The use of fast-growing plantation eucalypt (i.e., pulpwood eucalypt) in the construction of high-value structural products has received special attention from the timber industry in Australia and worldwide. There is still, however, a significant lack of knowledge regarding the physical and mechanical properties of the lumber from such plantation resources as they are mainly being managed to produce woodchips. In this study, the physical and mechanical properties of lumber from a 16-year-old pulpwood Eucalyptus nitens H.Deane & Maiden resource from the northeast of Tasmania, Australia was evaluated. The tests were conducted on 318 small wood samples obtained from different logs harvested from the study site. The tested mechanical properties included bending modulus of elasticity (10,377.7 MPa) and modulus of rupture (53 MPa), shear strength parallel (5.5 MPa) and perpendicular to the grain (8.5 MPa), compressive strength parallel (42.8 MPa) and perpendicular to the grain (4.1 MPa), tensile strength perpendicular to the grain (3.4 MPa), impact bending (23.6 J/cm²), cleavage (1.6 kN) and Janka hardness (23.2 MPa). Simple linear regression models were developed using density and moisture content to predict the mechanical properties. The variations in the moisture content after conventional kiln drying within randomly selected samples in each test treatment were not high enough to significantly influence the mechanical properties. A relatively high variation in the density values was observed that showed significant correlations with the changes in the mechanical properties. The presence of knots increased the shear strength both parallel and perpendicular to the grain and significantly decreased the tensile strength of the lumber. The results of this study created a profile of material properties for the pulpwood E. nitens lumber that can be used for numerical modelling of any potential structural product from such a plantation resource.

The mechanical properties of plantation Eucalyptus Nitens timber are currently assessed by applying visual stress grading (VSG) designed for the sawn timber from the mature plantation and do not represent the actual characteristics of the resource. However, the well-known limitation of VSG application for this resource led to the discovery of other methods to grade the timber to its relevant structural grade. There is potential for hardwood plantations in Australia to supply wood to the timber industry and be used in structural applications. However, it is necessary to employ criteria to evaluate the structural properties of this resource before it could be satisfactorily used for structural purposes. This research aimed to assess the use of non-destructive technique (NDT) through acoustic wave velocity (AWV), machine stress grading (MSG), and multiple linear regression (MLR) model to predict the modulus of elasticity (MOE) as a grade-determining factor. The results showed that there was a strong correlation (R² = 0.88) between the dynamic MOE (MOE_dyn) and static MOE (MOE_s) of the boards, proving the NDT as a reliable method for the MOE estimations of E. nitens timber. The results from the MLR model also showed that the density and AWV are effective parameters and their combination can be practical to estimate the MOE. There was a high correlation between the MOE obtained from MSG and MOE obtained from four-point bending, demonstrating that the MSG method through the flat-wise bending can be a suitable method for fast grading. The results also indicated that the measured MOE in the edgewise direction correlates with both the flatwise and longitudinal directions. The results also showed that the E. nitens timber resource has the potential to be used in structural applications with a wide range of MOE from 7 GPa to 21 GPa.

With the increasing availability of fast-growing Eucalyptus plantation logs in Australia in recent years, the timber manufacturing sector has become interested in discovering the opportunities of producing value-added timber products from this resource. Cross-laminated timber (CLT) could be a potential sustainable product recovered from this resource and supply material for commercial buildings. Shear of the inner cross-laminates, known as rolling shear, is one of the governing factors in serviceability and limit state design for this product under out-of-plane loading. This study evaluated the rolling shear (RS) properties of CLT with heterogonous layup configurations using different structural grade Eucalyptus nitens (E. nitens) timber under the planar shear test. Based on the results, G_r and ${\mathsf{\tau }}_{\mathrm{r}}$ values were shown to be significantly correlated with the density of the CLT panel. There was also a positive correlation between the RS modulus and MOR of the CLT panel. The specimens with high MOE in the top and bottom layers indicated the highest ${\mathsf{\tau }}_{\mathrm{r}}$ and F_max values. This indicated that using high-grade boards in the top and bottom lamellae plays an important role in increasing the RS strength, whereas using them in the cross-layer has a positive contribution in increasing shear modulus. The maximum observed RS strength and modulus ranged from 2.8–3.4 MPa and 54.3–67.9 MPa, respectively, exceeding the RS characteristic values of the resource. The results obtained in this study were comparable to those recommended in European standards for softwood CLT, demonstrating the potential use for eucalypt timber boards in CLT production. This paper provides an important insight into supporting the potential engineering applications of CLT panel products fabricated with eucalypt plantation.

The main goal of this study was to investigate the visual characteristics, recovery rate, and flexural properties of sawn boards from a fibre-managed plantation Eucalyptus globulus resource as a potential raw material for structural building applications. The impacts of the visual characteristics, strength-reducing features, and variation in basic density and moisture content on the bending modulus of elasticity (MOE) and modulus of rupture (MOR) of the boards were investigated. The reliabilities of different non-destructive methods in predicting MOE and MOR of the boards were evaluated, including log acoustic wave velocity measurement and numerical modellings. The MOE and MOR of the boards were significantly affected by the slope of grain, percentage of clear wood, and total number of knots in the loading zone of the boards. The normal variation in basic density significantly influenced the MOE of the boards while its effect on the MOR was insignificant. The numerical models developed using the artificial neural network (ANN) showed better accuracies in predicting the MOE and MOR of the boards than traditional multi-regression modelling and log acoustic wave velocity measurement. The ANN models developed in this study showed more than 78.5% and 79.9% success in predicting the adjusted MOE and MOR of the boards, respectively.