Mechanical properties and strength grading of Norway spruce timber of different origins

Mechanical properties and strength grading of Norway spruce timber of different origins Chrestin, Hauke 1 ABSTRACT This paper presents the results of a research project aimed at examining whether samples of Swedish grown sawn spruce timber of different geographical origins rendered significant differences in mechanical properties, relations between material properties, and strength grading yield. Individual growing conditions predetermined by the timber origins were expected to exert a visible influence on different timber properties such as annual ring width, proportion of latewood and knot characteristics. These characteristics were, in turn, expected to exert an influence on density, modulus of elasticity and the ultimate bending strength of the timber. The timber species examined was Norway spruce (Picea abies) with sawn dimensions 50x150 mm². Approximately 2,900 pieces of structural timber were sampled at seven different regions, three in southern, one in central and two in northern Sweden. The timber was machine strength graded and every tenth piece was destructively tested. The results from the destructive tests, and the corresponding machine grading were used as input in a simulation of bending strength and modulus of elasticity for the total population. The results indicate that the mean values of machine-determined flatwise modulus of elasticity, edgewise modulus of elasticity and edgewise bending strength are significantly different for some regions. Timber from the mountainous regions in northern Sweden has lower values of the mechanical properties, while timber from central Sweden and some parts of southern Sweden has higher values. The relationships between the mechanical properties differ significantly when timber from northern, central and southern Sweden is compared. This, for instance, applies to the relation between bending strength and machine-determined modulus of elasticity, which is the basis for the settings to be used in grading machines in Sweden. Currently, the same setting values are used regardless of timber origin. If individual settings for northern, central and southern Sweden or an output controlled grading system were used, the result would be an improved yield especially in high strength classes for timber from central and certain parts of the southern Sweden. In other regions, the yield would be reduced, but only for the higher strength classes. INTRODUCTION The setting values for machine strength grading of sawn timber in bending type machines currently applied in Sweden are the result of a joint British-Scandinavian investigation during the 1970s (BRUNDIN 1981). The material for this investigation had been structural pine and spruce timber collected from sawmills in northern, central and southern Sweden. The investigation resulted in general formulas to be applied in machine strength grading of both timber species originating from all over Sweden. A further study (JOHANSSON, BRUNDIN AND GRUBER 1992) concluded that the same settings could probably also be applied to German timber. However, physical and elasto-mechanical properties of sawn spruce timber from different locations in Sweden may not be identical, owing to varying structural wood characteristics influenced by different environmental conditions (see e.g. THÖRNQVIST 1992). More investigations dealing with Swedish sawn spruce timber were carried out during the 1990s. The question came up, as to whether variations in strength and stiffness between timber from different regions in Sweden were really so small that they could be neglected in an advanced machine strength grading. In late 1995, in co-operation between the Swedish National Testing and Research Institute (SP) and the University of Hamburg, a project was launched to investigate whether carefully performed strength grading of timber from different locations In Sweden rendered 1 Ph.D. candidate, School of Industrial Engineering, Växjö University, S-351 95 Växjö, SWEDEN

significant differences in the yield of different strength classes (CHRESTIN 1996). The primary objective of this investigation was to experimentally determine possible differences in mechanical properties of coniferous sawn timber depending on the origin of the raw material in Sweden and to compare their relationships. The investigations were based on Norway spruce timber since most of the structural timber produced in Sweden come from this timber species. To the best of the authors knowledge and except for the study presented by BRUNDIN (1981), no previous study comparing timber from several different regions of Sweden has been conducted. TEST MATERIAL The tested material consisted of about 2,900 planks of 150 by 50 mm 2 Norway spruce timber (Picea abies L. Karst). Basing the investigations on timber that came from different altitudes and extremely different geographical latitudes was expected to reveal the variations in wood characteristics probably caused by geographical origin of the raw material. Typical test material for each region was sampled from one sawmill in each of seven arbitrarily selected, geographically distinct regions of Sweden. A sample of about 400 planks of saw falling quality was taken directly from the normal production output on one occasion. One could assume all quality classes to be represented in a frequency typical of the production output of the particular sawmill. Prior to testing, all timber was kiln-dried and planed to final dimensions 145 by 45 mm². In the further course of the investigation, a sub-sample of about 40 test specimens was systematically selected from each sample. Table 1 gives an overview of the material. Table 1: Origin and size of the seven samples Geographical Altitude 1) of Size of Sawmill Swedish province latitude log intake area Sample Sub-sample A Mountainous southern Lapland 64 40' N 200 650 m 420 40 B Coastal Västerbotten 64 20' N 0 250 m 420 42 C Central Dalarna 60 40' N 150 650 m 399 40 D North eastern Småland 58 00' N 75 250 m 398 40 E North western Småland 57 40' N 150 400 m 424 41 F Northern Halland/ southern Västergötland 57 15' N 0 200 m 404 40 G Southern Småland 57 00' N 100 250 m 413 41 Total 2,878 284 1) Altitude above sea level DETERMINATION OF TIMBER PROPERTIES The flatwise bending stiffness profile along each plank was determined through non-destructive testing in a Cook Bolinders SG AF bending type strength grading machine. While testing, length and mass of each piece were determined to calculate the density. The strength grading machine measured the load necessary to give the timber a pre-set deflection every 10 mm along each plank with the exception of the first and the final 450 mm owing to the machine design. From these load readings, the machine determined flatwise modulus of elasticity (E cook ) was calculated as shown for example in BOSTRÖM (1994). The lowest load reading gave the lowest E cook over the entire (measured) length and was recorded as E cook,min. However, in order to determine the position of the weakest cross section, i.e. the critical section in which failure in the edgewise bending test was expected to occur, the lowest E cook in the testable range (E cook,test ) had to be calculated as well. The testable range depended on the test set-up given in EN 408 and excluded the outer 1305 mm (9 times the depth) of each plank. This means, that in several cases the bending strength of the weakest cross section according to Cook Bolinder could not be determined, but only the bending strength of the second and sometimes even of the third weakest cross section. Following 3 to 5 weeks of conditioning to about 12% moisture content, edgewise modulus of elasticity and bending strength of each specimen in the sub-samples were determined in 4-point-bending tests according to EN 408. After testing to failure, actual moisture content and density at the location of failure were determined. The measured timber properties were adjusted to be valid for 12% moisture content.

NON-LINEAR REGRESSION ANALYSIS The relationships between modulus of elasticity and bending strength were obtained be means of a non-linear regression analysis with the general model Y = a X b. The following basic relations were established: Edgewise modulus of elasticity (E m ) versus machine determined flatwise modulus of elasticity (E cook ) Bending strength (f m ) versus edgewise modulus of elasticity (E m ) Bending strength (f m ) versus flatwise modulus of elasticity (E cook ) Choosing the equation model as Y = a X b had several advantages. The course of the relations was very close to linearity in the observed range, while the relations reached the origin of the co-ordinate system. This reflected the expected behaviour in the relationships between the measured properties. After the equation constants 'a' and 'b' had been determined for each individual sample, a common exponent for all samples was chosen in each of the three relationships. This could be done without any significant worsening of the coefficient of determination. The relationships could then easily be compared because the equations for each relationship formed a number of relations with different slopes. The standard errors of the estimate (s Y.X) were calculated for each sub-sample together with the regression equations. Further, the coefficients of variation (COV) of the data along the regression curve were calculated as s Y.X divided by the mean of the dependent variable. SIMULATION OF EDGEWISE MODULUS OF ELASTICITY AND BENDING STRENGTH Strength data of about 40 specimens from each of the seven samples were not sufficient to obtain setting values for several strength classes. Thus, the edgewise modulus of elasticity and bending strength for the entire samples were simulated based on the measured E cook,min values together with the calculated regression equations for the samples. The applied procedure assumes the E cook data and the residuals of the regression curves to be normally, i.e. Gauss, distributed. This assumption was verified in a preliminary statistical analysis of the distribution. The edgewise modulus of elasticity was simulated using the machine determined modulus of elasticity as input. The bending strength was simulated using the simulated values on edgewise modulus of elasticity as input. This method was chosen because of (a) the stronger relationship (higher R 2 value) between E m and f m and (b) because this follows the way bending strength is determined in machine strength grading in the Swedish industry. The relation between the simulated bending strength and machine determined modulus of elasticity served as control. Two different relations were used in the simulation, see Equation [1], one based on the coefficient of variation used when the independent variable was less than the mean, and one based on the standard deviation of the estimate used when the independent variable was greater or equal to the mean. Figure 1 illustrates how the model fits the actually measured data. b b r a X COV if X < X Y = a X + Equation [1] sim r sy. X if X X where Y sim is the simulated value X is the independent variable on which the simulation is based a, b are the equation constants given in the individual regression equations r is a normally distributed random variable with µ=0 and σ=1 that is individual for each X COV is the coefficient of variation as described above and is the standard error of the estimate s Y.X

100.0 80.0 5th & 95th perc. std.err. of est. 5th & 95th perc. COV mean: E cook & f m 60.0 f m [N/mm²] 40.0 20.0 0.0 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 E cook [N/mm²] Figure 1: Illustration of the theoretical approach to the applied model. The data presented are the 284 actually measured values of all seven samples. GRADING PROCEDURE The European standard EN 338 defines strength classes and gives the characteristic bending strength, edgewise modulus of elasticity and density for each class according to Table 2. Table 2: Characteristic values for different strength classes of coniferous sawn timber according to EN 338. C18 C24 C30 C40 Bending strength f m,k [N/mm²] 18 24 30 40 Modulus of elasticity parallel E 0,mean [N/mm²] 9,000 11,000 12,000 14,000 Density ρ k [kg/m³] 320 350 380 420 Setting values were obtained in a trial and error process. In the process the highest grade was always selected first, then the second highest, and so on. The steps in the process used was as follows: 1. Decide which strength class to grade. Begin with the highest strength class. 2. Rank the sample according to E cook in descending order. 3. Select a group from the top of the ranked sample, as large as possible and with a mean edgewise modulus of elasticity equal to or greater than the required E 0,mean for the strength class to be graded. 4. Determine the 5 th -percentile bending strength value for the selected group. 5. If the 5 th -percentile bending strength does not fulfil the requirement for the strength class, continue with point 6. If the 5 th -percentile bending strength fulfils the requirement, go to point 7. 6. Remove specimens, one at the time, beginning with the lowest E cook -values until both mean modulus of elasticity and 5 th -percentile bending strength fulfil the requirement for the strength class. 7. The specimens remaining in the selected group, which fulfil the requirements of bending strength and modulus of elasticity, are assigned to the grade and removed from the total sample. 8. The specimens remaining in the sample are used for grading into the next, lower, strength class. Return to point 1. DESCRIPTIVE STATISTICS Table 3 presents the results obtained from the determination of mechanical properties in the bending machine and the bending tests. Moreover, it presents the sample mean values of all three properties obtained by means of regression estimation as mentioned above as well as the results of the simulation. Please note that the measured values presented under 'Bending tests' in many cases refer to the second or even third weakest cross section (E cook,test ) and may therefore be higher than the simulations which were based on the lowest flatwise modulus of elasticity value (E cook,min ).

Table 3: Mechanical properties of samples and sub-samples; the table presents in each column the arithmetic mean value (left), the absolute distance of upper and lower 95% confidence limit from the mean (centre), and the coefficient of variation (right). Saw- N 1) E cook,min [N/mm²] E m [N/mm²] f m [N/mm²] mill Bending tests Simulation Bending tests Simulation 40 9600 442 14.4% 10610 569 16.8% 10600 508 15.0% 43.7 3.8 26.9% 44.8 3.3 23.3% A 420 9360 142 15.9% 9340 198 22.1% 38.6 1.2 32.4% 42 10430 578 17.8% 11650 704 19.4% 11670 639 17.6% 47.8 4.2 27.9% 48.7 3.9 25.4% B 420 10220 146 14.9% 10510 203 20.1% 43.5 1.2 29.0% 40 11390 516 14.2% 13220 713 16.9% 13020 686 16.5% 51.6 4.3 26.1% 50.3 3.2 19.8% C 399 11000 177 16.4% 11930 226 19.2% 45.2 1.2 27.5% 40 10210 770 23.6% 11920 1097 28.8% 11970 1006 26.3% 43.7 4.7 33.3% 43.0 4.9 35.5% D 398 10810 186 17.5% 11720 267 23.1% 42.7 1.2 28.5% 41 11190 595 16.9% 12280 782 20.2% 12370 834 21.4% 44.0 4.2 30.6% 46.7 3.5 24.1% E 424 11060 165 15.6% 11400 232 21.3% 41.1 1.3 33.3% 40 10730 489 14.2% 12220 806 20.6% 11880 699 18.4% 43.1 4.0 29.0% 42.5 3.4 25.3% F 404 10670 152 14.5% 11330 213 19.3% 39.5 1.1 28.5% 41 10180 768 23.9% 11870 1069 28.5% 11700 1058 28.6% 44.8 5.2 36.6% 44.9 4.6 32.4% G 413 11020 155 14.5% 12180 225 19.1% 45.6 1.2 26.4% 284 10530 231 18.8% 11960 317 22.7% 11890 301 21.7% 45.5 1.6 30.5% 45.9 1.4 27.0% All 2878 10580 64 16.6% 11190 91 22.2% 42.3 0.5 29.9% 1) For each sawmill, the sub-sample means are presented in the first and the sample means in the second row. When examining the results obtained from the bending tests, the following conclusions can be drawn: The mean E cook,min is lower for samples A and B, especially sample A, than for the other samples which have roughly the same mean E cook,min. Sample A has a low modulus of elasticity, E m. Sample C has a higher modulus of elasticity than the other samples, which have about the same mean E m. Sample C has the highest bending strength, closely followed by sample B. The remaining samples have about the same bending strength. The following conclusions can be drawn from the simulations: The bending strength and the modulus of elasticity obtained through simulations are lower than values obtained by testing. Sample G is the only exception. The simulated edgewise modulus of elasticity is lowest for sample A and highest for sample G. The bending strength is lowest for sample A and F, and highest for sample C and G. RESULTS OF NON-LINEAR REGRESSION ANALYSIS It was observed that the calculated non-linear relationships between edgewise modulus of elasticity (E m ) and machinedetermined flatwise modulus of elasticity (E cook ) of the test specimens varied between timber samples from different regions in Sweden. Generally, the edgewise stiffness of southern Swedish timber was higher at a given flatwise stiffness than that of timber from northern Sweden although the observed deviations were relatively small. The deviation of the individual constants ( a ) in the relations between f m and the corresponding E m values of the sub-samples were more pronounced than for the relation between E cook and E m. Samples A, B, and C had a steeper slope than samples D, E and F, and sample G was in between. Consequently, it was decided to assume individual f m vs. E m regression functions for the timber from the different samples. The slopes for samples A, B, C and G in the relationships between f m and the corresponding E cook values of the test specimens are steeper than for samples D, E, and F. This means, that at a given level of flatwise modulus of elasticity the timber from sawmills A, B, C and G rendered higher bending strength values than the timber from sawmills D, E and F. GRADING

Prior to any strength grading procedures, the characteristic values of each simulated timber sample were determined and each sample was assigned as a whole to the best fitting strength class. This strength class varied from C18 for timber coming from the North to C27 for timber coming from the southern interior of Sweden. All 2,878 specimens together fulfilled the requirements for C22 and 99.5% of the timber (2,864 specimens) fulfilled the requirements for C24. Consequently, each simulated sample was graded in two strength class combinations: C18, C30 and better, and C24, C40 and better. Two kinds of setting values were also applied, a common one for all seven samples in each grading, and an individual setting value for each sample. Both types of setting values were obtained from the data rather than calculated from the relationships of the mechanical properties. Thus, the grading is referred to as optimised grading. The result of grading the seven samples in strength classes C18, C30, and better is presented in Table 4. The timber was graded applying both common and individual setting values. The following conclusions can be drawn from the results: Table 4: Setting values, yield and characteristic values of the simulated samples graded into strength classes C18, C30 and better; setting value, f m,k and E 0,mean in [N/mm²], ρ k in [kg/m³]. Common setting Individual setting Sample Value Yield [%] f m,k 1) E 0,mean 1) ρ k Value Yield [%] f m,k 1) E 0,mean 1) ρ k A 9,660 44 29.8 11,000 391 10,540 21 35.5 12,000 398 B 9,660 64 32.7 11,600 402 10,190 51 34.3 12,000 409 C 9,660 77 32.7 12,800 412 8,540 91 30.0 12,300 402 D 9,660 75 32.8 12,800 409 9,100 83 30.0 12,500 404 E 9,660 80 27.0 12,100 417 11,460 41 30.7 13,300 438 F 9,660 76 27.8 12,200 405 10,560 56 30.2 12,700 414 G 9,660 82 33.2 12,900 425 8,110 96 30.0 12,400 414 All 9,660 71 30.0 12,300 406 C18 A 7,940 40 22.0 8,620 378 7,660 67 22.0 9,000 380 B 7,940 30 23.7 8,960 374 5,700 48 22.3 9,010 377 C 7,940 19 24.6 9,190 374 0 D 7,940 18 25.9 9,170 382 8,510 6 27.7 9,000 382 E 7,940 17 19.7 9,030 372 < 5,990 59 19.7 10,090 391 F 7,940 20 19.4 9,050 368 < 6,000 44 19.5 9,580 377 G 7,940 15 23.3 9,560 382 0 All 7,940 23 22.0 9,000 374 Rejects A 16 14.7 6550 374 12 14.6 6,240 373 B 6 11.2 6,420 370 1 10.6 4,250 378 C 4 18.4 7,500 344 9 20.4 8,070 362 D 7 15.5 6,930 337 11 18.5 7,320 346 E 3 18.2 7,330 350 0 F 4 17.2 7,170 343 0 G 3 14.2 6,600 314 4 14.2 6,900 316 All 6 15.5 6,790 351 1) Cells are shaded where the requirements of EN 338 were not matched. C30 Samples A, B, E and F do not fulfil the requirements for strength class C30 when common setting values are used. Samples A and B do not fulfil the requirements for strength class C18 when common setting values are used. Using individual setting values for strength class C30 increases the yield for samples C and G by more than 15%. With individual setting values the yield in strength class C30 varies from 21% for sample A to 96% for sample G. For strength class C30 modulus of elasticity is the grade determining property for samples A and B, while bending strength is determining for the remaining samples. The result of grading the seven samples in strength classes C24, C40, and better is presented in Table 5. The timber was graded applying both common and individual setting values. The following conclusions can be drawn from the results:

Table 5: Setting values, yield and characteristic values of the simulated samples graded into strength classes C24, C40 and better; setting value, f m,k and E 0,mean in [N/mm²], ρ k in [kg/m³]. Common setting Individual setting Sample Value Yield [%] f m,k 1) E 0,mean 1) ρ k Value Yield [%] f m,k E 0,mean ρ k A 12,600 2 45.2 13,900 428 0 B 12,600 5 41.8 14,300 450 12,400 7 41.8 14,000 445 C 12,600 17 47.7 15,000 439 11,700 38 41.4 14,100 433 D 12,600 16 49.7 15,900 463 12,300 21 41.0 15,400 453 E 12,600 20 34.5 14,400 462 13,800 6 41.5 15,700 488 F 12,600 11 36.6 14,600 451 13,500 3 44.9 15,800 464 G 12,600 14 47.8 15,200 471 11,400 42 40.1 14,000 447 All 12,600 12 40.9 15,000 452 C24 A 8,030 81 24.5 9,800 384 9,620 45 29.8 11,000 392 B 8,030 88 27.3 10,600 390 9,160 68 29.0 11,000 369 C 8,030 79 28.3 11,500 398 8,600 53 28.6 11,000 392 D 8,030 77 28.2 11,300 402 7,600 75 27.7 11,000 397 E 8,030 77 22.4 10,800 400 8,640 86 24.6 11,400 406 F 8,030 85 23.0 11,100 392 8,150 91 24.8 11,400 393 G 8,030 82 29.6 11,900 410 7,730 55 29.1 11,000 400 All 8,030 81 26.2 11,000 392 Rejects A 17 14.6 6,590 373 55 18.4 7,950 376 B 7 11.2 6,520 368 25 19.3 8,090 372 C 4 18.4 7,620 348 9 20.4 8,070 363 D 7 15.5 6,930 337 4 14.4 6,360 324 E 3 18.2 7,320 353 8 18.7 7,940 361 F 4 17.2 7,260 346 6 17.9 7,410 348 G 4 14.2 6,900 316 3 14.2 6,270 337 All 7 14.7 6,870 352 1) Cells are shaded where the requirements of EN 338 were not matched. C40 Samples A, E and F do not fulfil the requirements for strength class C40 when common setting values are used. Samples A, B, E and F do not fulfil the requirements for strength class C18 when common setting values are used. Using individual setting values for strength class C40 increases the yield for samples B, C, D and G. The yield increases by more than 100% for sample C, and by 200% for sample G. With individual setting values the yield in strength class C40 varies from 0% for sample A to 42% for sample G. Bending strength is the grade determining property for strength class C40. For strength class C24 modulus of elasticity is the grade determining property for samples A, B, C, D and G, while bending strength is determining for samples E and F. DISCUSSION AND CONCLUSIONS The material sampled in this study gives a good impression of the wide variations in mechanical properties of timber of different origins in Sweden. Sampling the timber directly at the sawmills rendered samples of saw-falling quality, which could be regarded as typical of the individual sawmills. Subsequent investigations on material from sawmills B and C confirmed that the sampled material had been representative for the individual sawmills. Drawing systematically every tenth piece from these samples as test specimens for closer investigations gave sub-samples that represented the samples with good accuracy in terms of density and lowest flatwise modulus of elasticity. The mean values for E m and f m obtained from the sub-samples in both bending tests and simulations are somewhat higher than the corresponding sample means. This is to be explained by the fact that due to the set-up of the bending test in several cases the weakest cross section could not be tested, but only the second or third weakest. However, the similarity

of the tested and simulated sub-samples served as validation for the model and subsequently the model was applied in simulating the entire samples for grading based on the lowest flatwise MOE values. The sub-samples mainly served the purpose to establish the best possible relationships as input for the model. The relationship between bending strength and modulus of elasticity differed significantly when timber from different regions of Sweden was compared. As a result, for the timber from northern Sweden, edgewise modulus of elasticity became the determining property in assigning the timber to a certain strength class. This timber matched the strength requirements without problems. However, for some timber samples from southern Sweden the determining factor was the bending strength. Applying common setting values may cause that the timber, which was assigned to high strength classes in some regions not to match the required characteristic values. These setting values may also be far too conservative for some sawmills harvesting raw material with especially high strength and stiffness properties. The demand for a grading system makes it evident differences in raw material qualities must better be taken into account. The following conclusions can be drawn from this study: Norway spruce timber from different regions in Sweden rendered significant differences in the actual values for machine-determined flatwise modulus of elasticity, edgewise modulus of elasticity, and edgewise bending strength. There are differences between the samples with regard to the regression functions describing the relations between bending strength and modulus of elasticity. The application of individual setting values for different parts of Sweden or even for individual sawmills may be expected to improve the yield in high strength classes for timber coming from central and parts of the southern Sweden. Changing from a machine controlled grading system to an output controlled system seems to be an appropriate alternative for certain sawmills in Sweden that want to increase their yield of high strength timber. REFERENCES BOSTRÖM, L. (1994): Machine strength grading.- Comparison of four different systems.- The Swedish National Testing and Research Institute, SP-Report 1994: 49 BOSTRÖM, L. (1994): Machine strength grading the influence of moisture content.- IUFRO S5.02 Timber Engineering Conference, Sydney, Australia BRUNDIN, J. (1981): Maschinen-Festigkeitssortierung.- Zusammenhang zwischen Festigkeit bei Biegung auf Hochkante und Biegewiderstand für schwedisches Kiefern- und Fichtenholz. Prinzipien für Maschinenprogrammierung. - [Machine strength-grading. Relation between edgewise bending strength and bending stiffness for Swedish red- and whitewood. Principles for machine programming].- German translation of the STFI-Report Series A No. 543 by Hans-Heinrich Fickler and Eugen Jutsuk (1985) CHRESTIN, H. (1996): Elasto-mechanical properties and machine strength-grading of sawn spruce timber from different locations in Sweden.- Master's thesis (Diplom degree) in Wood Science and Technology.- University of Hamburg JOHANSSON, C.-J., BRUNDIN, J., AND GRUBER, R. (1992): Stress grading of Swedish and German timber.- Swedish National Testing and Research Institute, SP-Report 1992:23 THÖRNQVIST, T. (1992): Properties of timber from Southern Sweden.- Södra Timber, Södra Paper 1/93