The dynamic and static modulus of elasticity （MOE） between bluestained and non-bluestained lumber of Lodgepole pine were tested and analyzed by using three methods of Non-destructive testing （NDT）, Portable Ultras...The dynamic and static modulus of elasticity （MOE） between bluestained and non-bluestained lumber of Lodgepole pine were tested and analyzed by using three methods of Non-destructive testing （NDT）, Portable Ultrasonic Non-destructive Digital Indicating Testing （Pundit）, Metriguard and Fast Fourier Transform （FFT） and the normal bending method. Results showed that the dynamic and static MOE of bluestained wood were higher than those of non-bluestained wood. The significant differences in dynamic MOE and static MOE were found between bulestained and non-bluestained wood, of which, the difference in each of three dynamic MOE （Ep. the ultrasonic wave modulus of elasticity, Ems, the stress wave modulus of elasticity and El, the longitudinal wave modulus of elasticity） between bulestained and non-bluestained wood arrived at the 0.01 significance level, whereas that in the static MOE at the 0.05 significance level. The differences in MOE between bulestained and non-bluestained wood were induced by the variation between sapwood and heartwood and the different densities of bulestained and non-bluestained wood. The correlation between dynamic MOE and static MOE was statistically significant at the 0.01 significance level. Although the dynamic MOE values of Ep, Em, Er were significantly different, there exists a close relationship between them （arriving at the 0.01 correlation level）. Comparative analysis among the three techniques indicated that the accurateness of FFT was higher than that of Pundit and Metriguard. Effect of tree knots on MOE was also investigated. Result showed that the dynamic and static MOE gradually decreased with the increase of knot number, indicating that knot number had significant effect on MOE value.展开更多
Uniaxial Compressive Strength (UCS) and modulus of elasticity (E) are the most important rock parameters required and determined for rock mechanical studies in most civil and mining projects. In this study, two mathem...Uniaxial Compressive Strength (UCS) and modulus of elasticity (E) are the most important rock parameters required and determined for rock mechanical studies in most civil and mining projects. In this study, two mathematical methods, regression analysis and Artificial Neural Networks (ANNs), were used to predict the uniaxial compressive strength and modulus of elasticity. The P-wave velocity, the point load index, the Schmidt hammer rebound number and porosity were used as inputs for both meth-ods. The regression equations show that the relationship between P-wave velocity, point load index, Schmidt hammer rebound number and the porosity input sets with uniaxial compressive strength and modulus of elasticity under conditions of linear rela-tions obtained coefficients of determination of (R2) of 0.64 and 0.56, respectively. ANNs were used to improve the regression re-sults. The generalized regression and feed forward neural networks with two outputs (UCS and E) improved the coefficients of determination to more acceptable levels of 0.86 and 0.92 for UCS and to 0.77 and 0.82 for E. The results show that the proposed ANN methods could be applied as a new acceptable method for the prediction of uniaxial compressive strength and modulus of elasticity of intact rocks.展开更多
The dimension lumber （45mm×90mm×3700mm） of plantation Chinese fir （Cunninghamia lanceolata （Lamb.） Hook.） was graded to four different classes as SS, No. 1, No.2 and No.3, according to national lumber ...The dimension lumber （45mm×90mm×3700mm） of plantation Chinese fir （Cunninghamia lanceolata （Lamb.） Hook.） was graded to four different classes as SS, No. 1, No.2 and No.3, according to national lumber grades authority （NLGA） for structure light framing and structure joists and planks. The properties of apparent density was determined at 15% moisture content, bending strength and stiffness were tested according to American Society for Testing and Materials （ASTM） D198-99, and dynamic modulus of elasticity （Eusw） was measured by ultrasonic technique, for predicting the flexural properties of different grade lumbers. The results showed that Eosw was larger than the static MOE. The relationship between Eusw and static MOE was significant at 0.01 level, and the determination coefficients （R2） of the four grade lumbers followed the sequence as R^2No.2 （0.616）〉 R^2ss （0.567）〉 R^2No1 （0.366）〉 R^2No.3 （0.137）. The R^2 of Fusw and MOR were lower than that of the Etru and MOR for each grade. The Eusw of all the grade lumbers, except No.3-grade, had significant correlation with the static MOE and MOR, thus the bending strengthof those grade lumbers can be estimated by the E The Etru valuesof four grade lumbers followed a sequence as No.2-grade （10.701 GPa） 〉 SS-grade （10.359 GPa） 〉 No.l-grade （9.840 GPa） 〉 No.3-grade （9.554 GPa）. For the same grade dimension lumber, its Eusw value was larger than static MOE. Mean values of MOR for four grade lumbers follow a sequence as No.2-grade （48.67 MPa） 〉 SS-grade （48.16 MPa） 〉 No.3-grade （46.55 MPa） 〉 No. 1-grade （43.39MPa）.展开更多
The effectiveness of pilodyn was tested in evaluating wood basic density, outer wood density, heartwood density, and modulus of elasticity （MoE） at 22 four-year-old eucalyptus clones in Guangxi, China. Results indic...The effectiveness of pilodyn was tested in evaluating wood basic density, outer wood density, heartwood density, and modulus of elasticity （MoE） at 22 four-year-old eucalyptus clones in Guangxi, China. Results indicated that the mean value ranged from 9.44 to 15.41 mm for Pilodyn penetration, 0.3514 to 0.4913 g.cm^-3 for wood basic density, and 3.94 to 7.53 Giga Pascal （GPa） for MoE, respectively. There were significant differences （1% level） in pilodyn penetration between different treatments, different directions and among the clones. Generally strongly negative correlations were found between pilodyn penetration and wood properties, and the coefficients ranged from -0,433 to -0,755. Our results, together with other studies, suggest that the use of pilodyn for assessing wood density and MoE was confirmed as a possibility.展开更多
Recently,many regression models have been presented for prediction of mechanical parameters of rocks regarding to rock index properties.Although statistical analysis is a common method for developing regression models...Recently,many regression models have been presented for prediction of mechanical parameters of rocks regarding to rock index properties.Although statistical analysis is a common method for developing regression models,but still selection of suitable transformation of the independent variables in a regression model is diffcult.In this paper,a genetic algorithm(GA)has been employed as a heuristic search method for selection of best transformation of the independent variables(some index properties of rocks)in regression models for prediction of uniaxial compressive strength(UCS)and modulus of elasticity(E).Firstly,multiple linear regression(MLR)analysis was performed on a data set to establish predictive models.Then,two GA models were developed in which root mean squared error(RMSE)was defned as ftness function.Results have shown that GA models are more precise than MLR models and are able to explain the relation between the intrinsic strength/elasticity properties and index properties of rocks by simple formulation and accepted accuracy.展开更多
Chemical components are the main factors affecting the mechanical properties of wood fibers. Lignin is one of the main components of wood cell walls and has a critical effect on the mechanical properties of paper pulp...Chemical components are the main factors affecting the mechanical properties of wood fibers. Lignin is one of the main components of wood cell walls and has a critical effect on the mechanical properties of paper pulp and wood fiber based composites. In this study, we carried out tensile tests on single mature latewood tracheids of Chi- nese fir （Cunninghamia lanciolata （Lamb.） Hook.）, using three different delignified treatment methods to obtain different amounts of lignin. We applied single fiber tests to study the effect of the amount of lignin on mechanical tensile proper- ties of single wood fibers at the cellular level. The results show that in their dry state, the modulus of elasticity of single fi- bers decreased with the reduction in the amount of Iignin; even their absolute values were not high. The amount of lignin affects the tensile strength and elongation of single fibers considerably. Tensile strength and elongation of single fibers increase with a reduction in the amount of lignin.展开更多
Tree improvement programs on loblolly pine(Pinus taeda) in the southeastern USA has focused primarily on improving growth, form, and disease tolerance.However, due to the recent reduction of design values for visually...Tree improvement programs on loblolly pine(Pinus taeda) in the southeastern USA has focused primarily on improving growth, form, and disease tolerance.However, due to the recent reduction of design values for visually graded southern yellow pine lumber(including loblolly pine), attention has been drawn to the material quality of genetically improved loblolly pine. In this study,we used the time-of-flight(TOF) acoustic tool to assess the effect of genetic families on diameter, slenderness, fiber length, microfibril angle(MFA), velocity and dynamic stiffness estimated using green density(DMOEG) and basic density(DMOEB) of 14-year-old loblolly pine stands selected from two sites. All the 184 and 204 trees of the selected eight half-sib genetic families on sites 1 and 2 respectively were tested using TOF acoustic tool, and two 5 mm core samples taken at breast height level(1.3 m)used to for the anatomical and physical properties analysis.The results indicated a significant positive linear relationship between dynamic MOEs(DMOEGand DMOEB)versus tree diameter, slenderness, and fiber length while dynamic MOEs negatively but nonsignificant correlated with MFA. While there was no significant difference in DMOEBbetween sites; velocity 2 for site 1 was significantly higher than site 2 but DMOEGwas higher for site 2 than site 1. Again, the mean DMOEGand DMOEBreported in the present study presents a snapshot of the expected static MOE for green and 12% moisture conditions respectively for loblolly pine. Furthermore, there were significant differences between families for most of the traits measured and this suggests that forest managers have the opportunity to select families that exhibit the desired fiber morphology for final product performance. Lastly,since the dynamic MOE based on green density(DMOEG),basic density(DMOEB) and velocity 2 present difference conclusions, practitioners of this type of acoustic technique should take care when extrapolating results across the sites.展开更多
Thorn scrub vegetation in Mexico is distributed over 50 million ha, where native tree species are the source of forage, timber, firewood and charcoal. Research describing wood durability of species from this vegetatio...Thorn scrub vegetation in Mexico is distributed over 50 million ha, where native tree species are the source of forage, timber, firewood and charcoal. Research describing wood durability of species from this vegetation type has not been fully determined, nor classified according to international standards. Thus, the aim of this study was to determine and classify the natural durability of ten woody species. Their natural durability was determined according to the European Pre-Norm 807, the loss of dynamic modulus of elasticity （MOEdyo） （MPa） was determined and wood mass loss （g） after being exposed to Trametes versicolor and Coniophora puteana fungi. Wood durability was classified accord- ing to the European Norm 350-1. Highly significant differences （p 〈 0.001） were found between the durability of woody species. The more durable species with lower MOEdyn lost were Condalia hooked （57.5% ± 0.6%）, Havardia pallens （58.2% ± 0.4%） and Acacia schaffneri （58.9% ±6.3%）. Species with lower mass loss after exposed to Coniophora puteana were Ebenopsis ebano （6.3% ±1.9%）, Condalia hooked （8.6% ±2.3%） and Cordia boissieri （11.8% ±2.3%）. E. ebano （7.1% ±2.4%）, Condalia hooked （8.2% ± 2.5%） and Cordia boissieri （11.5% ± 3.1%） showed the lower mass lost after exposed to T. versicolor. According to European Norm 350-1, three woody species were classified as very durable and durable species.展开更多
The identification of timber properties is important for safe application.Near Infrared Spectroscopy(NIRS)technology is widely-used because of its simplicity,efficiency,and positive environmental attributes.However,in...The identification of timber properties is important for safe application.Near Infrared Spectroscopy(NIRS)technology is widely-used because of its simplicity,efficiency,and positive environmental attributes.However,in its application,weak signals are extracted from complex,overlapping and changing information.This study focused on the stability of NIR modeling.The Orthogonal Partial Least Squares(OPLS)and Successive Projections Algorithm(SPA)eliminates noise and extracts effective spectra,and an ensemble learning method MIX-PLS,is applied to establish the model.The elastic modulus of timber is taken as an example,and 201 wood samples of three species,Xylosmacongesta(Lour.)Merr.,Acer pictum subsp.mono,and Betula pendula,samples were divided into three groups to investigate modelling performance.The results show that OPLS can preprocess the near-infrared spectroscopy information according to the target object in the face of the system error and reduce errors to minimum.SPA finally selects 13 spectral bands,simplifies the NIR spectral data and improves model accuracy.The Pearson's correlation coefficient of Calibration(Rc)and the Pearson's correlation coefficient of Prediction(Rp)of Mix Partial Least Squares(MIX-PLS)were 0.95 and 0.90,and Root Mean Square Error of Calibration(RMSEC)and Root Mean Square Error of Prediction(RMSEP)are 2.075 and 6.001,respectively,which shows the model has good generalization abilities.展开更多
基金This paper was supported by "Wood-inorganic Res-toration Material" in "Technique Introduction and Innovation of Bio-macromolecule New Material" of Introducing Overseas Advanced Forest Technology Innovation Program of China ("948" Innovation Pro-ject, Number: 2006-4-C03)
文摘The dynamic and static modulus of elasticity （MOE） between bluestained and non-bluestained lumber of Lodgepole pine were tested and analyzed by using three methods of Non-destructive testing （NDT）, Portable Ultrasonic Non-destructive Digital Indicating Testing （Pundit）, Metriguard and Fast Fourier Transform （FFT） and the normal bending method. Results showed that the dynamic and static MOE of bluestained wood were higher than those of non-bluestained wood. The significant differences in dynamic MOE and static MOE were found between bulestained and non-bluestained wood, of which, the difference in each of three dynamic MOE （Ep. the ultrasonic wave modulus of elasticity, Ems, the stress wave modulus of elasticity and El, the longitudinal wave modulus of elasticity） between bulestained and non-bluestained wood arrived at the 0.01 significance level, whereas that in the static MOE at the 0.05 significance level. The differences in MOE between bulestained and non-bluestained wood were induced by the variation between sapwood and heartwood and the different densities of bulestained and non-bluestained wood. The correlation between dynamic MOE and static MOE was statistically significant at the 0.01 significance level. Although the dynamic MOE values of Ep, Em, Er were significantly different, there exists a close relationship between them （arriving at the 0.01 correlation level）. Comparative analysis among the three techniques indicated that the accurateness of FFT was higher than that of Pundit and Metriguard. Effect of tree knots on MOE was also investigated. Result showed that the dynamic and static MOE gradually decreased with the increase of knot number, indicating that knot number had significant effect on MOE value.
文摘Uniaxial Compressive Strength (UCS) and modulus of elasticity (E) are the most important rock parameters required and determined for rock mechanical studies in most civil and mining projects. In this study, two mathematical methods, regression analysis and Artificial Neural Networks (ANNs), were used to predict the uniaxial compressive strength and modulus of elasticity. The P-wave velocity, the point load index, the Schmidt hammer rebound number and porosity were used as inputs for both meth-ods. The regression equations show that the relationship between P-wave velocity, point load index, Schmidt hammer rebound number and the porosity input sets with uniaxial compressive strength and modulus of elasticity under conditions of linear rela-tions obtained coefficients of determination of (R2) of 0.64 and 0.56, respectively. ANNs were used to improve the regression re-sults. The generalized regression and feed forward neural networks with two outputs (UCS and E) improved the coefficients of determination to more acceptable levels of 0.86 and 0.92 for UCS and to 0.77 and 0.82 for E. The results show that the proposed ANN methods could be applied as a new acceptable method for the prediction of uniaxial compressive strength and modulus of elasticity of intact rocks.
基金Standard system on forestry engineering of Ministry ofScience and Technology ( 2004DEA70900-1).
文摘The dimension lumber （45mm×90mm×3700mm） of plantation Chinese fir （Cunninghamia lanceolata （Lamb.） Hook.） was graded to four different classes as SS, No. 1, No.2 and No.3, according to national lumber grades authority （NLGA） for structure light framing and structure joists and planks. The properties of apparent density was determined at 15% moisture content, bending strength and stiffness were tested according to American Society for Testing and Materials （ASTM） D198-99, and dynamic modulus of elasticity （Eusw） was measured by ultrasonic technique, for predicting the flexural properties of different grade lumbers. The results showed that Eosw was larger than the static MOE. The relationship between Eusw and static MOE was significant at 0.01 level, and the determination coefficients （R2） of the four grade lumbers followed the sequence as R^2No.2 （0.616）〉 R^2ss （0.567）〉 R^2No1 （0.366）〉 R^2No.3 （0.137）. The R^2 of Fusw and MOR were lower than that of the Etru and MOR for each grade. The Eusw of all the grade lumbers, except No.3-grade, had significant correlation with the static MOE and MOR, thus the bending strengthof those grade lumbers can be estimated by the E The Etru valuesof four grade lumbers followed a sequence as No.2-grade （10.701 GPa） 〉 SS-grade （10.359 GPa） 〉 No.l-grade （9.840 GPa） 〉 No.3-grade （9.554 GPa）. For the same grade dimension lumber, its Eusw value was larger than static MOE. Mean values of MOR for four grade lumbers follow a sequence as No.2-grade （48.67 MPa） 〉 SS-grade （48.16 MPa） 〉 No.3-grade （46.55 MPa） 〉 No. 1-grade （43.39MPa）.
基金supported by the National Eleventh Five-Year Science and Technology (2006BAD01A15-4 and 2006bad24b0203)
文摘The effectiveness of pilodyn was tested in evaluating wood basic density, outer wood density, heartwood density, and modulus of elasticity （MoE） at 22 four-year-old eucalyptus clones in Guangxi, China. Results indicated that the mean value ranged from 9.44 to 15.41 mm for Pilodyn penetration, 0.3514 to 0.4913 g.cm^-3 for wood basic density, and 3.94 to 7.53 Giga Pascal （GPa） for MoE, respectively. There were significant differences （1% level） in pilodyn penetration between different treatments, different directions and among the clones. Generally strongly negative correlations were found between pilodyn penetration and wood properties, and the coefficients ranged from -0,433 to -0,755. Our results, together with other studies, suggest that the use of pilodyn for assessing wood density and MoE was confirmed as a possibility.
文摘Recently,many regression models have been presented for prediction of mechanical parameters of rocks regarding to rock index properties.Although statistical analysis is a common method for developing regression models,but still selection of suitable transformation of the independent variables in a regression model is diffcult.In this paper,a genetic algorithm(GA)has been employed as a heuristic search method for selection of best transformation of the independent variables(some index properties of rocks)in regression models for prediction of uniaxial compressive strength(UCS)and modulus of elasticity(E).Firstly,multiple linear regression(MLR)analysis was performed on a data set to establish predictive models.Then,two GA models were developed in which root mean squared error(RMSE)was defned as ftness function.Results have shown that GA models are more precise than MLR models and are able to explain the relation between the intrinsic strength/elasticity properties and index properties of rocks by simple formulation and accepted accuracy.
基金supported by the Key Program of the National Natural Science Foundation of China (Grant No. 30730076)
文摘Chemical components are the main factors affecting the mechanical properties of wood fibers. Lignin is one of the main components of wood cell walls and has a critical effect on the mechanical properties of paper pulp and wood fiber based composites. In this study, we carried out tensile tests on single mature latewood tracheids of Chi- nese fir （Cunninghamia lanciolata （Lamb.） Hook.）, using three different delignified treatment methods to obtain different amounts of lignin. We applied single fiber tests to study the effect of the amount of lignin on mechanical tensile proper- ties of single wood fibers at the cellular level. The results show that in their dry state, the modulus of elasticity of single fi- bers decreased with the reduction in the amount of Iignin; even their absolute values were not high. The amount of lignin affects the tensile strength and elongation of single fibers considerably. Tensile strength and elongation of single fibers increase with a reduction in the amount of lignin.
基金supported by the Auburn University Intramural funds
文摘Tree improvement programs on loblolly pine(Pinus taeda) in the southeastern USA has focused primarily on improving growth, form, and disease tolerance.However, due to the recent reduction of design values for visually graded southern yellow pine lumber(including loblolly pine), attention has been drawn to the material quality of genetically improved loblolly pine. In this study,we used the time-of-flight(TOF) acoustic tool to assess the effect of genetic families on diameter, slenderness, fiber length, microfibril angle(MFA), velocity and dynamic stiffness estimated using green density(DMOEG) and basic density(DMOEB) of 14-year-old loblolly pine stands selected from two sites. All the 184 and 204 trees of the selected eight half-sib genetic families on sites 1 and 2 respectively were tested using TOF acoustic tool, and two 5 mm core samples taken at breast height level(1.3 m)used to for the anatomical and physical properties analysis.The results indicated a significant positive linear relationship between dynamic MOEs(DMOEGand DMOEB)versus tree diameter, slenderness, and fiber length while dynamic MOEs negatively but nonsignificant correlated with MFA. While there was no significant difference in DMOEBbetween sites; velocity 2 for site 1 was significantly higher than site 2 but DMOEGwas higher for site 2 than site 1. Again, the mean DMOEGand DMOEBreported in the present study presents a snapshot of the expected static MOE for green and 12% moisture conditions respectively for loblolly pine. Furthermore, there were significant differences between families for most of the traits measured and this suggests that forest managers have the opportunity to select families that exhibit the desired fiber morphology for final product performance. Lastly,since the dynamic MOE based on green density(DMOEG),basic density(DMOEB) and velocity 2 present difference conclusions, practitioners of this type of acoustic technique should take care when extrapolating results across the sites.
基金supported by the Professors improvement Program (PROMEP) and the Science and Technology Support Research Program (Granted to the first author PAICyT)
文摘Thorn scrub vegetation in Mexico is distributed over 50 million ha, where native tree species are the source of forage, timber, firewood and charcoal. Research describing wood durability of species from this vegetation type has not been fully determined, nor classified according to international standards. Thus, the aim of this study was to determine and classify the natural durability of ten woody species. Their natural durability was determined according to the European Pre-Norm 807, the loss of dynamic modulus of elasticity （MOEdyo） （MPa） was determined and wood mass loss （g） after being exposed to Trametes versicolor and Coniophora puteana fungi. Wood durability was classified accord- ing to the European Norm 350-1. Highly significant differences （p 〈 0.001） were found between the durability of woody species. The more durable species with lower MOEdyn lost were Condalia hooked （57.5% ± 0.6%）, Havardia pallens （58.2% ± 0.4%） and Acacia schaffneri （58.9% ±6.3%）. Species with lower mass loss after exposed to Coniophora puteana were Ebenopsis ebano （6.3% ±1.9%）, Condalia hooked （8.6% ±2.3%） and Cordia boissieri （11.8% ±2.3%）. E. ebano （7.1% ±2.4%）, Condalia hooked （8.2% ± 2.5%） and Cordia boissieri （11.5% ± 3.1%） showed the lower mass lost after exposed to T. versicolor. According to European Norm 350-1, three woody species were classified as very durable and durable species.
基金supported financially by the China State Forestry Administration“948”projects(2015-4-52)Heilongjiang Natural Science Foundation(C2017005)。
文摘The identification of timber properties is important for safe application.Near Infrared Spectroscopy(NIRS)technology is widely-used because of its simplicity,efficiency,and positive environmental attributes.However,in its application,weak signals are extracted from complex,overlapping and changing information.This study focused on the stability of NIR modeling.The Orthogonal Partial Least Squares(OPLS)and Successive Projections Algorithm(SPA)eliminates noise and extracts effective spectra,and an ensemble learning method MIX-PLS,is applied to establish the model.The elastic modulus of timber is taken as an example,and 201 wood samples of three species,Xylosmacongesta(Lour.)Merr.,Acer pictum subsp.mono,and Betula pendula,samples were divided into three groups to investigate modelling performance.The results show that OPLS can preprocess the near-infrared spectroscopy information according to the target object in the face of the system error and reduce errors to minimum.SPA finally selects 13 spectral bands,simplifies the NIR spectral data and improves model accuracy.The Pearson's correlation coefficient of Calibration(Rc)and the Pearson's correlation coefficient of Prediction(Rp)of Mix Partial Least Squares(MIX-PLS)were 0.95 and 0.90,and Root Mean Square Error of Calibration(RMSEC)and Root Mean Square Error of Prediction(RMSEP)are 2.075 and 6.001,respectively,which shows the model has good generalization abilities.
