最新刊期
卷 40 ， 期 3 ， 2026
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摘要：To address the low efficiency of prediction and complex testing procedures for the mechanical properties of wood in selection of the wood materials for replacing severely damaged wooden components in ancient buildings, developing a rapid method for predicting wood mechanical properties and establishing a suitability evaluation system for restoration materials is of great importance. This study measured anatomical and physical indicators of Larix gmelinii var. principis-rupprechtii specimens, including growth ring width, latewood percentage, and air-dry density. Simultaneously, non-destructive testing (NDT) parameters were obtained, including stress wave velocity, micro-drilling resistance, and their coupled composite parameter (wave resistance modulus). Five machine learning algorithms including Random Forest (RF), Decision Tree (DT), K-Nearest Neighbors Regression (KNNR), Support Vector Regression (SVR), and Tabular Prior-Data Fitted Network (TabPFN), were employed to construct prediction models for key mechanical properties, including modulus of rupture, modulus of elasticity, and compressive strength parallel and perpendicular to the grain, under limited sample conditions. Among all indicators, air-dry density, latewood percentage, and micro-drilling resistance exhibited the highest Pearson correlation coefficients with the mechanical properties (all>0.5), whereas growth ring width and stress wave velocity showed relatively weak correlations. By integrating these three highly correlated multi-source features (air-dry density, latewood percentage, and micro-drilling resistance) for modeling, the prediction accuracy improved by 23.26% and 72.05%, respectively compared to using anatomical/physical indicators or NDT parameters alone. Among these five models, the pre-training-based TabPFN achieved the best prediction approach for the mechanical properties, yielding an R² of 0.961 4 for the modulus of rupture. Using Shapley additive explanations (SHAP) values, feature contribution analysis further identified air-dry density, latewood percentage, and micro-drilling resistance as the core predictive features, with air-dry density contributing the most (average SHAP value of 61.29%). The proposed machine learning-based prediction method, integrating growth features, physical, and NDT parameters, enables a rapid and accurate method for predicting the key mechanical properties of Larix gmelinii var. principis-rupprechtii wood, providing a critical scientific basis for selecting suitable materials for replacing severely damaged components in the restoration of ancient timber structures such as the Yingxian Wooden Pagoda.关键词：Larix gmelinii var. principis-rupprechtii;ancient building restoration;machine learning;TabPFN;air-dry density;latewood percentage;micro-drilling resistance;mechanical properties67|0|0更新时间：2026-08-03
KEY SCIENTIFIC RESEARCH BASE OF HISTORICAL BUILDING WOOD
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摘要：To gain a deep understanding of the differences in wood properties and grade-based utilization of Sapindus mukorossi from various cultivation regions, this study investigated the physical and mechanical properties, chemical composition and fiber morphology of 11-year-old seedling stands of Sapindus mukorossi from four typical cultivation regions: Jianning (Fujian), Shimen (Hunan), and Zhenfeng and Dushan (Guizhou). The potential utilization was evaluated by using an equal-weight membership function. The results indicated that certain wood properties of Sapindus mukorossi exhibited significant geographic variations. The results indicated that certain wood properties of Sapindus mukorossi exhibited significant geographic variations. The fiber length ranged from 943.67 to 1 040.73 μm, holocellulose content ranged from 62.76% to 73.62%. The bending strength, and modulus of elasticity, compressive strength parallel to grain ranged from 124.9 to 153.2 MPa, 10 817 to 13 461 MPa, and 43.0 to 49.2 MPa, respectively. According to the equal-weight membership function evaluation, samples from Shimen and Zhenfeng scored relatively higher for small-diameter structural timber, Shimen samples showed higher scores for decorative applications, and Jianning samples achieved the highest score for papermaking raw material. These findings could provide a scientific basis for the grade-based utilization of juvenile Sapindus mukorossi resources, subsequent tracking evaluation of mature wood, and directional cultivation.关键词：Sapindus mukorossi;Wood properties;wood utilization36|0|0更新时间：2026-08-03 -
摘要：Establishing scientific and accurate wood species identification methods through the efficient extraction of characteristic information from different wood species holds significant practical importance for promoting biodiversity conservation and the sustainable utilization of forest resources. However, existing techniques such as computer vision and DNA barcoding are still insufficient to meet the demand for rapid and accurate species discrimination, underscoring the need for methodological innovation in wood identification. In this study, three morphologically similar Quercus species common in trade: Quercus alba, Quercus mongolic, and Quercus robur, which are difficult to differentiate using conventional anatomical methods, were selected as investigated species to acquire spectral fingerprint data using Direct Analysis in Real Time-Time-of-Flight Mass Spectrometry (DART-TOF-MS). Four machine learning algorithms, including logistic regression, multilayer perceptron (MLP), random forest(RF), and k-nearest neighbors (KNN), were then applied to DART-TOF-MS data to assess their feasibility for species classification. We further investigated the influence of different spectral preprocessing parameters on model performance. The results showed that the logistic regression model achieved the highest classification accuracy (89.5%), outperforming the other three algorithms. Distinct differences were observed among the four machine learning approaches in their ability to handle complex spectral features, and appropriate binning strategies-particularly threshold control and mass tolerance selection-were found to be critical for optimal model performance, with the best results obtained at a parameter setting of 3% relative threshold and 20 mmu binning tolerance. Although the three Quercus species exhibited similarities in lignin monomers and their derivatives, significant differences were detected in the distribution of flavonoids, lignin dimers, and ellagic acid. The present results demonstrated that DART-TOF-MS combined with machine learning exhibited a strong capability for identifying the three Quercus wood species examined in this study, providing a scientific basis and technical pathway for the accurate identification of wood species.关键词：Quercus;wood identification;machine learning;DART-MS;Logistic regression algorithm27|0|0更新时间：2026-08-03 -
摘要：This study proposed a new metal-organic frameworks (MOFs) synthesis strategy based on phase change media to solve the fire hazards associated with phase change energy storage wood in building applications and address challenges such as poor dispersibility, aggregation tendency, and ineffective impregnation modification of MOFs in phase change materials. By using polyethylene glycol (PEG) 2000 simultaneously as both a reaction solvent and phase change unit, the synthesis and dispersion of MOFs were integrated into a single process, enabling the preparation of Cu-MOF/PEG. Ochroma lagopus was then impregnated with PEG 2000 and Cu-MOF/PEG to produce phase change energy storage wood (PEG/DW) and flame-retardant phase change energy storage wood (Cu-MOF/PEG/DW), respectively. Results showed that Cu-MOF was successfully synthesized within PEG, exhibiting well-defined crystalline structures, with particle size and morphology consistent with Cu-MOF synthesized using the conventional solvent N,N-dimethylformamide. Both PEG 2000 and Cu-MOF/PEG were effectively filled into wood pores, and copper elements were uniformly distributed in Cu-MOF/PEG/DW. Due to the 35.6% lower weight gain rate of Cu-MOF/PEG/DW than PEG/DW, the melting and crystallization enthalpies decreased to 113.5 and 108.8 J/g, respectively, and the crystallization and melting temperatures decreased by 1.7 ℃ and 1.3 ℃, respectively. The slight decrease in enthalpy and phase transition temperature indicated that Cu-MOF/PEG/DW still exhibited excellent phase change heat storage capacity. The lower weight gain also reduced the surface heating time by 35 s compared with PEG/DW. In addition, the synergistic flame-retardant and smoke-suppressing effects of Cu and nitrogen-containing groups in organic ligands increased the limiting oxygen index (LOI) of Cu-MOF/PEG/DW by 29.8% (P＜0.05). During the 600 s cone calorimeter test, the total heat release decreased by 17%, total smoke release reduced by 91.7%, and no dripping occurred during combustion. This research overcame the technical barrier of efficiently combining MOFs with phase change energy storage wood, offering a new method for developing green, energy-efficient building materials with excellent thermal storage performance and enhanced fire safety.关键词：metal-organic frameworks;polyethylene glycol;phase-change energy storage wood;flame retardancy;limiting oxygen index34|0|0更新时间：2026-08-03 -
摘要：Current room-temperature phosphorescent transparent wood mainly relies on non-degradable petroleum-based polymers as fillers. However, such systems suffer from poor compatibility between the wood skeleton and functional components, making it difficult to meet the demand for biomass-based materials with excellent optical, mechanical, and degradable properties in fields such as anti-counterfeiting identification and intelligent photoresponsive applications. In this study, balsa wood (Ochroma lagopus) was used as the raw material. An H2O2 bleaching-steam method was adopted for delignification, and carboxymethyl cellulose (CMC) was used as the filler to prepare room-temperature phosphorescent cellulose-based transparent wood (RTP-CTW). The results showed that the H2O2 bleaching-steam method efficiently removed lignin and hemicellulose while well preserving the wood cell-wall skeleton mainly composed of cellulose. Through vacuum impregnation, CMC was filled into the wood pores and formed hydrogen bonds with the cellulose components in the skeleton, thereby reducing interfacial light scattering and enhancing structural bonding. Under 254 nm ultraviolet excitation, RTP-CTW emitted cyan-blue phosphorescence at 484 nm, with a phosphorescence lifetime of 450.27 ms, a maximum afterglow duration of 7 s, and a phosphorescence quantum yield of 8.12%. The carboxyl and carbonyl luminescent units in CMC were the main origin of the photoluminescence. The hydrogen-bonding network between CMC and the wood skeleton suppressed non-radiative transitions through a confinement effect and shielded oxygen, enabling tunable room-temperature phosphorescence from blue to green. RTP-CTW exhibited a maximum transmittance of 81%, a maximum haze of 92%, and a thermal conductivity of 0.33 W/(m·K). It shows tensile strength higher than delignified wood and CMC. Moreover, RTP-CTW can degrade in soil within 20 days, indicating good degradation potential. RTP-CTW showed reversible humidity-responsive and heat-recoverable properties, suggesting potential applications in anti-counterfeiting identification and intelligent photoresponsive materials.关键词：transparent wood;room-temperature phosphorescence;cellulose-based;carboxymethyl cellulose;delignified wood31|0|0更新时间：2026-08-03 -
摘要：To promote the continuous flat-pressing technology in manufacturing of plywood using polymeric methylene diphenyl diisocyanate (pMDI), this study investigated the effects of microwave pre-heating characteristics of seven-layer Eucalyptus veneer mats at power levels (i.e., 0.5, 1.0, 1.5, and 2.0 kW) and tested the bonding strength of the pMDI plywood made. The veneer had a thickness of 1.7 mm and three initial moisture contents of 12%, 18%, and 24%. The results showed that both microwave power and mat moisture content exerted an extremely significant influence on the heating rate of mats (P＜0.01). Within the selected range of initial veneer moisture content, the heating rate of the mat decreased with an increase in moisture content and increased with an increase in microwave power. The maximum heating rate of the mat occurred within the microwave preheating duration of 30~60 s. The linear relationship between microwave power and heating amplitude of the mat was obtained and verified. Based on the linear fitting results, combined with the actual production requirement of heating the mat to 80 °C within 60 s, a microwave preheating power of 3 kW and a mat moisture content of 24% were selected as the optimal parameters to make pMDI plywood. It was also found that the bonding strength and the 24 h water absorption rate of plywood with microwave preheating was significantly higher than that of plywood directly hot-pressed without microwave preheating (P＜0.05). Moreover, microwave preheating reduced the hot-pressing time in manufacturing of pMDI plywood to 15 s/mm, shorter than that of plywood without microwave preheating. The average bonding strength of the plywood made reached 1.09 MPa, which met the performance requirements for type Ⅰ Eucalyptus plywood specified in GB/T 9846—2015“Plywood for general use”. By contrast, the plywood without microwave preheating failed to produce qualified products. This study could provide data support and technical reference for the application of microwave preheating technology in manufacturing pMDI plywood on the industrial production lines.关键词：Eucalyptus plywood;polymeric methylene diphenyl diisocyanate (pMDI);microwave power;heating rate;heating amplitude;bonding strength;water absorption rate1|0|0更新时间：2026-08-03 -
摘要：To promote the application of laser technology in the precision wood processing industry, this study investigated the effects of laser cutting parameters, including working distance (A), feed rate (B), and laser power (C), on kerf depth and kerf width of Abies nephrolepis, and established mathematical models to predict the kerf size. Multifactor completely randomized analysis of variance, interaction effect analysis, and Tukey's honestly significant difference post-hoc test were used to examine the significance of the main and interaction effects of laser cutting parameters on kerf size. The results showed that the cutting parameters A, B, and C had extremely significant main effects on both kerf depth and kerf width (P<0.001). According to partial η² values, the order of main effect size for kerf depth was C>B>A, while that for kerf width was A>B>C. Both second-order and third-order interaction effects reached significant levels, and their influence on kerf depth and kerf width followed the order A×B>A×B×C>B×C>A×C, indicating obvious multi-parameter coupling during laser cutting. Based on the established regression equations, the cutting parameter A showed a nonlinear regulatory effect on laser cutting of fir, whereas the cutting parameters B and C exhibited approximately linear effects. The prediction errors for cutting performance were about 21.30% for kerf depth and 24.94% for kerf width, respectively. Therefore, the cutting parameter working distance, could be preferentially fixed in practical production to improve process stability.关键词：laser cutting;Abies nephrolepis;working distance;feed rate;laser power;kerf depth;kerf width;interaction effect1|0|0更新时间：2026-08-03 -
摘要：Rolling shear failure is one of the critical factors limiting the bending capacity of cross-laminated timber (CLT), however existing numerical models often fail to achieve accurate predictions due to neglecting the intrinsic coupling among rolling shear, transverse tensile, and longitudinal shear damage. A three-dimensional orthotropic constitutive model for wood was developed based on continuum damage mechanics (CDM) and elastoplastic theory, which explicitly incorporates such coupling effects among rolling shear, transverse tensile, and longitudinal shear damage modes. The model was implemented numerically via a user-defined material subroutine (VUMAT) in the ABAQUS/Explicit platform. Validation through wood mechanical property tests and full-scale bending tests of three-configuration CLT panels made of Chinese fir (Cunninghamia lanceolata) demonstrated that the model developed could accurately capture the elastic plastic yield behavior of wood under compression and the linear elastic brittle fracture behavior under tension and shear. For both three-layer and five-layer CLT specimens with span-to-thickness ratios of 15 and 20, the predicted bending strengths showed relative errors within 10% compared to experimental results, and the predicted macroscopic failure modes exhibited excellent agreement with experimental observations. Furthermore, damage evolution analysis of a three-layer CLT with a span-to-thickness ratio of 15 revealed that the ultimate bending failure was governed by rolling shear damage in the central transverse layer, which first reached the critical damage threshold. The rolling shear damage zone also coincided with regions of transverse tensile and longitudinal shear damage, verifying the synergistic evolution among multiple damage modes. The proposed coupled damage model could overcome the limitations of traditional independent failure criteria and provide a reliable tool for refined numerical analysis and safety assessment of CLT structures.关键词：Chinese Fir;cross-laminated timber (CLT);rolling shear;continuum damage mechanics;constitutive model;Numerical simulation1|0|0更新时间：2026-08-03 -
摘要：This study presented an integrated molding approach for wooden automotive models using five-axis simultaneous CNC machining, in response to the pressing demand for physical prototypes that are efficient, economical, and environmentally sustainable in design validation. High-density fiberboard (HDF) was employed as the substrate, and a full digital process chain was established by optimizing tool-axis vector control and tool-path strategies to accommodate the specific characteristics of HDF. Furthermore, a“material-process-machining”synergistic control system was proposed, grounded in the performance attributes of HDF, enabling the integrated high‑precision fabrication of complex‑curved automotive body surfaces. This approach effectively could resolve the long‑standing bottlenecks of poor accuracy and inadequate surface quality in machining wood‑based materials with intricate geometries. Application and sustainability assessments revealed that the machining cycle was set at only 2 700 minutes, resulting in a reduction of over 60% compared with traditional clay modeling. The total cost could be reduced to one‑third that of clay models and two‑fifth that of resin‑based 3D‑printed counterparts. The change in key linear dimensions of the vehicle contour after 30 days of static placement was not larger than 0.3 mm, demonstrating outstanding dimensional stability. This rigid prototype solution offered high repeatability and was well suited for rapid multi‑scheme iteration during mid‑stage design, batch validation, preliminary aerodynamic evaluation, and high‑end display mock‑up production. Notably, as a recyclable wood-based material, HDF could facilitate a paradigm shift in prototype manufacturing-from consumable materials like clay toward a digitally traceable, full-process, and environmentally responsible production chain. This work provided a practical reference for the integration of intelligent manufacturing technologies at the intersection of wood science and automotive engineering.关键词：Automotive exterior model;Five-axis machining;high-density fiberboard;Integrated molding;coupled control system60|0|0更新时间：2026-08-03 -
摘要：The operational efficiency, resource utilization rate and production cost of panelized wood furniture production lines are directly related to the market competitiveness of enterprises, constituting a critical link in wooden furniture manufacturing. Aiming at addressing the problems of unbalanced process allocation and prominent bottleneck processes existing in the panelized wood table furniture production line of Enterprise M, this study adopted the 0-1 integer programming method to construct quantitative models and solved them for two types of assembly line balancing problems, namely fixed production tempo (type I balancing problem) and fixed number of workstations (type II balancing problem), so as to identify the optimization potential of the production line. Subsequently, simulation verification of the optimization results was carried out based on the FlexSim simulation platform, and a comparative analysis was performed between the pre- and post-optimization schemes. The results showed that for the Type I balance problem, the model reduced the workstations from 15 to 8, improved the balance rate of the production line to a good level of 87.73%, and increased the average processing rate of each process by 18.62%. For the Type II balance problem, the model reduced the Takt time from 53.22 min to 30.01 min, while also achieving a good level of balancing efficiency and an approximate 12% rise in average processing rate. Although the two optimization paths differed in perspectives, both could effectively improve the assembly line balancing level. This study provided a feasible reference for the lean upgrading and intelligent transformation of panelized wood furniture production lines.关键词：panelized wood furniture;integer programming;process optimization;line balance rate;number of workstations;takt time;processing rate1|0|0更新时间：2026-08-03
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