Hong Ling, Sandhya Samarasinghe, G. Don Kulasiri. (2009). Modelling variability in full-field displacement profiles and Poisson ratio of wood in compression using stochastic neural networks. Silva Fennica vol. 43 no. 5 article id 460. https://doi.org/10.14214/sf.460

Keywords: wood; digital image correlation; displacement profiles; variability; micro structure; stochastic neural networks; Poisson ratio

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Vertical and horizontal displacement profiles in compression parallel-to-grain in a 20 x 20 mm area (30 x 21 or 630 points) in the Tangential–Longitudinal (T–L) and Radial Longitudinal (R–L) sections of small wood columns were obtained from digital image correlation applied to simultaneously captured images of the two surfaces. These consisted of 21 displacement realisations of 30 points along the length of the specimen. They revealed considerable local variations. Stochastic neural networks were successfully developed to simulate trends and noise across and along a specimen in both displacements as well as Poisson ratios in T–L and R–L sections for two selected load levels of 20kN and 40kN. These networks specifically embed noise characteristics extracted from data to generate realistic displacement and Poisson ratio realisations with inherent variability. Models were successfully validated using independent data extracted based on bootstrapping method with high accuracy with R² ranging from 0.79 to 0.91. The models were further validated successfully using a second approach involving Confidence Intervals generated from the data extracted from the models. Models and experimental results revealed that for 20kN load, both vertical and horizontal displacements in T–L section were less heterogeneous across the specimen (smaller vertical shearing and horizontal strain, respectively) than those in the R–L section. For the 40kN load, both displacement profiles in the T–L section were less noisy and more compact than those for the 20kN load indicating less heterogeneity due to compaction of structure. In the R–L section, larger vertical shearing and horizontal strains persisted at 40 kN load. Poisson ratio decreased with load and it was nonlinear in both sections but T–L section showed much less noise across the specimen than the R–L section.

Ling, Centre for Advanced Computational Solutions (C-fACS), Lincoln University, Canterbury, New Zealand E-mail: hl@nn.nz
Samarasinghe, Centre for Advanced Computational Solutions (C-fACS), Lincoln University, Canterbury, New Zealand E-mail: sandhya.samarasinghe@lincoln.ac.nz
Kulasiri, Centre for Advanced Computational Solutions (C-fACS), Lincoln University, Canterbury, New Zealand E-mail: gdk@nn.nz

article id 415, category Research article

Sandhya Samarasinghe, Don Kulasiri. (2004). Stress intensity factor of wood from crack-tip displacement fields obtained from digital image processing. Silva Fennica vol. 38 no. 3 article id 415. https://doi.org/10.14214/sf.415

Keywords: Pinus radiata; wood; fracture toughness; stress intensity factor; digital image correlation; orthotropic fracture theory

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Stress intensity factor of radiata pine (Pinus radiata) in Tangential-Longitudinal opening mode was determined from crack-tip displacement fields obtained from digital image correlation in conjunction with orthotropic fracture theory. For lower loads, experiments agreed with the linear elastic fracture theory but for higher loads, stress intensity factor and load relationship was nonlinear. For 41% of the specimens tested, tip-displacement based stress intensity factor agreed with that based on the ASTM standard formula for lower loads but deviated for higher loads closer to failure. The tip displacement plots showed that the nonlinear behaviour is due to large displacements which we attributed to large plastic deformations and/or micro-cracking in this region. The other 59% specimens showed a similar trend except that the crack-tip based stress intensity factor was consistently higher than the value obtained from the standard formula. The fracture toughness from tip displacements was larger than the standard values for all specimens and the two were related by a logarithmic function with an R2 of 0.61. The study also established that fracture toughness increases with the angle of inclination of the original crack plane to the Radial Longitudinal plane.

Samarasinghe, Lincoln University, P.O. Box 84, Canterbury, New Zealand E-mail: ss@nn.nz
Kulasiri, Lincoln University, P.O. Box 84, Canterbury, New Zealand E-mail: kulasird@lincoln.ac.nz

article id 630, category Research article

S. Samarasinghe, G. D. Kulasiri. (2000). Displacement fields of wood in tension based on image processing: Part 2. Crack-tip displacements in mode-I and mixed-mode fracture. Silva Fennica vol. 34 no. 3 article id 630. https://doi.org/10.14214/sf.630

Keywords: wood; digital image correlation; fracture modes; orthotropic fracture; tip displacement

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Near tip displacement fields for tensile loaded cracked rubber and wood with a crack parallel-, perpendicular-to-grain, and a parallel-to-grain crack inclined 30°, 45°, and 60° to the load axis were obtained from digital image correlation (DIC). Theoretical displacements were also obtained for rubber and wood using isotropic and orthotropic fracture theory, respectively. The results showed that DIC can reveal fine details of the nature of displacements and the influences of crack tip in both rubber and wood. Experimental crack tip displacements for wood compare well with theory; particularly, when load is perpendicular-to-grain. Some anomalies were found in the tip displacements in the direction of the tracheids due to the unique nature of their behaviour not accounted for by theory. Mixed-mode crack tip displacement fields for wood clearly showed the increasing influence of crack angle on the displacements, and the displacements perpendicular to crack compared very well with theory. The displacements parallel to crack showed some variations owing to the involvement of tracheids.

Samarasinghe, Lincoln University, Appl. Computing, Mathematics and Statistics Group, P.O. Box 84, Canterbury, New Zealand E-mail: ss@nn.nz
Kulasiri, Lincoln University, Appl. Computing, Mathematics and Statistics Group, P.O. Box 84, Canterbury, New Zealand E-mail: kulasird@tui.lincoln.ac.nz

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