Search Results (109)

Traditionally, mechanical bending tests are used to measure the stiffness of lumber, which is generally represented by the static modulus of elasticity (MoE). However, it is desirable to measure the stiffness of wood before it is processed into lumber. Acoustic nondestructive testing techniques are therefore the main techniques used by the wood industry to estimate the dynamic MoE of wood. The acoustic resonance technique is employed for measuring the MoE in felled logs and lumber. In contrast, the acoustic time-of-flight (ToF) technique is traditionally used for MoE measurements on standing trees and seedlings. However, the ToF technique overestimates stiffness compared to both resonance and static bending tests (considered the gold standard). In this work, a guided wave technique is used to measure the stiffness of wooden rods. This work is the first to compare the MoE values obtained using static bending tests (gold standard) with those obtained using acoustic resonance, ToF, and guided wave methods. Measurements were performed on 16 mm diameter radiata pine wooden rods. For comparison, measurements were also performed on acetal, aluminium, and steel rods of similar dimensions. The findings show that stiffness measurements obtained using the proposed guided wave method are more accurate than those obtained using the traditional ToF method and closely match those of the resonance method across all materials. The measurements from the ToF method were overestimated compared to resonance, guided wave, and static bending methods. The findings show the potential for the guided wave method to be used as an alternative method to provide more accurate stiffness measurements in juvenile trees/seedlings compared with the traditional ToF technique. Full article

This study proposes a novel LK-BP-AFPSO model for the nondestructive evaluation of wood mechanical properties, combining a backpropagation neural network (BP) with adaptive fractional-order particle swarm optimization (AFPSO) and Liang–Kleeman (LK) information flow theory. The model accurately predicts four key mechanical properties—longitudinal tensile strength (SPG), modulus of elasticity (MOE), bending strength (MOR), and longitudinal compressive strength (CSP)—using only nondestructive physical features. Tested across diverse wood types (fast-growing YKS, red-heart CSH/XXH, and iron-heart XXT), the framework demonstrates strong generalizability, achieving an average prediction accuracy (R²) of 0.986 and reducing mean absolute error (MAE) by 23.7% compared to conventional methods. A critical innovation is the integration of LK causal analysis, which quantifies feature–target relationships via information flow metrics, effectively eliminating 29.5% of spurious correlations inherent in traditional feature selection (e.g., PCA). Experimental results confirm the model’s robustness, particularly for heartwood variants, while its adaptive fractional-order optimization accelerates convergence by 2.1× relative to standard PSO. This work provides a reliable, interpretable tool for wood quality assessment, with direct implications for grading systems and processing optimization in the forestry industry. Full article

Acoustic tomography is a non-destructive technique used in the internal assessment of standing trees. Various researchers have focused on developing analytical tools using this technique, demonstrating that they can detect internal biodeterioration in cross-sections with good accuracy. This study evaluates the use of two ultrasonic wave devices with different frequencies (USLab and Sylvatest Duo) and a stress wave device (Microsecond Timer) to generate acoustic tomography using ImageWood VC1 software. The tests were carried out on 12 cross-sections of urban trees in the city of Madrid of the species Robinia pseudoacacia L., Platanus × hybrida Brot., Ulmus pumila L., and Populus alba L. Velocity measurements were made, forming a diffraction mesh in both standing trees and logs after cutting them down. An inspection was carried out with a perforation resistance drill (IML RESI F-400S) in the radial direction in each section, which allowed for more precise identification of defects and differentiating between holes and cracks. The various defects were determined with greater accuracy in the tomographic images taken with the higher-frequency equipment (45 kHz), and the combination of ultrasonic tomography and the use of the inspection drill can provide a more accurate representation of the defects. Full article

The behavior of structural elements, which is very important in structural engineering, can be determined non-destructively using ambient vibration tests. Composite elements used in structures can be formed by combining elements of different materials. It is much more difficult to predict the structural behavior of composite elements because they are made of different materials. Ambient vibration tests are one of the most important methods used to determine the dynamic characteristics of composite elements. In this study, composite cantilever beams were formed by combining wood and steel profiles in various combinations. The dynamic characteristics of these beams (natural frequency, mode shape, modal damping ratio) were determined by both the numerical method and operational modal analysis (OMA) method. Firstly, the initial analytical models of the beams were modeled using the finite element program. The natural frequencies and mode shapes of the models were determined using the modal analysis method. While creating the initial analytical model, the material properties of the beams were entered by taking into account the standard values in the literature. Then, the dynamic characteristics of the beams were determined using an experimental modal analysis method (operational modal analysis test). The dynamic characteristics obtained from tests and the analysis of the initial analytical models were compared. The analytical models were calibrated according to the test results. In this way, the modeled beams were provided with a more realistic dynamic behavior. Numerical models were modeled using the SAP2000 program. As a result of the analysis, the dynamic characteristics and structural properties of composite cantilever beams were compared. As the elasticity modules and cross-sections of the profiles used in the beams increase, the stiffness of the beams also increases. It was determined that the natural frequencies of the composite beams increase with the increase in their stiffness. When the frequencies of the first modes of the least rigid wood (W) beam and the most rigid steel–wood–steel (S-W-S) beam were compared, an increase of 47% was detected. Full article

This text provides a comprehensive overview of structural timber old buildings, from an in-depth analysis of construction processes to laboratory-based research aimed at establishing a pattern for estimating the density of wood in buildings. It is now widely recognised by society that historic buildings should be subject to conservation or rehabilitation. This article discusses the good technical knowledge that those involved in old buildings should have: the understanding of and respect for old construction techniques; rigorous inspections and diagnosis before a project; and the recognition of the properties of wooden structural elements, either visually or by means of non-destructive or semi-destructive testing methods (NDT/SDT). The final section of this article presents a laboratory study that correlates penetration resistance test results with wood density and verifies them in situ by direct analysis with wood core extraction. The aim of this study is to establish and verify a reliable pattern that allows the user to estimate the density of Scots pine in any structural member in service in an old building. The results obtained in the laboratory and of wood in service show that Equation (1) is a suitable pattern to obtain wood density through the wood penetration resistance test. Full article

The diversity of commercial tree planting sites, with their distinct environmental conditions, directly influences tree growth and consequently impacts the wood properties in various ways. However, there is limited research evaluating the impact of these variations in nondestructive testing. Therefore, this study aimed to investigate whether edaphoclimatic variations affect parameters obtained through nondestructive tests conducted on standing trees. To this end, 30 specimens were selected from 3 Eucalyptus sp. clones, aged 1, 3, and 4 years, grown in 2 regions, totaling 540 trees. Tree development was monitored quarterly over 12 months. The tests included ultrasound propagation, drilling resistance, and penetration resistance, and the trees were measured for diameter at breast height (DBH) and height. Among the edaphoclimatic factors evaluated, only temperature and soil water storage differed statistically between the two study regions. The higher temperature and lower soil water storage in region 2 promoted tree growth, with these trees showing greater drilling resistance and higher longitudinal wave velocities. In addition, the influence of climatic factors was evidenced by the variation of wave propagation velocity throughout the year. Periods of lower water availability resulted in higher velocities, while periods of greater precipitation were associated with lower velocities. The research results showed that temperature and soil water storage had significant effects on tree growth (DBH and height), as well as ultrasound wave propagation velocity and drilling resistance. Full article

Inferring forest properties is crucial for the timber industry, enabling efficient monitoring, predictive analysis, and optimized management. Nondestructive testing (NDT) methods have proven to be valuable tools for achieving these goals. Recent advancements in data analysis, driven by machine learning (ML) algorithms, have revolutionized this field. This study analyzed 492 eucalyptus trees (Eucalyptus sp.), aged 3 to 7 years, planted in São Paulo, Brazil. Data from forest inventories were combined with results from ultrasound, drilling resistance, sclerometric impact, and penetration resistance tests. Seven machine learning algorithms were evaluated to compare their generalization capabilities with conventional statistical methods for predicting basic wood density. Among the models, extreme gradient boosting (XGBoost) achieved the highest accuracy, with a coefficient of determination (R²) of 89% and a root mean square error (RMSE) of 10.6 kg·m⁻³. In contrast, the conventional statistical model, using the same parameters, yielded an R² of 33% and an RMSE of 26.4 kg·m⁻³. These findings highlight the superior performance of machine learning in the nondestructive inference of wood properties, paving the way for its broader application in forest management and the timber industry. Full article

Modulus of elasticity (MOE) and modulus of rupture (MOR) are crucial indicators for assessing the application value of wood. However, traditional physical testing methods for the mechanical properties of wood are typically destructive, costly, and time-consuming. To efficiently assess these properties, this study proposes a multi-input residual network (MIRN) model, which integrates microscopic images of wood with physical density data and leverages deep learning technology for rapid and accurate predictions. By using larger convolution kernels to enhance the receptive field, the model captures fine microstructural features in the images. Batch normalization layers were removed from the ResNet architecture to reduce the number of parameters and improve training stability. Shortcut connections were utilized to enable deeper network architectures and address the vanishing gradient problem. Two types of residual blocks, convolutional block and identity block, were defined based on input dimensional changes. The MIRN method, based on multi-input residual networks, is proposed for non-destructive testing of wood mechanical properties. The experimental results show that MIRN outperforms convolutional neural networks (CNNs) and ResNet-50 in predicting MOE and MOR, with an R² of 0.95 for MOE and RMSE reduced to 46.88, as well as an R² of 0.85 for MOR and an RMSE of 0.44. Thus, this method offers an efficient and cost-effective tool for wood processing and quality control. Full article

The widespread adoption of wood in construction is driven by its sustainability, cost-effectiveness, and esthetic appeal. The construction of wood buildings often requires minimal specialized equipment, contributing to affordability and higher demand for wood-frame structures. Wood is considered more sustainable than other building materials, such as steel or concrete, for several reasons, including its renewable nature, low embodied energy, carbon sequestration, energy efficiency, and biodegradability, among others. In the United States, wood is the most common material used in building construction. While many of the structures are single-family homes, wood framing is also prevalent in larger apartment complexes, as well as commercial and industrial buildings. Timber has also been traditionally used for bridge construction, and recently, it has been considered again for the construction of new bridges. Over time, wood-frame construction has developed from a basic method for primitive shelters into a sophisticated field of structural design. As an eco-friendly resource, wood is crucial for promoting sustainable building practices. However, ensuring the long-term performance and safety of timber structures is essential. Regular inspections and testing of wooden structures are important to identify signs of wear, damage, or decay. One type of testing which is gaining popularity is nondestructive testing (NDT). NDT techniques have become invaluable for assessing the condition of timber components because such techniques are non-invasive in nature and do not cause damage, ensuring that structures remain functional with minimal disruptions. These methods provide critical insights into the structural integrity and operational efficiency of wood under sustained loads and in inclement environments. This article examines various NDT techniques used to evaluate timber structures, highlighting their capabilities, as well as advantages and limitations. It also discusses the importance of wood in advancing sustainability within the construction industry and emphasizes the need for accurate and reliable assessment methods to enhance the use of timber as an environmentally friendly building material. By incorporating NDT practices into regular inspection and maintenance protocols for buildings, bridges, and other structures, various stakeholders can ensure the durability, longevity, and safety of timber structures, thereby contributing to the progress and advancement of sustainable construction practices worldwide. Full article

To overcome the problems of the low signal-to-noise ratio and poor performance of wood ultrasonic images caused by ring-down vibrations during the ultrasonic quality detection of wood, a composite pulse excitation technique using a wood air-coupled ultrasonic detection system is proposed. Through a mathematical analysis of the output of the ultrasonic transducer, the conditions necessary for implementing composite pulse excitation were analyzed and established, and its feasibility was verified through COMSOL simulations. Firstly, wood samples with knot and pit defects were used as experimental samples. We refined the parameters for the composite pulse excitation technique by conducting A-scan measurements on both defective and non-defective areas of the samples. Moreover, two stepper motors were employed to control the path for C-scan imaging to detect wood defects. The experiment results showed that the composite pulse excitation technique significantly enhanced the precision of nondestructive ultrasonic testing for wood defects compared to the traditional single-pulse excitation method. This technique successfully achieved precise detection and location of pit defects, with a detection accuracy rate of 90% for knot defects. Full article

As a mature non-destructive testing technology, near-infrared (NIR) spectroscopy can effectively identify and distinguish the structural characteristics of wood. The Wood Defect One-Dimensional Visual Geometry Group 19-Finite Element Analysis (WD-1D-VGG19-FEA) algorithm is used in this study. 1D-VGG19 classifies the near-infrared spectroscopy data to determine the knot area, fiber deviation area, transition area, and net wood area of the solid wood board surface and generates a two-dimensional image of the board surface through inversion. Then, the nonlinear three-dimensional model of wood with defects was established by using the inverse image, and the finite element analysis was carried out to predict the elastic modulus of wood. In the experiment, 270 points were selected from each of the four regions of the wood, totaling 1080 sets of near-infrared data, and the 1D-VGG19 model was used for classification. The results showed that the identification accuracy of the knot area was 95.1%, the fiber deviation area was 92.7%, the transition area was 90.2%, the net wood area was 100%, and the average accuracy was 94.5%. The error range of the elastic modulus prediction of the three-dimensional model established by the VGG19 classification model in the finite element analysis is between 2% and 10%, the root mean square error (RMSE) is about 598. 2, and the coefficient of determination (R2) is 0. 91. This study shows that the combination of the VGG19 algorithm and finite element analysis can accurately describe the nonlinear defect morphology of wood, thus establishing a more accurate prediction model of wood mechanical properties to maximize the use of wood mechanical properties. Full article

Intending to safeguard architectural heritage, the assessment of the health of timber structures is crucial, though challenging, due to the organic nature of wood and to the uncertainties of its preservation state. To this end, useful support is provided by the ICOMOS guidelines, which provide conservation strategies based on thorough diagnosis and safety evaluations. In this context, the study summarized in this paper focuses on the medieval Tower of Montorio, which suffered considerable damage due to the strong earthquake that occurred in those area in September 2003. Its subsequent process of rehabilitation and restoration involved a widespread experimental campaign and the substitution of some timber beams. This circumstance has offered a rare opportunity to study these ancient elements in detail, although they are limited in number. Six beams made of oak and removed from an intermediate floor of the tower were evaluated through a comprehensive approach that included both non-destructive tests (NDT) and destructive tests (DT). Particularly, they were subjected to visual inspections, ultrasonic, sclerometric, and resistographic methods, and destructive four-point bending tests. Overall, the study presented here provides a useful qualitative comparison between them. Results highlighted that relying only on NDT might lead to an overestimation of mechanical properties and that combining NDT with DT is crucial for a more accurate assessment. Therefore, the need to deepen the research on correlations between NDT and DT to obtain reliable values of mechanical properties while respecting the conservation aim was confirmed. Full article

Cross Laminated Timber (CLT) is a structurally complex panel that poses challenges in analysis due to the anisotropic nature of wood and the orthotropic characteristics of the composite. Numerical modeling using the Finite Element Method (FEM) offers a viable solution for analysis, particularly for addressing boundary value problems that are analytically challenging. Therefore, it is crucial to validate the experimental properties to ensure accurate results. The objective of this study was to validate the physical and mechanical properties for structural modeling using FEM, based on the characterization of Eucalyptus benthamii Maiden & Cambage wood and CLT panels. For wood characterization, the basic and apparent density were determined, and mechanical tests, including static bending, parallel-to-grain compression, and shear tests, were conducted. Utilizing the same batch of wood, three-layer CLT panels were manufactured and subjected to a non-destructive three-point bending test. This test was simulated in RFEM finite element software, employing Mindlin’s theory, and the displacements obtained were compared with the experimental method. The results from a Student’s t-test at a 5% significance level indicated no significant difference between the experimental and numerical methods, suggesting that the properties of the experimental E. benthamii CLT panel can be accurately represented by FEM. Full article

With the rapidly growing interest in using structural timber, a need exists to inspect and assess these structures using non-destructive testing (NDT). This review article summarizes NDT methods for wood inspection. After an overview of the most important NDT methods currently used, a detailed review of Ground Penetrating Radar (GPR) and Ultrasonic Testing (UST) is presented. These two techniques can be applied in situ and produce useful visual representations for quantitative assessments and damage detection. With its commercial availability and portability, GPR can help rapidly identify critical features such as moisture, voids, and metal connectors in wood structures. UST, which effectively detects deep cracks, delaminations, and variations in ultrasonic wave velocity related to moisture content, complements GPR’s capabilities. The non-destructive nature of both techniques preserves the structural integrity of timber, enabling thorough assessments without compromising integrity and durability. Techniques such as the Synthetic Aperture Focusing Technique (SAFT) and Total Focusing Method (TFM) allow for reconstructing images that an inspector can readily interpret for quantitative assessment. The development of new sensors, instruments, and analysis techniques has continued to improve the application of GPR and UST on wood. However, due to the hon-homogeneous anisotropic properties of this complex material, challenges remain to quantify defects and characterize inclusions reliably and accurately. By integrating advanced imaging algorithms that consider the material’s complex properties, combining measurements with simulations, and employing machine learning techniques, the implementation and application of GPR and UST imaging and damage detection for wood structures can be further advanced. Full article

Fast-growing teak trees are cultivated extensively in Indonesia to meet the growing demand for teak wood. However, it is necessary to assess the conditions of teak stands throughout their growth period. The nondestructive testing of wood utilizing dielectric spectroscopy approaches based on electrical properties is currently under development, particularly for evaluating tree stands. This study aimed to analyze the dielectric values of fast-growing teak tree stands within a frequency range of 250 kHz to 60 MHz and to understand the relationship between their physical and anatomical properties. A capacitance measurement system was employed to collect dielectric spectroscopy data directly from trees aged 4, 5, and 7 years. Simultaneously, physical and anatomical samples were obtained using a 0.5 cm diameter increment borer. The results revealed significant differences in the fiber length, lumen diameter, and wall thickness at each age. The optimal dielectric frequency for distinguishing wood properties in standing trees was identified to be within a range of 18 MHz to 23 MHz. In the linear model, a moderate relationship was observed with a correlation coefficient of (r)0.403, although the coefficient of determination (r²) was weak at 0.162 for green density. However, a robust relationship was observed in the linear model for specific gravity with r = 0.826 and r² = 0.682. A weak but significant relationship was also identified with r = 0.2, a coefficient of determination of r² = 0.04, and a significance level < 0.05 in the predictive model of wood anatomy properties (vessel diameter and fiber wall thickness). Models with low r² but high significance indicate that the independent variables still noticeably contribute to explaining the dependent variable. Further analysis and data processing can be enhanced by identifying the crucial variables in the capacitance measurement system. Full article