Identification of orthotropic elastic properties of wood by digital image correlation and finite element model updating techniques

Identification of orthotropic elastic properties of wood by digital
image correlation and finite element model updating techniques
4th InternationalConference on Structural Integrity (ICSI2021)
30th August – 2nd September 2021 (virtual)
*Corresponding author: joaodiogofh@ua.pt
J. Henriquesa,*, J. Xavierb, A. Andrade-Camposa
aTEMA, Department of Mechanical Engineering, University of Aveiro, Campus Universitário de Santiago, 3810-193
Aveiro, Portugal
bUNIDEMI, Department of Mechanical and Industrial Engineering, NOVA School of Science andTechnology, NOVA
University Lisbon, 2829-516 Caparica, Portugal

Identification of orthotropic elastic properties of wood by digital image correlation and finite element model updating | ICSI2021 J. Henriques, J. Xavier, A.Andrade-Campos 2
1
4
2
3
Introduction
Experimental tests
Methodology
Results and discussion
5 Conclusions
Outline

3
Introduction
1
Food and Agriculture Organization of the United Nations (FAO))Global demand for wood product
▪ Wood and wood-based
products have been
gathering momentum over
the past decade.
▪ Wood is a complex
biological material with a
heterogeneous and
hierarchical structure.
Chen, C., Kuang, Y., Zhu, S. et al. Structure–property–function relationships of
natural and engineered wood. Nat Rev Mater 5, 642–666 (2020)
Identification of orthotropic elastic properties of wood by digital image correlation and finite element model updating | ICSI2021 J. Henriques, J. Xavier, A.Andrade-Campos

4
Introduction
1
Marcia Argyriades, Metropol Parasol // The World’s Largest Wooden Structure
▪ The characterization of the wood’s properties is crucial in development of
new products and design of wood structures.

5
Introduction
1
Vegter, H. & An, Y.G.. (2008). Mechanical testing for modeling of the
material behaviour in forming simulations. Proceedings of the 7th
International Conference and Workshop on Numerical Simulation of
3D Sheet Metal Forming Processes, Interlaken, Switzerland. 55-60.
DIC standard 3D, Dantec Dynamics.
▪ Classical identification methods rely on
punctual surface deformation measurements,
such as the use of strain gauges.
▪ Novel photomechanical approaches involving
full-field measurements coupled to inverse
identification techniques.

6
Introduction
1
Main goal of the work:
➢Identification of homogeneous linear elastic orthotropic constitutive parameters of
Pinus pinaster Ait. on the RT plane through novel photomechanical approach:
▪ Using uniaxial compression
test on on-axis rectangular
specimens, under quasi-
static loading conditions.
Ux= 0
Uy= 0
Fexp
x
y

7
Experimental tests
2
Material and specimens
▪ Pinus pinaster Ait. specimens:
Radial boards were initially cut and air-
dried to a moisture content of 12%.
20 mm
10 mm
T
R
Clear wood specimens manufactured
on the RT plane with nominal
dimensions:
20(R)×10(T)×4(L) mm3

8
Experimental tests
2
Compressive experimental test
▪ Instron 5848 Microtester machine;
▪ Cross-head displacement of 0.5
mm/min;
▪ Load cell of 2 kN.
Testing
machine
Lightning
Optical system
(camera and lens)
Specimen

9
Experimental tests
2
2D digital image correlation – optical system
DIC region of interest
2D DIC – optical system
Camera: Baumer Optronic FWX20
Lens: AF Micro-Nikkor 200mm f/4D ED-IF
Image resolution: 1624×1236 px2
Field of view: 20.5×15.5 mm2
Working distance: 742 mm
Conversion factor: 0.0132 pxmm
Image acquisition rate: 1 Hz
Speckle pattern technique: Airbrush painting
Average speckle size: 2.714 px/0.0365 mm
DIC software: MatchID

10
Experimental tests
2
DIC - Parameteric analyis
Correlation settings of the parametric analysis
Step size: 5 px
Shape function: {Affine, Quadratic}
Strain interpolation: {Bilinear (Q4),
Biquadratic (Q8)}
Virtual strain gauge: {41-661 px
0.54 – 8.73 mm}

11
Experimental tests
2
Selected DIC settings
2D DIC settings
Image resolution: 1624×1236 px2
Conversion factor: 0.0132 pxmm
Correlation criterion: Zero-normalized sum of square
differences (ZNSSD)
Interpolant: Bicubic spline
Shape function: Quadratic
Subset size, step size: 17 px, 5 px
Image pre-filtering: Gaussian, 5 px kernel
Strain window size: 11
Strain interpolation: Bilinear Q4
Strain convention: Green-Lagrange

12
3
Finite element model
Methodology
▪ Geometry constructed on experimental
images.
▪ FE model implemented in ANSYS software using:
- 2D 4-node structural solid elements, mainly quadrilateral;
- Changing to triangular when it is required to fit the
irregular geometry.

Ux
Uy
Ux
Uy
13
3
Finite element model - DIC based boundary conditions
Methodology
x
y

14
3
Finite element model updating
Methodology
▪ Objective function:
▪ Strain term:
▪ Force term:
Measurement points,
WeigthingCoeffiecient,

15
3
Flowchart of the described material parameter identification chain
Methodology

16
4
Convergence study for the identified parameters
Optimization method:
▪ Nelder-Mead simplex method
WeigthingCoeffiecient:
▪ WF = 10-3
Initial parameters set:
▪ ReferenceValues

17
4
Numerical vs experimental strain fields (Specimen 06)
εxx
εyy
εxy
DIC FEMU Difference (%)

18
4
Results from the inverse parameter identification
Specimen 01 2103
Specimen 02 2305
Specimen 03 1221
Specimen 04 1416
Specimen 05 1981
Specimen 06 1624
Specimen 07 1534
Mean 1740
Standard deviation 396
COV (%) 22.7
ER (MPa)
Reference parameters 1912

19
4
Specimen 01 580
Specimen 02 820
Specimen 03 845
Specimen 04 536
Specimen 05 1361
Specimen 06 912
Specimen 07 798
Mean 836
COV (%) 32.3
ET (MPa)

20
4
Specimen 01 0.701
Specimen 02 0.781
Specimen 03 0.721
Specimen 04 0.653
Specimen 05 0.800
Specimen 06 0.750
Specimen 07 0.762
Mean 0.738
Standard deviation 0.050
COV (%) 6.8
νRT
Reference parameters 0.586

21
4
Specimen 01 502
Specimen 02 481
Specimen 03 298
Specimen 04 412
Specimen 05 448
Specimen 06 140
Specimen 07 226
Mean 358
COV (%) 38.8
GRT (MPa)

22
5 Conclusions
▪ The results from the inverse parameter identification approach show the accurate
identification of two out of four RT linear elastic parameters of Pinus pinaster.
▪ There is the potential to identify all the material parameters with only one test
configuration, given that the test configuration submits the material to a
combined state of stress and strain, in a way that all material parameters play a
role in its mechanical behaviour.
▪ In future work, other single test configurations can be inspected in order to
enhance the identifiability of wood material properties.

Thank you for your attention!
4th International Conference on Structural Integrity (ICSI2021)
30th August – 2nd September 2021 (virtual)
*Corresponding author: joaodiogofh@ua.pt
J. Henriquesa,*, J. Xavierb, A. Andrade-Camposa
Identification of orthotropic elastic properties of wood by digital image correlation and finite element model
updating techniques
ACKNOWLEDGEMENTS
This project has received funding from the Research Fund for Coal and Steel under grant agreement No
888153. The author also gratefully acknowledges the financial support of the Portuguese Foundation for
Science and Technology (FCT) under the project PTDC/EME APL/29713/2017 by UE/FEDER through the
programs CENTRO 2020 and COMPETE 2020, and UID/EMS/00481/2013-FCT under CENTRO-01-0145-
FEDER-022083.

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