COMPARISON BETWEEN TENSILE AND COMPRESSIVE YOUNG’S MODULUS OF STRUCTURAL SIZE LUMBER Kwang-Mo Kin1, Kug-Bo Shim2 ABSTRACT: To evaluate MOE of glued laminated timber, usually non-destructive MOE values of lumber were used as input data. However, as the glulam in under bending load, bending stress of the glulam divided into two loading mode to the lumber. It is tension and compression stress in the glulam. The tensile modulus is roughly two times greater than compressive modulus. Therefore, it is important to define the differences and relations with non-destructive MOE and tensile and compressive modulus. This study was carried out to predict tensile and compressive modulus from dynamic or static MOE of major softwood lumber in Korea. The measured MOE of the same specimens by various test methods were slightly different. Especially, the tensile modulus was two times greater than the compressive modulus at the same specimen. The dynamic MOE or static edgewise and flatwise MOE could be used to predict tensile and compressive modulus for estimate glulam MOE because of its significant correlation between those MOE and tensile and compressive modulus.

KEYWORDS: Glulam, Tensile modulus, Compressive modulus, Flatwise MOE, Edgewise MOE, Dynamic MOE 1 INTRODUCTION 1 2

The Korea Forest Research Institute has studied on glued laminated timber (glulam) to improve its properties for adding values [1-4]. Kim et al. [3,4] predicted modulus of elasticity of glulam by transformed section methods. The predicted MOE of glulam was overestimated about 10 to 30% when dynamic MOE of lumber was chosen as the imput data. Shim et al. [5] studied to improve MOE prediction accuracy of glulam based on neutral axis movement under bending stress. In this study, the measured tensile and compressive modulus from actual size structural lumber showed different values from static or dynamic MOE of lumber which are used as input data of lumber to predict MOE of glulam. Especially, the neutal asix under bending stress shifted to the tension side greater than predicted movement based on the MOE of lumbers because tensile modulus of actual size structral lumber was about two times greater than compressive modulus. Shim et al. reported that the difference between tensile and compressive was caused by growing characteristics of lumber, such as grain deviation near konts or immature wood. However, measuring tensile and compressive modulus for using input data of glulam in

1 Kwang-Mo Kim, Div. of Wood Engineering, Dept. of Forest

t to predict tensile nd compressive modulus from dynamic or static MOE

AND METHODS

elected nd dried. The species, size, moisture contents and oven-

Table 1. Table fication o en

M. Densit(g

plants needs additionally expensive equipment and time consuming job. Therefore, this study was carried ouaof major softwood lumber in Korea. 2 MATERIALS2.1 MATERIALS Six species of major domestic softwoods were chosen to be tested. Ten lumbers from each species were sadry density of specimens were shown in

1: Speci f test specim

Species Size(mm) C.(%)

y/cm3)

Korean Red Pine 38ⅹ140ⅹ3,600 8.68 0.44 Korean Larch 33ⅹ152ⅹ3,600 10.47 0.51 Pitch Pine 34ⅹ148ⅹ3,600 9.54 0.50 Korean Pine 39ⅹ150ⅹ3,600 10.62 0.42 Japanese Cedar 30ⅹ120ⅹ3,600 10.95 0.32 Japanese Cypress 30ⅹ149ⅹ3,600 11.79 0.46 2.2 MEASUREMENT 2.2.1 Surface images Digital images of four sides of lumber were taken to evaluate growing characteristics of lumber prior to

Resources Utilization, Korea Forest Research Institute, Seoul, 130-712, Korea. Email: lovewood@forest.go.kr 2 Kug-Bo Shim, Div. of Wood Engineering, Dept. of Forest Resources Utilization, Korea Forest Research Institute, Seoul,130-712, Korea. Email: kbshim@forest.go.kr

measure MOE. Lumber scanning system and image merging algirithm were used to get digital images of 3,000mm distance of the middle of lumber [6,7].

ngth by ltasonic transmission timber. PUNDIT (CNS Farnell,

UK) was used to m smission timand MODD wa ion (1).

ion velocity, c, was calculated by the average ansmission time divided by the specimen length. Mass

e weight and size of mber.

Figure 1: Lumber scanning system 2.2.2 Dynamic MOE Dynamic MOE of lumber was measured at the middle of lumber in 3,000mm length and 1,000mm leu

easure ultrasons calculated by the e

ic tranquat

e,

ρ×= 2CMOED (1)

Dynamic MOE were measured in three different transducer locations at the end of lumber. Ultrasonic transmisstrdensity, ρ, was measured by thlu 2.2.3 Edgewise bending MOE

Figure 2: Edgewise bending testing machine Edgewise bending MOE was measured by continuous MOE measuring equipment. The edgewise bending MOE was calculated by three point loading method

which measured loads of 5mm edgewise bending deflection at the center of lumber. The span length of dgewise MOE measurement was 3,000mm. To measure

o opposite edgewise

ese Ceder, 85kgf). As the same as e edgewise MOE measurement, the average value of

flection was taken to calculate

e at each end. The displacement of ecimen at 4tonf tension load for 5 species except the

eedgewise bending MOE, twdirections of lumber were tested and the average value of two directions were taken to calculated edgewise bending MOE. 2.2.4 Flatwise bending MOE Flatwise bending MOE was measured by three point loading method with universal testing machine (Instron 5585, 200kN). The load limitation to measure flatwise deflection of lumber was 150kgf for 5 species except the weakest species (Japanthtwo flatwise direction deflatwise MOE of lumber. The specimen length for measuring flatwise MOE was 1,400mm and the span length was 1,000mm. 2.2.5 Tensile modulus Tensile modulus was measured by acutual size tension testing machine (Kyoung Sung Testing Machine Co., Ltd, Korea, 1,000kN) for 3,000mm specimen length and 600mm grip distancspweakest species (Japanese Cedar, 2.5tonf) was measrued by LVDT in two wide sides and 1,000mm distance at thecenter of specimen. The displacements were averaged intwo wide surfaces.

Figure 3: Acutual size tension testing machine 2.2.6 Compressive modulus Universal testing machine (Instron 5585, 200kN) was used for testing compressive modulus of lumber. Additional plates were designed and attached to prevent buckling of specimen under compressive load. The

ecimen length was 1,000mm and compressive ad movement.

spdisplacement was measured from cross-heThe maximum slope of 200 kgf load increase was

lected from the load-displacement curve and used to secalculate compressive modulus.

2. MEASUREMENT PROCEDURE The tes describe 2 and 4. Table 2 ure and corresp ing specim

Measurements Length(mm) Note

3 t procedure was d in table figure

: Measurement proced onden length

① OE 3,600

( 2.2.3 Edgewise bending M 3,000)*

② 2.2.1 Surface image

3,000 ③ Dy E 2.2.2 namic MO

④ odulus Tensile m 2.2.5

⑤ 400 2.2.4 Flatwise 1,bending MOE (1,000)

⑥ Dynamic MOE 1,000

2.2.2

⑦ Compressive modulus 2.2.6

* ( ) : Span length for bending test

Figure 4: Cutting length for each measurement procedure 3 RESULTS AND DISCUSSIONS 3.1 VARIATION OF MOE BY TEST METHODS The average MOE values by different test methods were shown in table 3. However, 3 specimens of Korean Pine

ere broken under edgewise bending load and 2

Korean Larch and Japanese Cypress had higher MOE values and Pitch pine and Japanese Cedar had lower MOE values, respectively. However, due to the sample sizes, it is difficult to define that the MOE values in table 3 were representative

wspecimens of Korean Red Pine and Korean Pine were failed under tensile load because of unexpectedly great latter

knot of ters (figure 5).

values of those species. The

MOE

ucing strength of lumber.

odulus

compressive modulus and edgewise bending MOE showed that the formar had 6% higher than the

and the correlation coefficient (R2) was 0.905 (figu

Table 3: Average MOE of each speci s by lo es (N/mm

s nami ending

Compressive

Japanese Cypress showed higher values and Pitch Pine showed lower values than its density order with other specimens, relatively. The dynamic MOE was the greatest and tensile modulus, flatwise bending MOE, edgewise bending MOE and compressive modulus was followed in order. In the case of dynamic MOE values, the longer specimen (3,000mm) showed 5% lower value than shorter specimen (1,000mm). This might be the energy reducing effect of ultrasonic transmission caused by the length of specimen. The differences of dynamic MOE in long and short specimens of low grade lumber (lowspecimen) were greater than high grade lumber (high MOE specimen) because low grade lumbers had more defects to reduce ultrasonic transmission energy Edgewise bending MOE value was 10% lower than flatwise bending MOE. It is because of the location and size effect of growing characteristics in the edgewise bending which are redAdditionally, shear effect of edgewise specimen were greater than flatwise specimen because of span to depth ratio during bending test. The value of tensile and compressive modulus of Korean Larch and Pitch pine was greater than the results in Shim et al. reported [5], but there was the same tendency which the tensile modulus was about two times greater than compressive modulus. The tendency of mdifferences between tensile and compressive modulus of actual size lumber was because of low compressive modulus due to the grain deviation near defects. The value of bending MOE was nearly the same as the average values of the tensile and compressive modulus. As a lumber resists against bending stress, tensoin and compression stress acts at the same time in the opposite side of lumber. The correlation between average value of tensile and

knot clus re 6).

e ading mod 2)

SpecieDy c B

Tensile 3 1 E e F ,000mm ,000mm dgewis latwise

Korean Red Pine 12,160 12,420 8,160 8,660 11,230 6,130

Korean Larch 13,420 14,000 9,700 9,920 13,010 6,900

Pitch Pine 8,890 9,970 6,590 6,820 8,320 4,620

Korean Pine 10,630 10,890 6,260 8,040 9,270 4,810

Japanese Cedar 8,500 8,810 6,490 7,050 8,800 4,610

Japanese Cypress 13,170 13,790 9,660 10,710 13,280 7,050

Average 11,150 11,680 7,890 8,560 10,810 5,730

(a) Korean pine

(b) Korean red pine

Figure 5: Examples of surface images of specimens dama

ged during tensile test

Figure 6: Relationship between edgewise bending MOE nd the average of tensile and compressive MOE for

the correlation oefficient between estimated and measured edgewise ending MOE was improved to 0.927.

very high.

the

is possible because of high correlation between tensile and compressive modulus

E values. Table 4: Correlation coefficien asuri

am din

Tensile Compressive

3.2 PREDICTION OF TENSILE AND COMPRESSIVE MODULUS

The linear correlations between MOE measurement methods were analized, and the results shown in table 4 and figure 7. It is certain that there were dependent relationships in the MOEs measured by different test methods becuase the coefficients were Especially, the case of including compressive modulus showed the highest correlation coefficients. Generally, the dynamic and static bending MOE were used as input data for predicting mechanical properties of lumber or glulam because it is easy to measure. Many commercial equipments to measure dynamic and static bending MOE have been developed. However, measuring tensile and compressive modulus was not easy, and the measuring equipment of tensile and compressive modulus for structural lumber was not being developed for commercial purposes. Therefore,

aeach specimen When a lumber was under bending load, the neutral axis moved to tension side because of the tensile and compressive modulus difference. To consider this effect, edgewise bending MOE was estimated with tensile and compressive modulus by transformed section method. The result showed that the compressive area was about 57.7% of lumber cross-section and

bending MOE of lumber was suggested in most research results as representative MOE of the lumber species. Based on the results of this study, there were high correlations between tensile and compressive modulus and the other MOE values. Therefore, predicting MOE of engineered wood based on the tensile and compressive modulus c

b and other MO

ts between different MOE me

Dynng metho

Bends

ic g

3,00 m 1, E e F 0m 000mm dgewis latwise

Dynamic 0. 1 3,000mm 1 92 0.827 0.834 0.805 0.876

1,000mm 0.921 1 0. 5 86 0.824 0.806 0.893

Bendin0. 3

g Edgewise 0.827 0.865 1 83 0.841 0.949

Flatwise 0 0.834 0.824 0.833 1 .812 0.878

Tensile 0.805 0.806 0.841 0.812 1 0 .879Compressive 0.876 0.893 0.949 0.878 0.879 1

Figure 7: Linear correlation between MOE measurement methods

Figure 7: Linear correlation between MOE measurement methods (Continue)

eTable 5: Prediction equations of tensile and ssiv

nsile compre MOE based on edgewise b MOE

Com ssive Mending

Te MOE pre OE

A b* ** R2 a b* ** R2

Korean Red Pine 1.674 -2,431 0.711 0.571 1,206 0.961

Korean Larch 1.698 -3 ,465 0.833 0.716 -54 0.782

Pitch Pine 1.399 -903 0.642 0.780 -527 0.678

Korean Pi 1 ne 1.307 1,071 0.926 0.521 ,392 0.749

Japanese Cedar 1.343 85 0.706 0.729 -117 0.838

Japanese Cypress 0.674 6,771 0.610 0.589 1,360 0.934

Total 1.383 -208 0.841 0.712 17 0.951

* a: Gradient, ** b: y-axis intercept, R2: Coefficient of determination The linear regression coefficients for predicting tensile and compressive modulus for each species from

predicted and easured MOE was calculated by equation (2) and

sho on was r each

edgewise MOE of lumber were shown in table 5. However, there is possibility to predict tensile and compressive modulus from flatwise MOE or dynamic MOE. The root mean square error (RMSE) ofm

wn in figure 8. The prediction equaticonstructed from the coefficients in table 4 species basis and all species base values.

fo

specimenofNumberMOEMOE

RMSE measredpredicted

⋅⋅−

= ∑ 2)( (2)

The RMSE of tensile modulus was about 800N/mm2. On the other hand, RMSE of compressive modulus was

latively. The RMSE calculated from all species base value showed greater than the RMSE calculated from each species base value but the differences were not

all species base could be used r predicting tensile and compressive modulus of

lts between predicted

predict tensile and

latwise MOE could be used to predict tensile and compressive modulus for estimate glulam MOE because of its significant correlation between those MOE and tensile and compressive modulus.

lower than 400N/mm2. The RMSE of high MOE species such as Korean Larch had higher value but low MOE species such as Korean Pine had low RMSE value,

significant. Therefore, considering the applicability, and equation constructed fromfolumber. The comparison resumodulus from all species base and measured modulus were shown in figure 9. CONCLUSIONS 4

This study was carried out tocompressive modulus from dynamic or static MOE of major softwood lumber in Korea. The conclusions are as followed: A. The measured MOE of the same specimens by

various tes methods were slightly different. Especially, the tensile modulus was two times grater than the compressive modulus at the same specimen.

B. The dynamic MOE or static edgewise and f

re

(a) Tensile MOE (b) Compressive MOE Figure 8: RMSE’s of predicted MOE for each species (N/mm2). Prediction equations derivated for each species and for total specimen were compared

(a) Tensile MOE (b) Compressive MOE

Figure 9: Prediction accuracy of tensile and compressive MOE based on edgewise bending MOE

REFERENCES [1] S. R. Shim, and H. Yeo: Visual log grading and

evaluation of lamina yield for manufacturing structural glued laminated timber of pitch pine. Journal of the Korean Wood Science and Technology, 32(2):90-95, 2004.

[2] S. R. Shim, H. Yeo, and K. B. Shim: Evaluation of shear bond strength and adhesive bond durability of mixed species structural glued laminated timber. Journal of the Korean Wood Science and Technology, 33(1):87-96, 2005.

[3] K. M. Kim, K. B. Shim, J. S. Park, W. S. Kim, J. A. Lim, and H. Yeo: Development of pitch pine glued laminated timber for structural use – Improvement of bending capacity of pitch pine glulam by using domestic larch laminars. Journal of the Korean Wood Science and Technology, 35(6):13-22, 2007.

[4] K. M. Kim, S. R. Shim, K. B. Shim, J. S. Park, W. S. Kim, B. N. Kim, and H. Yeo: Development of structural glued laminated timber with domestic cedar. Journal of the Korean Wood Science and Technology, 37(3):184-191, 2009.

[5] K. B. Shim, K. M. Kim, and J. S. Park: Improvenent of prediction accuracy of glulam modulus of elasticity by considering neutral axis shift in bending. Wood and Fiber Science, 41(1):90-96, 2009.

[6] B. N. Kim, H. W. Lee, and K. M. Kim: The development of image processing system using area camera for feeding lumber. Journal of the Korean Wood Science and Technology, 37(1):37-47, 2009.

[7] B. N. Kim, K. M. Kim, K. B. Shim, H. W. Lee, and S. R. Shim. The verification of image merging for lumber scanning system. Journal of the Korean Wood Science and Technology, 37(6):556-565, 2009.