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Wood Properties and Processing

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Nguyễn Gia Hào

Academic year: 2023

Chia sẻ "Wood Properties and Processing"

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Douglas fir (Pseudotsuga menziesii(Mirb.) Franco), the main commercial timber in the Pacific Northwest (PNW), is primarily recognized for its stiffness and strength [1]. Weiskettel [19] found that the maximum branch size was very sensitive to forestry treatment and Brix [20] saw thinning effects mainly in the lower half of the crown.

Materials and Methods 1. Study Sites

They also noted that the branches accounted for some of the variation seen in the acoustic measurements. In the second step, the frequency of the assessment was assessed, given that the assessment was present.

Figure 1. Locations of the Stand Management Cooperative (SMC) installations selected for this study.
Figure 1. Locations of the Stand Management Cooperative (SMC) installations selected for this study.

Results

The behavior of the visual quality models as a system was examined by comparing the effects of log small-end diameter (SED), harvest age and treatment regimen on the predicted quality ratios. As a log's small diameter increases, the share of the Select Structural class increases at the expense of the No.

Figure 2. Percent of end-trim of lumber (a) and visual grade downgrade factors (b) for all lumber combined.
Figure 2. Percent of end-trim of lumber (a) and visual grade downgrade factors (b) for all lumber combined.

Discussion

Mean stand diameter (QMD plot) positively influenced the presence of the Selected Structure scale, as expected, further enhancing the positive effect of log SED. As expected, the greater the TSV, the greater the abundance of the Selected Structure and the No.

Conclusions

Effects of thinning and nitrogen fertilization on branch and leaf production in Douglas-fir.Can. Predicting the effects of forestry regime on branch size and crownwood core in Douglas-fir.For.

Acoustic Velocity—Wood Fiber Attribute Relationships for Jack Pine Logs and Their

Introduction

Final product forecasts can be used to inform and optimize log allocation, distribution and trading decision-making, thus contributing to the potential realization of the objective of value maximization [4-6]. Mathematically, as derived from engineering principles, the dynamic modulus of elasticity (MOEdyndenotedmein this study; GPa) of a log can be expressed as a function of the density-weighted velocity of a longitudinal stress wave (vl; km/s) that propagates through the xylem tissue with its influence on the generation of transverse transversely. ation (1) and noted the primary relationship with which is the green (fresh) wood density (kg/m3) of the xylem tissue of the logs.

Materials and Methods

Table 4 provides a descriptive summary of the derived logs in terms of their dimensions and associated acoustic velocity measurements. Attribute observation pairs and acoustic velocity within the calibration data subset for each of the 8 ratios evaluated are presented in Figure 1A,B.

Table 3. Descriptive statistical summary of the mensuration characteristics of the 61 sample trees by site (n = 31 and 30 for Sewell and Tyrol, respectively).
Table 3. Descriptive statistical summary of the mensuration characteristics of the 61 sample trees by site (n = 31 and 30 for Sewell and Tyrol, respectively).

Variations in Orthotropic Elastic Constants of Green Chinese Larch from Pith to Sapwood

Materials and Methods 1. Materials

A schematic of the sawing pattern used to obtain green larch specimens for static testing is shown in Figure 1. Eight clean test specimens of the required shape and orientation were machined from the cut wood. Resistance strain gauges were attached directly to the specimen surfaces prior to compression testing.

Strain gauges should be placed close to each other so that measurements record the state of deformation for the same point without variation in their elastic properties due to the heterogeneity of the wood. At the same time, the glue must have a high shear stiffness, so that the deformation of the strain gauge is not dampened by the thickness of the glue [19]. Measurements for each sample were performed as quickly as possible to reduce the influence of moisture content on the test results.

As above, the samples for the bending test were measured sequentially and tested as quickly as possible to reduce the variation in the moisture content of the measured samples.

Figure 1. Schematic of sawing pattern for testing specimens. Dashed lines represent the sawing line and the units are millimeters
Figure 1. Schematic of sawing pattern for testing specimens. Dashed lines represent the sawing line and the units are millimeters

Results and Discussion

However, no significant relationship with sampling distance was found for either shear modulus or Poisson's ratio. Therefore, the modulus of elasticity and Poisson's ratio of green larch measured in this research should be satisfied the constraints of Maxwell's theorem. The results from experimental data (Table 2) showed that the relationship between the values ​​of Poisson's ratio at the four sampling positions and sampling distance R was relatively discrete, except for Poisson's ratioνRT.

Thus, the relationships between Poisson's ratios and sampling distance R were obtained as shown in Figures 9a–f. Figure 9 shows the variation patterns of the six Poisson's ratios along the greenwood cross section. However, for the other five Poisson's ratios, there was a discrete relationship between the Poisson's ratio and the sampling distance R .

The values ​​of Poisson's ratios determined in this study changed irregularly with the sampling distance probably due to the difference in moisture content, density or microfibril angle in different parts of the wood.

Table 2. Twelve elastic constants at different sampling locations in cross-sections of green Chinese larch.
Table 2. Twelve elastic constants at different sampling locations in cross-sections of green Chinese larch.

Conclusions

When the sampling distance was above 80 mm, the values ​​of Poisson's ratio increased with the sampling distance again. Therefore, more efforts are required to investigate the variation patterns of Poisson's ratio throughout the cross-section of dry or green wood. Similarly, νRT >νLT>νLR was found for Poisson's ratioνRT,νLT andνLR at the four sampling sites.

The Poisson's ratios measured at the four different sampling positions were similar and the differences between them were not significant. The four sampling positions had similar Poisson's ratiosνTL, although the coefficient of variation was 11.7%. The Poisson's ratio had the largest variation in all elastic constants with a 48.7% in coefficient of variation.

We found a good linear relationship between the longitudinal modulus of elasticity EL, shear modulus of elasticity GRT, Poisson's ratioνRT and the distance from pith.EL,GRT andνRT.

Intra-Ring Wood Density and Dynamic Modulus of Elasticity Profiles for Black Spruce and Jack Pine

Practical Implications

This method was used to determine earlywood and latewood properties in order to obtain a more detailed characterization of wood mechanical behavior. For black spruce and jack pine, the correlation coefficients between wood density and wood DMOE were positive and statistically significant in rings, earlywood, and latewood. Furthermore, high positive correlations were obtained between ring DMOE and both earlywood and latewood DMOE.

Nondestructive Evaluation of Static Flexural Properties of Pine Wood Using Stress Wave Technique.Wood Res. Effects of cambial age and stem height on wood density and growth of jack pine grown in boreal stands.Wood Fib. Tensile properties of earlywood and latewood of lobolly pine (Pinus taeda) using digital image correlation.Wood Fib.

Comparison of earlywood and latewood fibers with respect to tree height and youthfulness. Wood Fib.

Use of Time-of-Flight Ultrasound to Measure Wave Speed in Poplar Seedlings

The results of the statistical analysis for ultrasonic velocity and days of growth are summarized in Table 2. This result implies that days of growth may play a positive role in the ultrasonic velocity of poplar seedlings. As shown in Figure 8, ultrasonic velocity in seedlings increased linearly with increasing days of growth.

There was no significant correlation between ultrasonic velocity and root collar diameter in this work. Therefore, seedling root diameter did not show a significant effect on ultrasonic velocity in this work. Figure 12 shows the relationship between ultrasonic velocity and acoustic resonance velocity in 60 poplar seedlings.

There was a significant correlation between ultrasonic velocity and acoustic velocity, and a similar result was also found in the dynamic MOE values ​​derived from the acoustic resonance test and the ultrasonic test, respectively.

Figure 1. Schematic diagram of specimen preparation for MFA measurement: (a) disc sample position; (b) specimen sampling from cross-section; (c) specimens from discs A, B, C, and D of P-146 poplar seedlings.
Figure 1. Schematic diagram of specimen preparation for MFA measurement: (a) disc sample position; (b) specimen sampling from cross-section; (c) specimens from discs A, B, C, and D of P-146 poplar seedlings.

Machinability Study of Australia’s Dominate Plantation Timber Resources

Materials and Methods 1. Plantation Timber

Due to the depth of the profile, the patterns on the side grain were formed by manual feeding in two passes. The results of ANOVA showed no significant difference between the densities of the three species in this study (p>0.05), which allowed a statistical comparison between the workability characteristics. The changes in density and MC values ​​of the test samples within each species are shown in Figures 3–5.

The rating results of the machinability properties for each species sample are shown in Tables 2–7. The grading results of the samples regarding the formation of silk grain are shown in Table4. None of the test samples of the three species had any grade worse than G3 regarding the formation of silk grain (raised or faded) (Figure 8).

This is partly due to the variation in the density of the samples and its influence on the results obtained.

Table 1. Species sample data.
Table 1. Species sample data.

Artificial Neural Network Modeling for Predicting Wood Moisture Content in High Frequency Vacuum

Results and Discussion 1. Determination of Neuron Number

The BP neural network model has a good performance and can explain 97% of the above experimental values ​​[24]. Initially, the BP neural network model can simulate and predict the change of wood MC during high frequency drying. Figure 8 displays the predicted error curve for the neural network (error = experimental value - predicted value [29]).

The prediction error is about 2%, which proves the feasibility of the BP neural network model in MC prediction. The BP neural network was used to simulate the MC of wood during the high-frequency drying process. Artificial neural network modeling for temperature and moisture content prediction in tomato slices undergoing microwave-vacuum drying.

Moisture content prediction model of ginger hot air drying based on BP Neural Network and SVM.

Figure 5. Training regression graph of BP neural network.
Figure 5. Training regression graph of BP neural network.

Multi-Scale Evaluation of the Effect of Phenol Formaldehyde Resin Impregnation on the

Dimensional Stability and Mechanical Properties of Pinus Massoniana Lamb

Results and Discussion 1. Weight Percent Gain and Density

Figure 2 shows the weight percent gain (WPG) and density of the control and modified wood samples. The increased density of the samples was mainly attributed to the filling of the cell lumens with PF resin. That is, higher concentrations of PF resin could reduce the permeability of the resin in wood.

The anti-swelling and anti-shrinkage efficiency of the modified wood: (a) anti-swelling efficiency; (b) anti-shrinkage efficiency. The longitudinally reduced modulus of elasticity (Er) and hardness (H) of the control and modified wood cell walls are shown in Figure 7, respectively. The modulus of elasticity (Er) and hardness (H) of the wood cell walls modified with 15% PF resin increased by approximately 24.9% and 47.3% compared to the control.

The significance of the elastic modulus of wood cell walls obtained from nanoindentation measurements. Compos.

Figure 3. Micrographs of the cross-sections of (a,b) the control wood, (d,e) the wood modified by PF resin, and tangential-section of (c) the control wood, (f) the modified wood.
Figure 3. Micrographs of the cross-sections of (a,b) the control wood, (d,e) the wood modified by PF resin, and tangential-section of (c) the control wood, (f) the modified wood.

The Impact of Anatomical Characteristics on the Structural Integrity of Wood

Results and Discussion 1. Structural Integrity

Finally, mean early wood vessel diameters were not correlated with structural integrity, although the early wood fractures of all ring-porous hardwoods preferentially occurred in a tangential direction after the vascular rings. Therefore, the potentially positive effect of the wood rays on structural integrity may be superimposed by other anatomical features. Nevertheless, unlike the ring-porous hardwoods, the mean early vessel diameter of the diffuse-porous hardwoods was correlated with the RIM (R) as shown in Fig. 6.

As a result, veins have been shown to be general weak points in the fibrous tissue of hardwood, where the weakness increases with increasing vein diameter. The size, density and distribution of the veins and the density of the rays in the wood have been found to have a significant impact on the structural integrity of the hardwood. On the other hand, the structural integrity of softwood was affected by the number of growth ring edges and the occurrence of resin channels.

As shown by the HEMI method used in this study, it is possible to provide indicators of, for example, the structural integrity of wood.

Figure 1. The relationship between the average oven-dry density and Resistance to Impact Milling (RIM): (a) all wood species (y = 3.1629x + 82.887); (b) softwoods (y = 1.1035x + 83.791);
Figure 1. The relationship between the average oven-dry density and Resistance to Impact Milling (RIM): (a) all wood species (y = 3.1629x + 82.887); (b) softwoods (y = 1.1035x + 83.791);

Hình ảnh

Figure 1. Locations of the Stand Management Cooperative (SMC) installations selected for this study.
Table 2. Selected site, stand and tree characteristics for the four installations by plot.
Table 3. Sample data and percent volume yield by lumber grade of the sampled installations.
Figure 2. Percent of end-trim of lumber (a) and visual grade downgrade factors (b) for all lumber combined.
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