Wood-steel hybrid (WSH) elements are gaining popularity in the construction industry due to their reduced environmental impact and high load capacity. However, fire resistance remains a crucial challenge for advancing wood as a construction material. The proposed WSH slab consists of a trapezoidal steel profile sandwiched between two laminated veneer lumber (LVL) beech panels. This research aims to numerically predict the fire performance of the proposed WSH slab element by generating heat transfer models that consider convection, radiation, and conduction. The objectives are to predict the temperature profile of the system's components, assess the charring rate of the LVL panels, and validate the results with experimental fire tests. Computed Tomography (CT) scanning was additionally used to detect the material density variation in the remaining LVL layers after fire tests. Simulations reveal that the size and shape of the internal cavity significantly influence heat flow within the system. Analysis of different thicknesses and heights of the steel sheet shows a substantial impact on the charring initiation time of the upper LVL layer. Temperature profiles of the components from numerical analysis exhibit similar behavior to that observed in the experiments. The experimental charring rate averages between 0.88—1.00 mm/min, while the numerical rate averages between 0.95—1.06 mm/min, with a 5–8% average deviation attributed to conduction interaction between LVL and the steel sheet. This variation may also be caused by the definition of generic thermal properties of wood according to EN1995-1-2, which may not accurately represent the behavior of the LVL element under fire.

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Fatigue failures pose significant challenges across various engineering disciplines. Wood, due to its low carbon emissions and high strength-to-weight ratio, has been gaining attention in engineering applications. The fatigue behavior of wood is complex due to its heterogeneous, anisotropic, and viscoelastic nature. This research explores essential insights into the fatigue behavior of wood, with a focus on S–N curves, stress–strain behavior, and failure mechanisms. Due to often varying failure criteria and test settings, direct comparison of S–N curves across different studies can be challenging and inconclusive. A closer look shows that wood in fatigue shows both irreversible and recoverable strain components that are delayed. However, there have been conflicting reports about residual stiffness changes under fatigue loading. Theoretical fatigue life models based on S–N curves or duration of load theory have shown limited applicability. Efforts to develop progressive damage model based on stress–strain behaviors have been challenging and largely unsuccessful due to the lack or inconsistency of data. Understanding the microstructural failure mechanism is crucial in order to build a more trustworthy fatigue modeling technique. Further work is suggested to monitor the microstructural deterioration during high-cycle fatigue loading.@en

This contribution aims for an enhanced numerical representation for strength prediction of timber. This implies a validated elasto-plastic continuum damage model which considers orthotropy and heterogeneity of the material, and represents the ductile behavior under compression and the brittle material behavior under tension dependent on the three-dimensional orthogonal fiber directions. The behavior under compression is captured by Hill (1948) plasticity and an exponential hardening law enhanced by the loading direction dependency. The same model covers also the brittle damaging behavior by means of continuum damage mechanics (CDM). In this study, a separated damage mode (SDM) criterion with simultaneously evolving damage variables is investigated. After the experimental validation of the model for axially loaded clear wood samples, the developed numerical model is implemented to a sawn timber with fiber deviation, where homogenization of the material and simplification to transverse isotropy is not anymore possible. The 3D orthotropic material behavior is experimentally validated for this application example with bi-axial loading and aims for further numerical investigation of wood with heterogeneities as occurring in sawn (hard)wood for its efficient use in engineered wood products such as glued laminated timber.

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When curved glulam beams are subjected to bending, tension perpendicular to grain is introduced. In this work, Monte-Carlo analysis is conducted to study the influence of the annual-ring orientation of individual board on stress concentration in the radial direction. A virtual cutting program is developed which simulates the sawing processes of boards and yields a database of sawn boards, each with a characterized material direction with respect to the pith location. Lamellas are randomly selected from the database to construct curved glulam beams in FE models for Monte-Carlo simulation. Parameters including lumber diameter distribution, taper function, orthotropic elastic properties are considered for four common wood genera in Europe: spruce, pine, larch, and beech. Statistical analysis shows that when the annual-ring effect is considered, the average radial stress in the middle height area of the glulam beams can reach up 1.56 times (even higher on the middle width and height area) compared to the common practice, where wood is usually simplified as transverse isotropic material. Such stress concentration, which can trigger early damage of the structure, indicates an underestimation of stress perpendicular to grain in common practice. Moreover, parameter studies show that the stress redistribution depends not only on the mechanical properties of wood species but also on the width of the board layer.

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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 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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Strength grading of timber boards is an important step before boards can be used as lamellas in glued laminated timber. Grading is generally done visually or by machine, whereby machine grading is the faster and more accurate process. Machine grading gives the best strength prediction when dynamic modulus of elasticity (MoE_dyn) is measured and some kind of knot assessment algorithm is included as well. As access to the actual density for the measurement of MoE_dyn may be impossible in some conditions, this grading method may face some problems in strength prediction. As the strength of a board is related to its natural defects and the ability of the stress waves to propagate around these defects, a virtual method for more accurate strength predictions is developed based on the knot information on the surface. Full 3D reconstruction of the boards, based on knot information on the surfaces of these boards, is an important step in this study. Simulations were run for 450 boards of spruce, Douglas fir, beech, ash and maple, covering a large quality range. Abaqus and Python were used for the numerical simulations. From the numerical simulations, three different stress concentration factors were calculated in the vicinity of the defects. Additionally, a virtual longitudinal stress wave propagation was modeled for the determination of the dynamic modulus of elasticity. The FEM results were used to predict the tensile strength. By means of a regression analysis, the correlation with actual visual and machine readings was validated. An improvement in the strength prediction was observed based on the virtual method, when compared to currently available grading machines. It shows the potential of numerical methods for strength prediction of wood based on visual knot information.

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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

The strength of wooden boards is related to its natural defects and the ability of a stress wave to propagate around them. Anisotropy, heterogeneity, and the strong moisture dependency of wood make it difficult to predict its strength. Covering the ordinary quality range of wood, a numerical simulation model was developed for strength prediction of timber, and 250 boards were numerically simulated. In this study, by virtually reconstructing a three-dimensional (3D) geometrical model of each case based on the surface information of the knots, and by predicting the fiber patterns, the material properties of wood were virtually predicted. Thus, the strength predictions were done solely based on the surface information of the knots. Strength variation in a knot-free board is only dependent on the variation of the actual density of the board. As the actual density of wood may not be available under different environmental conditions for measuring the dynamic modulus of elasticity (MoEdyn), the average density of each set was used as one of the only input parameters for simulations. The resonance kind stress wave propagation and its return were calculated in the reconstructed boards. Numerical results of the finite-element (FE) stress wave analysis were used in a linear regression analysis for prediction of the tensile strength based on the information of the calculated time of the stress wave. The predicted results were benchmarked against the measured values in the laboratory. Performing a multiple regression analysis, the virtual results provided much higher strength predictions than the geometrical parameters available from scanners. However, strong knot interactions in lower-quality boards also affect the strength predictions. This study provides a comprehensive system (starting from the geometrical reconstruction of the boards to the virtual analysis for calculation of the virtual MoEdyn) for the strength prediction of wood that is based solely on the surface images. The developed model makes it possible to predict the tensile strength of timber with relatively high accuracy, which is approximately at the same level as current grading machines.

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Tests on double-shear steel-to-timber joints loaded parallel-to-grain were undertaken, using beech and azobé with one, three and five dowels in a row. The dowels were made of high strength steel (hss) and very high strength steel (vhss). The experiments have shown a significant difference in load-carrying capacity of joints with vhss and hss dowels. Joints with one dowel provided enough plastic deformation capacity to allow for ductile failure modes whilst this does not hold for joints with three or five dowels in a row. No correlation between load-carrying capacity and density within one wood species could be observed. Novel failure modes including steel failure of the dowels were observed. The observed effective number of fasteners was lower for the joints with vhss dowels. Also for the stiffness Kser, an effective number of fasteners could be observed. The tested timber joints with their simultaneous ductile and brittle failure modes still present a major challenge for modelling. Wood is heterogeneous, highly anisotropic and shows ductile behaviour in compression and brittle behaviour in tension and shear. A bespoke 3D constitutive model for wood based on continuum damage mechanics was used to capture these effects. Eight stress-based failure criteria were defined in order to formulate piecewise defined failure surfaces. The damage development was controlled by nine damage variables that were inserted in the damage operator. The joint test results were compared to modelling outcomes. The failure modes could be identified and the general shape of the load-displacement curves agreed with the experimental outcomes.@en

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

Timber boards are numerically reconstructed in the full 3D space based on knot information on the wood surface. The 3D model is then transformed into a full 3D-FEM model and successively used for tensile strength prediction. By knowing the exact locations of the knots, as the main strength governing parameters in timber boards, simulations are run for a large quality range of wood laminations. This includes low-medium quality Douglas fir and medium-high quality spruce boards. ABAQUS and PYTHON are used for the numerical simulations. An automatic link is programmed to extract data of the database and to create the 3D geometrical model. From the numerical simulations, three mathematical methods are presented to calculate the stress concentration factors (SCFs) around the 3D heterogeneous defects in anisotropic wooden boards. Additionally, the explicit dynamic analysis are run to obtain the dynamic modulus of elasticity (MoEdyn). To reduce the dependency of the numerical predictions on the real density of the boards, the average density of each sample is used for the simulations. Each board is tested in tension physically and is used for the validation of the model. The FEM results are used in a regression analysis to analyze the correlation with the visual measurements and to predict the tensile strength. Based on the results of a multiple regression analysis, two SCFs and MoEdyn are sufficient to accurately predict the strength of spruce and Douglas fir boards. The results of the current study show that an improvement in the strength prediction of wood is possible in comparison with current machine grading systems based on dynamic MoE and knot parameters.@en