The market share of European beech (Fagus sylvatica L.) wood in the construction sector is low despite an increase in beech stock in Central European Forests in recent years. More efficient sawing techniques, higher lamella grading yields and solving of adhesion challenges may increase the competitiveness of beech glulam and promote its use. The aim of this paper is to revise the lamella grading system in the current German technical approval for beech glulam Z-9.1-679:2019 (DIBt (2019). BS-Holz aus Buche und BS-Holz Buche Hybridträger und zugehörige Bauarten. Allgemeine bauaufsichtliche Zulassung Z-9.1-679:2019. Deutsches Institut für Bautechnik) and to suggest modifications in the lamella grading rules for glulam production allowing higher yields and reliable tensile strength values at the same time. The unique dataset in this study combined different origins of lamellas and covered a wide range of visual, physical and mechanical wood characteristics including a high amount of low quality material. Indicating properties (IPs) for tensile strength, such as knot parameters and dynamic modulus of elasticity, were contrasted with tensile strength and static modulus of elasticity. Beech lamellas, graded by means of Z-9.1-679:2019 (DIBt (2019). BS-Holz aus Buche und BS-Holz Buche Hybridträger und zugehörige Bauarten. Allgemeine bauaufsichtliche Zulassung Z-9.1-679:2019. Deutsches Institut für Bautechnik), did not achieve the tensile strengths required for glulam production in many grading classes and the yield was low. A machine grading approach with dynamic modulus of elasticity as a single grading criterion gave higher yields than the current grading procedure and high reliability for tensile strength prediction with a prediction accuracy of R2 = 0.67.

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The conversion to climate-stable, resilient and productive forests has resulted in an increasing share of mixed stands. Different growth conditions and silvicultural treatments lead to an increased scatter in strength compared to what is expected from monoculture experience. The study (i) quantified the magnitude of variation in strength of European beech timber from stands of different composition and (ii) showed the impact of grading on the characteristic strength value of timber coming from those stands. Strength grading models and machine settings for hardwood tensile classes on over 900 European beech (Fagus sylvatica L.) boards were derived. One model used only the dynamic modulus of elasticity (E_dyn), and a more complex model used a knot value in addition. Afterwards, 407 boards from pure beech stands as well as mixed stands of beech with Douglas fir (Pseudotsuga menziesii (Mirb.) Franco), Norway spruce (Picea abies (L.) Karst.), sessile oak (Quercus petraea (Matt.) Liebl.), and Scots pine (Pinus sylvestris L.) were graded and analyzed for their material properties from tension tests parallel to grain. Although a variance components analysis attributed only 4.2% of the variation to mixture, the ungraded timber showed significant strength differences between the pure and the beech-pine stands (65.2 versus 46.6 MPa). The yield of the material graded to the highest class in a class combination was higher in pure beech stands. The required characteristic strength values were mostly met for boards from the pure stands; while boards from the beech-pine mixed stands hardly ever reached the required values. To reduce strength variation and guarantee reliable timber products, strength grading should consider the various growth situations in forests when sampling material for the derivation of settings.

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In central Europe forests, the share of European beech (Fagus sylvatica L.) trees has been increased in the last decades. Machine strength grading of hardwood is challenging due to a lack of knowledge about strength predictors. However, high strength classes are needed for the utilization as glued and cross laminated timber. We used the information of an industrial scanner on fiber orientations, developed a 3D cluster value (SOG_3D,150,max) for strength assessment and combined the parameter with the dynamic modulus of elasticity (MOE_dyn) to compute an indicating property (IP). A sample of 407 European beech boards passed a multi-sensor scanner to detect wood density, eigenfrequency and slope of grain (SOG). Fiber angle on the surfaces of four board sides was measured using the tracheid effect. The spatial fiber orientation inside the board was modeled for a total of approximately 150,000 points per board meaning 12 points per cm³. Finally, the board section with the largest average local fiber orientation in a window of 150 mm defined the grading parameter SOG_3D,150,max. The prediction of tensile strength via SOG_3D,150,max reached r² between 0.466 and 0.605 depending on the type of data transformation. A combination with the MOE_dyn, the probably most common IP, increased the r² to 0.722 at best. Local grain deviation is a suitable wood parameter for hardwood strength grading. By detecting local defects, the causality between wood strength and tree functioning as well as silvicultural steering may be further understood in future.

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Strength grading is an important step for the production of homogenous and high-quality solid wood material. In particular, for hardwoods, the use of non-visible characteristics is indispensable. Dynamic MOE (E_dyn) is an important parameter widely used for grading of softwoods and applicable to hardwoods as well. There are two common ways to measure E_dyn—ultrasound (US) wave propagation and longitudinal vibration (LV) method. Both methods are used in practice, however, due to the different inherent measurement techniques, the results differ. The current paper analyses the stiffness and strength coefficients of determination for several temperate European hardwood species and emphasizes the differences between the two measurement systems. The performance was analysed with regard to grading techniques, testing modes for the mechanical properties (tension and bending) and wood qualities. For more than 2861 pieces of European ash (Fraxinus excelsior), European beech (Fagus sylvatica), European oak (Quercus spp.) and maple (Acer spp.), the E_dyn was measured using both techniques, and destructive tests (tension and edgewise bending) were applied. The results show that LV has higher coefficient of determination compared to the US E_dyn. The coefficient of determination for both methods and tensile application can be increased by calculating E_dyn with average density. Furthermore, the results support species-independent strength grading of hardwoods. Further research on the effect of different wood qualities and sawing patterns is required.

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Detection of local wood inhomogeneities is important for accurate strength and stiffness prediction. In hardwood specimens, visual characteristics (e.g. knots or fibre deviation) are difficult to detect, either with a visual surface inspection or by the machine. Transversal ultrasound scan (TUS) is a non-destructive evaluation method with high potential for hardwoods. The method relies on differences in ultrasound wave propagation in perpendicular to the grain direction. The aim of this study is to estimate and analyse the capabilities of TUS for defect detection in hardwoods and prediction of mechanical property values. In the current paper, the TUS was applied to the hardwood species European ash (Fraxinus excelsior L.), Norway maple (Acer platanoides L.) and sycamore maple (Acer pseudoplatanus L.). In total, 16 boards of both specimens were completely scanned perpendicular to the grain using a laboratory scanner with dry-coupled transducers. The measurements were processed to 2D scan images of the boards, and image processing routines were applied to further feature extraction, defect detection and grading criteria calculation. In addition, as a reference for each board, all relevant visual characteristics and mechanical properties from the tensile test were measured. Using the TUS global fibre deviation, the size and the position of the knots can be detected. Knottiness correlates to the strength properties similarly or even better compared to the manual knottiness measurement. Between the global fibre angle measured using TUS and measured on the failure pattern, no correlation could be found. The ultrasound modulus of elasticity perpendicular to the grain does not show any meaningful correlation to the elastic properties parallel to the grain. In overall, TUS shows high potential for the strength grading of hardwoods.

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Samples of European beech (Fagus sylvatica) were used for this study. Logs of these samples covered a scatter of mild-to-strong curvatures and the boards of these samples covered strong fiber deviations. This study consists of two separate parts: (1) log reconstruction and optimization of the cutting pattern, and (2) board reconstruction and strength prediction. Information about the internal quality of the logs is missing in this study, as laser scanning has been used for surface reconstruction of logs. Therefore, two separate steps were implemented here. (1) Influence of cutting pattern and board-dimensions on yield were analyzed. For this step, 50 logs were checked. (2) A more advanced numerical method based on the finite element (FE) analysis was developed to improve the accuracy of tensile strength predictions. This step was performed, because visual grading parameters were relatively weak predictors for tensile strength of these samples. In total, 200 beech boards were analyzed in this step. However, due to the geometrical configuration of some knots, the reconstruction and numerical strength prediction of 194 boards out of 200 boards were possible. By performing tensile tests numerically, stress concentration factors (SCFs) were derived, considering the average and maximum stresses around the imperfections. SCFs in combination with the longitudinal stress wave velocity were the numerical identifying parameters (IPs), used in the nonlinear regression model for tensile strength prediction. The influence of the combination of different numerical parameters in the developed non-linear model on improving the quality of the strength prediction was analyzed. For this reason, improvement of coefficient of determination (R²) after adding each parameter to the multiple regression analysis was checked. Performance of the developed numerical method was compared to the typical grading approaches [using knottiness and the dynamic MoE (MoE_dyn)], and it was shown that the coefficient of determination is higher, when using the virtual methods for tensile strength predictions.

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Detection of local wood inhomogeneities is important for accurate strength and stiffness prediction. In hardwood specimens, visual characteristics (e.g. knots or fibre deviation) are difficult to detect, either with a visual surface inspection or by the machine. Transversal ultrasound scan (TUS) is a non-destructive evaluation method with high potential for hardwoods. The method relies on differences in ultrasound wave propagation in perpendicular to the grain direction. The aim of this study is to estimate and analyse the capabilities of TUS for defect detection in hardwoods and prediction of mechanical property values. In the current paper, the TUS was applied to the hardwood species European ash (Fraxinus excelsior) and European maple (Acer sp.). In total, 16 boards of both specimens were completely scanned perpendicular to the grain using a laboratory scanner with drycoupled transducers. The measurements were processed to 2D scan images of the boards, and image processing routines were applied to further feature extraction, defect detection and grading criteria calculation. In addition, as a reference for each board, all relevant visual characteristics and mechanical properties from the tensile test were measured. Using the TUS global fibre orientation, the size and the position of the knots can be detected. Knottiness correlates to the strength properties similarly or even better compared to the manual knottiness measurement. Between the global fibre orientation (measured using TUS and measured on the failure pattern) no correlation could be found. The ultrasound MOE perpendicular to the grain does not show any meaningful correlation to the elastic-properties parallel to the grain. In overall, TUS shows high potential for the strength grading of hardwoods. @en

Wood is a strongly anisotropic and heterogeneous material with natural defects that are affecting the uniform scatter of the fiber patterns. European beech (Fagus sylvatica) is the species, used for this study. The logs of these species have generally complicated shapes with frequent curvatures, which is in contrast to most of the softwood species with relatively straight log shapes. From structural point of view, these species have fewer knots and natural features, but stronger fiber deviations compared to different softwood species that have complicated knot configurations. This study consists of two parts: 1) log reconstruction and optimization of the cutting pattern, and 2) board reconstruction and strength prediction. Due to the complex structural pattern of hardwoods, the visual grading method is a relatively weak strength predictor for these species. The aim of this study is to develop a numerical method based on the finite element (FE)-analysis to provide a better prediction for the tensile strength of the boards. The analysis covers the scatter of 200 beech boards. By resembling the tensile test setup numerically, the stress concentration factors (SCFs) are calculated, considering the average and maximum stresses around the imperfections. SCFs in combination with the longitudinal stress wave velocity are the numerical parameters, used in the nonlinear regression model for tensile strength prediction. The nonlinear model is checked for different combinations of the numerical parameters to estimate and visualize the potential of the virtual predictions. Performance of the novel criteria is compared to the typical grading criteria (knottiness and the dynamic MoE (MoEdyn)), and is shown that the coefficient of determination is higher, when using the virtual methods for tensile strength predictions.@en

Medium dense hardwoods (HWs) show higher tensile strength (TS) values than softwoods (SWs). These advantages cannot be utilised effectively because HW grading is not well developed. The aim of the present paper was to analyse the utilisation potential of European ash (Fraxinus spp.) and maple (Acer spp.) grown in Central Europe, which were graded by different methods. The visual grading characteristics of 869 HW boards were determined and the dynamic modulus of elasticity (MOE _dyn ) and X-ray attenuation (XRA) were measured by an industrial scanner. The specimens were subsequently tested in tension according to EN 408:2010 and according to German visual grading rules show strength values of 28 MPa and 30 MPa, respectively. Machine strength grading and for a combination of manually assessed boards and MOE _dyn give rise to higher strength data. MOE _dyn , in particular, results in lamella data with 62 MPa for ash and 42 MPa for maple. There is good agreement with recently presented HW tensile profiles. Machine grading with a multisensor system allows better strength prediction compared to the MOE _dyn or visual strength grading. Best performance is achieved by a combined grading approach.

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The usage of hardwoods for engineered wood products, such as glulam, requires defined mechanical properties reflecting the actual tensile strength of the material. Currently, the European strength class system EN 338 only covers profiles for hardwoods tested in bending. In this study, the material properties of medium-density hardwoods are analysed with the focus on a total of 3663 European ash (Fraxinus excelsior) and European beech (Fagus sylvatica) specimens tested in different loading modes (tension, compression, bending, and shear). The relationships between the material properties—tensile strength, stiffness, and density—are analysed on grouped data of both graded and ungraded specimens. As a result, a tailored ratio of tensile strength to tensile MOE and density is given, which allows to utilize a higher tensile strength of hardwoods (ft,0,k over 30 N/mm²) compared to softwoods. Furthermore, the relationship of the test values and the derived values is checked. The equations for deriving the compression and bending strength from tensile strength are verified based on available data. For tensile and compression strength perpendicular to the grain and for shear strength of both beech and ash, higher strength values than the ones listed in EN 338 are possible. The relationship between the mechanical properties are combined to tensile strength profiles for hardwoods.@en

Strength grading is an important step for the production of homogenous and high-quality solid wood material. In particular, for hardwoods, the use of non-visible characteristics is indispensable. Dynamic MOE (MOEdyn) is an important parameter widely used for grading of softwoods and applicable to hardwoods as well. There are two common ways to measure MOEdyn – ultrasound (US) wave propagation and longitudinal stress wave (LSW) propagation. Both methods are used in practice, however, due to the different measurement techniques behind them, the results differ. Current paper analyses the stiffness and strength prediction accuracy for several temperate European hardwood specimens and stress the differences between the two measurement systems. The performance was analysed with regard to grading techniques, testing modes for the mechanical properties (tension and bending) and wood qualities. For more than 2861 pieces of European ash (Fraxinus excelsior), European beech (Fagus sylvatica), European oak (Quercus spp.) and maple (Acer spp), the MOEdyn was measured using both techniques, and destructive tests (tension and edgewise bending) were applied. The results show that LSW has higher prediction accuracy compared to the US MOEdyn. The prediction accuracy for both methods and tensile application can be increased by calculating MOEdyn with average density. Furthermore, the results support the species independent strength grading of hardwoods. Further research on the effect of different wood qualities and sawing pattern is required. @en

Background and Objectives: In the near future, in Europe a raised availability of hardwoods is expected. One possible sales market is the building sector, where medium dense European hardwoods could be used as load bearing elements. For the hardwood species beech, oak, and sweet chestnut technical building approvals already allow the production of hardwood glulam. For the species maple and ash this is not possible yet. This paper aims to evaluate the economic feasibility of glulam production from low dimension ash and maple timber from thinnings. Therefore, round wood qualities and the resulting lumber qualities are assessed and final as well as intermediate yields are calculated. Materials and Methods: 81 maple logs and 79 ash logs cut from trees from thinning operations in mixed (beech) forest stands were visually graded, cant sawn, and turned into strength-graded glulam lamellas. The volume yield of each production step was calculated. Results: The highest volume yield losses occur during milling of round wood (around 50%) and "presorting and planning" the dried lumber (56-60%). Strength grading is another key process in the production process. When grading according to DIN 4074-5 (2008), another 40-50% volume loss is reported, while combined visual and machine grading only produces 7-15% rejects. Conclusions: Yield raise potentials were identified especially in the production steps milling, presorting and planning and strength grading.@en

For the production of lamellas for GLT or CLT visually or machine strength graded timber is required. Visual grading allows only for a limited number of classes while reject rates tend to be high. The present paper shows the potential of an evolutionary algorithm NSGA-II optimizing the boundaries of multiple visual grading criteria in a reliable way. The optimization routine is applied to optimize the boundaries of the visual grading criteria given in DIN 4074-1 and DIN 4074-5. Destructive and non-destructive test data of 1515 specimens of Norway spruce (Picea abies) and 704 specimens of European beech (Fagus sylvatia) tested in tension were analysed. The optimization aims at: a) a maximization of the yield; 2) grade timber to the desired strength classes. Using this optimization routine for both beech and spruce higher yield figures compared to the grading according to DIN 4074 can be obtained while the desired characteristic strength are being reached.@en

Generally, for structural timber the main properties are listed in a strength class system. In Europe EN 338 (2016) lists available strength class and their respective characteristic properties. Depending on the product application the bending or the tension properties are of main interest. For glulam lamellas, tension classes are preferred as through tension classes the mechanical properties of glulam can be better predicted. Also, machine grading allows for a better prediction of tensile properties compared to bending properties. So far, tension grades were regulated in EN 14081- 4. Due to the increased demand on glulam products, the grades were recently analysed, and a tensile class table was introduced in EN 338 (2016). The new strength profiles are the preferred option for glulam production. The requirements for softwood glulam are regulated in EN 14080 (2013). So far, no tension classes exist for hardwoods. The EN 338 lists for hardwood specimens only so-called “D” classes based on the bending strength. The other properties, like tension strength, are assigned by the default on the safe side using the equations listed in EN 384. For those classes, the ratio tension strength to bending strength is declared on the safe side 0.6. However as shown by Burger & Glos (1997) for higher quality timber higher ratio can be expected. New tensile classes for hardwoods would allow utilising the properties of hardwoods more efficiently. Whereas the old European standards EN 1194 and EN 14080 (2005) did not regulate species, the most recent version of EN 14080 (2013) is restricted to softwoods only. This means that hardwood glulam producers in Europe face additional costs for obtaining approvals for their products. @en