Abstract
Tensile, edgewise, and flatwise bending behaviors of visually graded fir (Abies nordmanniana subsp. bornmuelleriana) boards were investigated through destructive and non-destructive testing to evaluate their mechanical performance and grading accuracy. A total of 724 specimens were prepared and tested in accordance with EN 408 standards. Knot diameter ratios (narrow, mean, and parallel) were used to establish three visual grading methods. Vibration-based (PLG, Hitman) and time of flight (ToF) (Microsecond Timer, Ultrasonic Timer, and Sylvatest Duo) techniques were used for non-destructive evaluation (NDE), along with screw withdrawal tests. The results showed that although the vibration method had lower dynamic modulus of elasticity (MOEd) values than the ToF method, it provided stronger correlations with tensile and bending properties. The mean and parallel knot diameter ratios provided more reliable grading results than the narrow ratio. Tensile strength was more affected by defects than bending strength, and the flatwise bending method consistently produced the highest strength values. The adjustment from global to local MOE reduced modulus values below 9000 MPa, resulting in lower strength class assignments. Overall, the vibration-based NDE method proved the most effective for predicting lumber quality, and the flatwise bending test emerged as a viable alternative to tension and edge bending methods for structural grading.
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Tensile, Edgewise Bending, Flatwise Bending, and Non-Destructive Evaluations of Visually Graded Fir Boards
Fatih Kurul 
*
Tensile, edgewise, and flatwise bending behaviors of visually graded fir (Abies nordmanniana subsp. bornmuelleriana) boards were investigated through destructive and non-destructive testing to evaluate their mechanical performance and grading accuracy. A total of 724 specimens were prepared and tested in accordance with EN 408 standards. Knot diameter ratios (narrow, mean, and parallel) were used to establish three visual grading methods. Vibration-based (PLG, Hitman) and time of flight (ToF) (Microsecond Timer, Ultrasonic Timer, and Sylvatest Duo) techniques were used for non-destructive evaluation (NDE), along with screw withdrawal tests. The results showed that although the vibration method had lower dynamic modulus of elasticity (MOEd) values than the ToF method, it provided stronger correlations with tensile and bending properties. The mean and parallel knot diameter ratios provided more reliable grading results than the narrow ratio. Tensile strength was more affected by defects than bending strength, and the flatwise bending method consistently produced the highest strength values. The adjustment from global to local MOE reduced modulus values below 9000 MPa, resulting in lower strength class assignments. Overall, the vibration-based NDE method proved the most effective for predicting lumber quality, and the flatwise bending test emerged as a viable alternative to tension and edge bending methods for structural grading.
DOI: 10.15376/biores.21.1.1364-1387
Keywords: Knot diameter ratio; Visual grading; Fir; Vibration; Time of flight; Screw withdrawal
Contact information: Istanbul University-Cerrahpaşa Faculty of Forestry, Department of Wood Mechanics and Technology, Istanbul, Türkiye; *Corresponding author: fatihkurul@iuc.edu.tr
INTRODUCTION
Wood has long been recognized as one of the most sustainable and versatile materials in structural engineering applications. Its renewability, favorable density/strength ratio, and natural aesthetic appeal have made it a building material used for centuries (Ridley-Ellis et al. 2016; Kurul and As 2024). Today, wood, which remains essential in modern engineering and architecture, is gaining attention as an alternative to steel and concrete as sustainability becomes a key issue in construction. Beyond its positive aspects, wood is also a complex engineering material that requires careful attention due to its wide variation in physical and mechanical properties, driven by its natural structure and inherent imperfections (Kurul and As 2024; Kurul et al. 2024). Therefore, intensive research is being conducted on its mechanical behavior and performance under various loading conditions (Stapel and van de Kuilen 2014; Ridley-Ellis et al. 2016; Kurul et al. 2025).
In Europe, a series of standards published by the European Committee for Standardization (CEN) is used to ensure quality control and form the basis for design calculations in the use of wood for structural purposes (Ridley-Ellis et al. 2016). These standards form the basis for visual and mechanical strength grading of wood structural materials, enabling their safe and economical use in construction. The application of grading systems for wood structural materials is essential not only for quality control but also for the reliability of engineering calculations (Steiger and Arnold 2009; Ridley-Ellis et al. 2016; Kurul and As 2024). The standard EN 1995-1-1 (2023) (Eurocode 5) stipulates that the strength values of wood used in structural system designs should be determined according to the classes specified in EN 338 (2020). The EN 338 (2020) standard includes three systems: “C and D” classes obtained from edgewise bending tests, and “T” classes obtained from tensile tests. While structural grading in Europe is primarily based on edgewise bending tests, tensile properties are equally important, especially for elements such as glulam lamellas (Gil-Moreno et al. 2022). Countries participate in this system by subjecting tree species to visual or machine strength classification, and the results are published in the EN 1912 (2024) standard.
Visual grading is a traditional quality assessment method based on measuring the physical defects of timber, such as the slope of grain, knot diameters, fissures, wane, and resin pockets (Seco et al. 2004; Stapel and van de Kuilen 2013; Stapel and van de Kuilen 2014; Ridley-Ellis et al. 2016; Kurul et al. 2024; Kurul and As 2024; Kurul 2025). While each country has its own visual grading criteria, the EN 14081-1 (2019) standard specifies lower limit values for these defects. All local standards must meet the lower limit values specified in this standard (Steiger and Arnold 2009; Ridley-Ellis et al. 2016). Visual grading methods provide a cost-effective and straightforward assessment. However, their main disadvantage is their reliance on human observation and experience (Brunetti et al. 2016; Kurul and As 2024). Machine grading, performed using non-destructive devices that automatically measure some mechanical and physical properties of wood, is considered a more objective and repeatable method (Steiger and Arnold 2009; Nocetti et al. 2010; Ridley-Ellis et al. 2016; Ravenshorst and van de Kuilen 2016; Kurul and As 2024). This method typically uses parameters, such as stress wave velocity, vibration frequency, or flexural modulus, to estimate the timber’s strength class (Arriaga et al. 2012; Brunetti et al. 2016; Gil-Moreno et al. 2022). The machine classification process, according to European standards, is defined in EN 14081-2 (2018).
Accurately identifying natural defects within wood is important for visual and machine strength grading. The measurement principles for all defects in wood materials intended for structural use are outlined in EN 1309-3 (2018). Knots are among the most critical natural growth defects in wood construction materials and are a key factor directly affecting timber’s mechanical strength (As et al. 2006; Roblot et al. 2010; Guindos and Guaita 2014). Studies have shown that knot ratio, knot diameter, knot area, and location are decisive factors in the impact of knots on wood strength. Furthermore, it has been determined that as the knot diameter increases, the wood’s bending and tensile strengths, as well as the bending and tensile modulus of elasticities, decrease significantly (As et al. 2006; Roblot et al. 2010; Guindos and Guaita 2014; Qu et al. 2020; Lovrić Vranković et al. 2025). Therefore, knot diameter or knot area measurements are among the most important criteria for determining the visual grade of lumber in national visual classification standards.
Many studies conducted in Europe have determined the visual and mechanical strength classes of structural boards, classified using both destructive and non-destructive methods. The majority of these studies have been based on edgewise bending tests (Fink and Kohler 2011; Krajnc et al. 2019; Rais et al. 2021; Kurul et al. 2024; Kurul 2025; Lovrić Vranković et al. 2025). However, few studies have simultaneously examined the tensile, edgewise, and flatwise bending strengths of wood using both destructive and non-destructive methods. This study aims to compare and correlate the tensile, edgewise bending, and flatwise bending tests of visually graded fir structural boards using three methods to determine the knot diameter ratio (KDR). With this, the aim is to select the best method by examining three methods for measuring KDR. In this context, C and T classes were separately calculated and compared for each quality class determined by the three KDR methods for three different tests. In addition, the research aimed to correlate destructive tests with non-destructive tests (screw withdrawal, stress wave method using three separate devices, and vibration methods using two separate devices) to estimate wood quality as accurately as possible and to determine which devices were most efficient. Finally, 3-point and 4-point bending tests were performed on small-clear specimens to determine and compare the bending characteristics of the fir species. Thus, it was planned to increase the usage potential of the fir species, which is suitable for use in engineered structural wood materials and an important raw material source for the regional industry, by examining the structural characterization of the most commonly used destructive and non-destructive methods.
EXPERIMENTAL
Wood Specimens
In this study, 80 samples of fir (Abies nordmanniana subsp. bornmuelleriana) with dimensions of 30 x 210 x 4000 mm³ (thickness × width × length) were used. The wood pieces were supplied by a commercial firm and dried to 12% (±2) moisture content. These samples were initially cut as shown in Fig. 1. The evaluations included a tensile test (A1-B2), an edgewise bending test (A2-B1), a flatwise bending test (C1-C2), and 3- and 4-point small-clear bending test samples (D1-D2-D3); a total of 724 test samples were prepared (Fig. 2). The moisture content of all samples was then measured using an electrical resistance method, as described in EN 13183-2 (2002) (Fig. 3). The sample code, group no, test type, dimension, number of samples and average moisture content for each test group are given in Table 1.
Fig. 1. Cutting diagram of fir structural boards
Fig. 2. All test specimens: (A) tension and edgewise bending, (B) flatwise bending, (C) small-clear specimens for 3 and 4-point bending tests
Table 1. Number of Tested Structural Boards for Each Test Type
Fig. 3. Measuring moisture content using electrical resistance method (Hydrometer HT 65, GANN, Germany)
Visual Grading
From the samples prepared according to Table 1, tensile, edgewise, and flatwise bending samples were visually graded. All defects were measured in accordance with EN 1309-3 (2018b). Visual class limit values for defects were determined according to TS 1265 (2012) as a reference for Class 1, Class 2, Class 3, and Reject (R). Table 2 shows the lower limit values for knot, slope of grain, and rate of growth according to the TS 1265 (2012).
Table 2. Lower Limit Values for Knot, Slope of Grain and Rate of Growth for Each Visual Class According to TS 1265 (2012)
Knots were evaluated in three different categories based on knot diameter. These are the narrow knot diameter ratio (NKDR), which refers to the narrow diameter of the knot; the mean knot diameter ratio (MKDR), which refers to the average of the narrow and wide diameters of the knot; and the parallel knot diameter ratio (PKDR), which refers to the diameter parallel to the surface of the knot. Although the limit values in the TS 1265 (2012) are referenced by the PKDR method, the same limit values were used in this study for the other two methods. Knot diameter measurement methods are shown in Fig. 4. The knot diameter ratios for each method are obtained by dividing the reference knot diameters by twice the material width.
Fig. 4. Knot diameter measuring methods
Non-destructive Tests
After the visual grading, all samples underwent non-destructive testing to determine their dynamic modulus of elasticity. The non-destructive tests used longitudinal vibration-based PLG (Portable Lumber Grader, Fakopp, Hungary) and Hitman HM220 (Fibre-gen, New Zealand) devices. Additionally, a Microsecond Timer (Fakopp, Hungary) based on the time-of-flight (ToF) method, an Ultrasonic Timer (Fakopp, Hungary), and a Sylvatest Duo (Concept Bois Structure, Switzerland) that generates ultrasonic sound waves were used. Additionally, screw withdrawal tests were performed on all samples using a Screw Withdrawal Force Meter (Fakopp, Hungary).
Two dynamic moduli of elasticity based on longitudinal vibration were determined. First, the dynamic modulus of elasticity (MOEd,PLG) was calculated for tensile, edgewise, and flatwise bending specimens using the PLG device. The samples were placed on two specially designed supports of the device. A stress wave was generated by striking the end of the board with a hammer. The natural frequency of the material was read using a dynamic microphone and Fast Fourier Transform (FFT) software at the other end of the sample (Fig. 5a). The obtained natural frequency was multiplied by twice the material length to calculate velocity (m/s) for all specimens. Because one of the supports served as a balance, the weight of the specimens was recorded simultaneously. The volume of the specimens was determined by measuring their cross-sectional dimensions, and the density ρ (kg/m3) was calculated by calculating the ratio of mass to volume. Secondly, the dynamic modulus of elasticity (MOEd,HITMAN) was calculated for tensile and edgewise bending specimens using the Hitman HM220 device. The device was pressed against the cross-section of the specimen, and a stress wave was created at the exact location using a hammer (Fig. 5b). The velocity value was read from the device’s display and recorded. The dynamic modulus of elasticity based on longitudinal vibration for all specimens was then calculated using Eq. 1,
(1)
where V (m/s) is the velocity for all test methods, respectively, and ρ (kg/m3) is the full-size sample’s density.
Fig. 5. Longitudinal vibration test setup using PLG (A) and Hitman HM 220 (B) devices
Three dynamic moduli of elasticity based on ToF method were determined. First, the dynamic modulus of elasticity (MOEd,MS) was calculated for all samples using a Microsecond Timer device. The device’s sensors were placed at both ends of the samples, and the start sensor was struck with a hammer to generate a stress wave. The time required for this wave to travel the length of the board between the start and the stop sensors was recorded in microseconds (Fig. 6a). The stress wave velocity was determined using the formula distance/time (m/s). Secondly, the dynamic modulus of elasticity (MOEd,UT) was calculated for all samples using an Ultrasonic Timer device. The device’s sensors were placed at both ends of the samples and secured with wooden wedges. Before each test, ultrasonic gel was applied to the sensors to prevent air gaps from forming between the sensors and the sample. The time required for the generated ultrasonic wave to travel the length of the board between the start and the stop sensors was recorded in microseconds (Fig. 6b). The ultrasonic velocity was determined using the formula m/s. Lastly, the dynamic modulus of elasticity (MOEd,ST) was calculated for all samples using the Sylvatest Duo device. First, 5-mm diameter holes were drilled at the center of each board’s cross-section. Sensors were placed in these holes, and the time required for the ultrasonic wave to travel the length of the board between the start and stop sensors was recorded in microseconds (Fig. 6c). Ultrasonic velocity was determined using the m/s.
Fig. 6. ToF test setup with Microsecond Timer (A), Ultrasonic Timer (B), and Sylvatest Duo (C)
For all three ToF methods, the dynamic modulus of elasticity was calculated according to Eq. 1. In accordance with EN 14081-2 (2018), the dynamic modulus of elasticity for each method was adjusted to a reference moisture content (MC) of 12%.
The final non-destructive test was the screw withdrawal (SW) test. In this test, 4-mm diameter screws were screwed into all samples to a depth of 18 mm. The device handle was then rotated clockwise at a speed of approximately 0.5 m/s. The maximum load was read and recorded in newton (N) from the device (Fig. 7). For tensile and edgewise bending test samples, measurements were taken from two edges and the average was taken. For flatwise bending and small-clear samples, a single measurement was taken.
Fig. 7. Screw withdrawal test setup for all boards (A) and small-clear specimens (B)
Mechanical Tests
After non-destructive tests, tensile (MOET) and bending modulus of elasticity (MOEB,E) tests were conducted on 320 samples coded A1-A2-B1-B2 according to EN 408 (2012). Subsequently, tensile strength (fT) tests were conducted on 160 samples coded A1-B2 according to the same standard, and edgewise bending strength (fm,E) tests were conducted on 160 samples coded A2-B1. Taking the EN 408 (2012) standard as a reference, flatwise bending tests were conducted on 160 samples coded C1-C2, and the modulus of elasticity (MOEB,F) and bending strength (fm,F) were determined. In addition, the modulus of elasticity (MOEB,C3) and bending strength (fM,C3) in 3-point bending were determined on 122 small-clear samples according to ISO 13061-3 (2014) and 13061-4 (2014). Additionally, the modulus of elasticity (MOEB,C4) and bending strength (fM,C4) were determined in 4-point bending on 122 small-clear samples, using EN 408 (2012) as a reference.
Tensile strength and modulus of elasticity in tension parallel to the grain were measured using an 800 kN-capacity horizontal tensile testing machine (BESMAK, Türkiye). The distance between the machine grips was set to 810 mm (9×h), and two LVDTs with 0.001 precision were connected to the gauge at 450 mm (5×h) to measure the deformation (Fig. 8a). In the tensile modulus of elasticity tests, 10000 N was determined as the elastic limit load, and the test speed was adjusted to reach this force within 3 to 5 min.
After determining the tensile modulus of elasticity for all samples, the same sample was subjected to edgewise bending tests to determine the bending modulus of elasticity. Edgewise bending strength and modulus of elasticity in bending tests were performed on a 300 kN capacity bending testing machine (BESMAK, Türkiye). The distance between the supports was set to 1620 mm (18×h), the distance between the loading points to 540 mm (6×h), and the deformation was measured at the midpoint of the sample using a single LVDT with 0.001 precision (Fig. 8b). The elastic limit load for this test was determined as 1200 N. The test speed was adjusted to reach this force within 3 to 5 min. The elastic limit loads for both the tensile and bending modulus of elasticity tests were determined through preliminary tests. The modulus of elasticity in tension parallel to grain and the global modulus of elasticity in edgewise bending were calculated using Eqs. 2 and 3, respectively.