conclusions
• The concept of resin area coverage has been incorporated into
the multi-scale model.
• A series of codes were developed to distribute void elements
randomly and analyze results both at meso- and macroscale.
• Stochastic simulation shows that MOE could vary between 8 to
10 GPa depending on the resin thickness and resin area
coverage.
• Establishing a realistic relation between RC and RA could help
predicting the macroscopic properties of wood composites
more accurately within a large range of RC.
• Incorporation of resin penetration and strand compaction will
improve the model in the future (microscale)
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Acknowledgements
• Benjamin Tressou, ENSMA, France
• Dr. Carole Nadot-Martin, ENSMA, France
• Sardar Malekmohammadi, UBC
• Dr. Chunping Dai, FPInnovations
• Mr. Gregoire Chateauvieux and Mr. Xavier Mulet,
ENSAM, France
• Financial support: Natural Sciences and Engineering
Research Council of Canada (NSERC)
Questions?