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DOI 10.1007/s00107-008-0248-2
DOI 10.1007/s00107-010-0516-9
The behaviour of cork under tensile stress in the tangential direction was evaluated in relation
with its structural characteristics
Cork is known as the material used for the production of wine stoppers. The specific properties of
cork, e.g. low density, very low permeability to water, elastic properties and inertness have made it the
best sealant for quality wine. Here we studied the relation between compression, tensile and bending
stress in cork and the influence of structural characteristics of cork on its mechanical behaviour. The
material was sampled from raw cork planks of good quality (class 1) and poor quality (class 4) collected at
one industrial mill after post-harvest six-month air stabilization, water boiling and air drying as usually
applied in cork industrial processing. The samples had densities ranging 0.123 - 0.203 g.cm-3 and
porosities between 0.5 and 22.0%.
There are differences between the type of stress and the corresponding direction of stress. For
the same direction of stress, the Young modulus in tension is higher then in bending and it is lowest in
compression. The bending Young modulii were well correlated with the tensile Young modulii, because
while in bending the sample is submitted to both tensile and compression stresses, the fracture occurs in
the tensile zone. There were no significant differences in the mechanical properties of cork samples
obtained from cork planks of different quality classes but the density is an important factor and samples
with higher density showed overall larger resistance. Mechanical properties were influenced by the
structural features related to the lenticular channels, namely the presence of thick walled and lignified cells
that may border the lenticular channels.
Comunicação oral da qual só está disponível o resumo.
In this paper, the morphological properties of fiber length (weighted in length) and
of fiber width of unbleached Kraft pulp of Acacia melanoxylon were determined using TECHPAP
Morfir equipment (Techpap SAS, Grenoble, France), and were used in the calibration development
of Near Infrared (NIR) partial least squares regression (PLS-R) models based on the spectral data
obtained for the wood. It is the first time that fiber length and width of pulp were predicted with
NIR spectral data of the initial woodmeal, with high accuracy and precision, and with ratios of
performance to deviation (RPD) fulfilling the requirements for screening in breeding programs.
The selected models for fiber length and fiber width used the second derivative and first derivative
+ multiplicative scatter correction (2ndDer and 1stDer + MSC) pre-processed spectra, respectively,
in the wavenumber ranges from 7506 to 5440 cm 1. The statistical parameters of cross-validation
(RMSECV (root mean square error of cross-validation) of 0.009 mm and 0.39 m) and validation
(RMSEP (root mean square error of prediction) of 0.007 mm and 0.36 m) with RPDTS (ratios of
performance to deviation of test set) values of 3.9 and 3.3, respectively, confirmed that the models
are robust and well qualified for prediction. This modeling approach shows a high potential to be
used for tree breeding and improvement programs, providing a rapid screening for desired fiber
morphological properties of pulp prediction.
In this paper, the morphological properties of fiber length (weighted in length) and of fiber width of unbleached Kraft pulp of Acacia melanoxylon were determined using TECHPAP Morfi® equipment (Techpap SAS, Grenoble, France), and were used in the calibration development of Near Infrared (NIR) partial least squares regression (PLS-R) models based on the spectral data obtained for the wood. It is the first time that fiber length and width of pulp were predicted with NIR spectral data of the initial woodmeal, with high accuracy and precision, and with ratios of performance to deviation (RPD) fulfilling the requirements for screening in breeding programs. The selected models for fiber length and fiber width used the second derivative and first derivative + multiplicative scatter correction (2ndDer and 1stDer + MSC) pre-processed spectra, respectively, in the wavenumber ranges from 7506 to 5440 cm−1. The statistical parameters of cross-validation (RMSECV (root mean square error of cross-validation) of 0.009 mm and 0.39 μm) and validation (RMSEP (root mean square error of prediction) of 0.007 mm and 0.36 μm) with RPDTS (ratios of performance to deviation of test set) values of 3.9 and 3.3, respectively, confirmed that the models are robust and well qualified for prediction. This modeling approach shows a high potential to be used for tree breeding and improvement programs, providing a rapid screening for desired fiber morphological properties of pulp prediction.
Aim of the study: The ability of NIR spectroscopy for predicting the ISO brightness was studied on unbleached Kraft pulps of Acacia melanoxylon R. Br.
Area of study: Sites covering littoral north, mid interior north and centre interior of Portugal.
Materials and methods: The samples were Kraft pulped in standard identical conditions targeted to a kappa number of 15. A Near Infrared (NIR) partial least squares regression (PLSR) model was developed for the ISO brightness prediction using 75 pulp samples with a variation range of 18.9 to 47.9 %.
Main results: Very good correlations between NIR spectra and ISO brightness were obtained. Ten methods were used for PLS analysis (cross validation with 48 samples), and a test set validation was made with 27 samples. The 1stDer pre-processed spectra coupling two wavenumber ranges from 9404 to 7498 cm-1 and 4605 to 4243 cm-1 allowed the best model with a root mean square error of ISO brightness prediction of 0.5 % (RMSEP), a r2 of 99.5 % with a RPD of 14.7.
Research highlights: According to AACC Method 39-00, the present model is sufficiently accurate to be used for process control (RPD ≥ 8).
Pulp yield is an important measure of pulpwood quality, which is used regularly by the pulp and paper industry for which the possibility of using rapid methods to predict pulp yield would be very useful for screening and quality control. This work addresses the prediction of Kraft pulp yield under standard identical conditions and targeted to a kappa number of 15, using near-infrared (NIR) partial least squares regression modelling. A total of 75 pulp samples of Acacia melanoxylon R. Br. (blackwood) with a pulp yield variation range of 47.0–58.2 % were used. Very good correlations between NIR spectra and pulp yield were obtained. Ten methods were used for PLS analysis (cross-validation with 62 samples), and an external validation was made with 13 samples. The 2ndDer pre-processed spectra coupling two wavenumber ranges from 9087 to 5440 and 4605 to 4243 cm−1 allowed the best model with a standard error of prediction of 0.4 %, a r2 of 98.1 %, and the ratios of performance to deviation (RPDTS) of 4.8. According to AACC Method 39-00, the present model is sufficiently accurate to be used in screening programs and in quality control (RPDCV = 6.9).
Together the forest and industrial activities within the Portuguese forest sector have a
great importance in the national economy. The most used wood species in Portugal for industry
(wood panel, sawmill, wood crates) are pine and eucalypt, which leads to extreme dependence
and competition between the various industries for the same material, and thus unsustainable
pressure on these forest resources. This is one of the causes of the decrease of pinewood area in
recent years. On the other hand, this dependence leads to extensive areas of forest monocultures
and, subsequently, increased risk of the forest fire propagation.
This work intends to stimulate the diversification of the wood products used in the
national industry of pulp and to provide a pulp with appropriate characteristics for incorporation
as fibber for paper reinforcement. At the level of forest producers, the use of this prime-material
would increase competitiveness among tree species and revitalization of less favoured rural areas
and, turning them into a possible solution for the lack of wood and an incentive to the
reforestation of these areas.
Wood from species Cupressus sempervirens and Cupressus arizonica, Acacia delbata
and Acacia melanoxylon were analysed. Content of extractives and of Klason lignin, fibre length
and coarseness were determined. Representative wood samples from Pinus pinaster grown in
Portugal and from Pinus sylvestris grown in Finland were used as reference. The wood from
Cupressus sempervirens showed lower Klason lignin and a fibre quality that appears to be more
adequate to pulp and paper.
Acacia species, with their relatively short, flexible and collapsible fibres, have potential
to produce papers with good relationships light scattering/tensile strength and smoothness/tensile
strength, at low energy consumption in refining. The studied acacia species showed slightly
better performance in pulping than the Eucalyptus globulus sample used as a comparison.
Comunicação apresentada no 5.º Congresso Florestal Nacional que decorreu em Viseu em Maio de 2005.
Só está disponível o resumo da comunicação
The aim of this study was to incorporate ring width data into sawing yield strudies through simulation and tree modelling techniques. Results on data analysis measuring anual growth variation contribute also to the raw material characterisation.
Com este trabalho pretende-se dar um contributo para o estudo dos factores de variação radial e axial da espessura dos anéis de crescimento de pinheiro bravo. O trabalho foi desenvolvido com base em técnicas de análise de imagem e tem como objectivo final incluir a variação dos anéis de crescimento na qualidade dos produtos finais serrados da madeira desta espécie.
A informação para o estudo da variação das camadas de crescimento baseou-se numa amostra de tiras radiais e de discos nos níveis de altura 0, 5, 10, 15, 17 e 20 m de árvores de quatro estações em Portugal. A amostragem em discos permitiu a medição das camadas de crescimento em várias direcções e a posterior criação de um modelo tridimensional do tronco com base nos anéis de crescimento.
A variação das camadas de crescimento foi analisada em sequência vertical, onde se analisam os anéis de crescimento em cada nível, obtendo-se assim o crescimento das árvores e quais as suas variação ao longo do tempo, e em sequência oblíqua onde se pode analisar o comportamento dos 13 anos terminais ao longo da árvore. Efectuou-se uma análise de variância para diferentes factores onde se contabilizou a percentagem de variação correspondente a cada um desses factores. Verificou-se que a maior parte da variação se deve à variação lenho juvenil/lenho adulto.
O modelo tridimensional do tronco foi desenvolvido numa interface que permite observar a variação das camadas de crescimento nas diferentes secções transversais a níveis de altura especificados. De futuro este modelo será integrado na reconstrução tridimensional já desenvolvida para o Pinheiro bravo e que descreve a geometria do tronco e os anéis internos. O objetcivo final será o uso da informação sobre as camadas de crescimento em programas de simulação de serração de forma a constituir mais um parâmetro de qualidade dos produtos finais.
A total of 120 Acacia melanoxylon R. Br. (Australian blackwood) stem discs, belonging to 20 trees from four sites in Portugal, were used in this study. The samples were kraft pulped under standard identical conditions targeted to a Kappa number of 15. A Near Infrared (NIR) partial least squares regression (PLSR) model was developed for the Kappa number prediction using 75 pulp samples with a narrow Kappa number variation range of 10 to 17. Very good correlations between NIR spectra of A. melanoxylon pulps and Kappa numbers were obtained. Besides the raw spectra, also pre-processed spectra with ten methods were used for PLS analysis (cross validation with 48 samples), and a test set validation was made with 27 samples. The first derivative spectra in the wavenumber range from 6110 to 5440 cm-1 yielded the best model with a root mean square error of prediction of 0.4 units of Kappa number, a coefficient of determination of 92.1%, and two PLS components, with the ratios of performance to deviation (RPD) of 3.6 and zero outliers. The obtained NIR-PLSR model for Kappa number determination is sufficiently accurate to be used in screening programs and in quality control.
Só está disponível resumo.
The compression properties of cork were studied on samples grouped in three density classes: 0.11 - 0.15, 0.15 - 0.19 and 0.19 - 0.25 g cm3. In all cases, cork had higher strenght for the radial compression. There were significant differences between cork samples with higher density showed overall larger resistance to compression in the three directions.
The aim of this work is to develop a tool to predict some pulp properties e.g., pulp yield, Kappa number, ISO brightness (ISO 2470:2008), fiber length and fiber width, using the sapwood and heartwood proportion in the raw-material. For this purpose, Acacia melanoxylon trees were collected from four sites in Portugal. Percentage of sapwood and heartwood, area and the stem eccentricity (in N-S and E-W directions) were measured on transversal stem sections of A. melanoxylon R. Br. The relative position of the samples with respect to the total tree height was also considered as an input variable. Different configurations were tested until the maximum correlation coefficient was achieved. A classical mathematical technique (multiple linear regression) and machine learning methods (classification and regression trees, multi-layer perceptron and support vector machines) were tested. Classification and regression trees (CART) was the most accurate model for the prediction of pulp ISO brightness (R = 0.85). The other parameters could be predicted with fair results (R = 0.64–0.75) by CART. Hence, the proportion of heartwood and sapwood is a relevant parameter for pulping and
pulp properties, and should be taken as a quality trait when assessing a pulpwood resource.
A tool to predict the tensile properties of cork was applied in order to be used for material and application selection. The mechanical behaviour of cork under tensile stress was determined in the tangential and axial direction. Cork planks of two commercial quality classes were used and samples were taken at three radial positions in the planks.For the construction of the predictive model, nine properties were measured: mechanical properties (Young’s modulus, fracture stress and fracture strain) and the physical properties (porosity, number of pores, density, approximation of the pores to elliptical and circular shape and distance to the nearest pore). The aim of this research work was to predict the mechanical properties from the physical properties using neural networks.Initially, the problem was approached as a regression problem, but the poor correlation coefficients obtained made the authors define a classification problem. The criterion used for the classification problem was the test error rate, training the neural network with a variety of neurons in the hidden layer until the minimum error was achieved. The influence of each individual variable was also studied in order to evaluate their importance for the prediction of the mechanical properties.The results show that the Young’s modulus and fracture stress can be predicted with an error rate in test of 10.6 and 10.2 %, respectively, being the measure of the approximation of the pores to elliptical shape avoidable. Regarding the fracture strain, its prediction from physical properties implies an excessive error.
Só está disponível o resumo.
info:eu-repo/semantics/publishedVersion
In this paper we report new data about two wood species that could play a role in the Portuguese forest as raw material for the paper industry: Cupressus arizonica and Cupressus sempervirens. Results on the behaviour of wood samples taken from 16 year-old trees, (two per species and two height levels), have shown lower kraft pulp yields than reference pine softwoods, as a consequence of higher lignin content. The pulps from C. sempervirens present values of fibre lenght and coarseness slightly lower than the Nordic Pinus sylvestris, but properties of pulp fibres from C. arizonica are significantly lower.
DOI 10.1007/s10086-012-1286-2
Wood samples of Cupressus arizonica, C. lusitanica, and C. sempervirens were evaluated for chemical, anatomical, and pulp characteristics as raw material for pulp production. Two 17-year-old trees per species were harvested, and wood samples were taken at a height of 2 m. Wood chips from Pinus pinaster (Portugal) and P. sylvestris (Finland) were used as references. C. arizonica differed from C. lusitanica and C. sempervirens with significantly lower (p < 0.05) tracheid diameter and wall thickness in the earlywood. The total extractives contents were 3.9%, 3.3%, and 2.5% for C. lusitanica, C. sempervirens, and C. arizonica, respectively, lower than the 5.1% for P. pinaster and 4.5% for P. sylvestris. Klason lignin content ranged from 33.0 to 35.6%, higher than the 28.0 to 28.7% for the pinewoods. The kraft pulp yields for C. arizonica, C. lusitanica, and C. sempervirens were 37.7%, 36.7%, and 38.7%, respectively, with kappa numbers of 32.0, 31.6, and 28.7, respectively; the yield values were 40.8% and 42.8%, with kappa numbers of 23.4 and 21.0, for P. pinaster and P. sylvestris, respectively. The cypress species are clearly different from pine in relation to wood pulping behavior. Among the cypress, C. sempervirens provided the best pulping results
In this study, the accuracy of mathematical techniques such as multiple linear regression, clustering, decision trees (CART) and neural networks was evaluated to predict Young’s modulus, compressive stress at 30% strain and instantaneous recovery velocity of cork. Physical properties, namely test direction, density, porosity and pore number, as well as test direction were used as input. The better model was achieved when a classification problem was performed. Only compressive stress at 30% strain can be predicted with neural networks with an error rate of about 20%. The prediction of Young’s modulus and instantaneous recovery velocity led to unacceptably high error rates due to the heterogeneity of the material.
Neste trabalho desenvolveu-se um modelo para estimar a densidade básica na madeira da Acacia melanoxylon po NIR.
Paper properties determine the product application potential and depend on the raw material, pulping conditions,and pulp refining. The aim of this study was to construct mathematical models that predict quantitative relations between the paper density and various mechanical and optical properties of the paper. A dataset of properties of paper handsheets produced with pulps of Acacia dealbata, Acacia melanoxylon, and Eucalyptus globullus beaten at 500, 2500, and 4500 revolutions was used. Unsupervised classification techniques were combined to assess the need to perform separated prediction models for each species, and multivariable regression techniques were used to establish such prediction models. It was possible to develop models with a high goodness of fit using paper density as the independent variable (or predictor) for all variables except tear index and zero-span tensile strength, both dry and wet.
Prediction paper properties based on a limited number of measured variables can be an important tool for the industry. Mathematical models were developed to predict mechanical and optical properties from the corresponding paper density for some softwood papers using support vector machine regression with the Radial Basis Function Kemel. A dataset of different properties of paper handsheets produced from pulps of pine (Pinus pinaster and P. sylvestris) and cypress species (Cupressus lusitanica, C. sempervirens e C. arizonica) beaten at 1000, 4000, and 7000 revolutions was used. The results show that it is possible to obtain good models (with high coefficient of determination) with two variables: the numerical variable density and the categorical variable density.
Paper properties determine the product application potential and depend on the raw material, pulping conditions, and pulp refining. The aim of this study was to construct mathematical models that predict quantitative relations between the paper density and various mechanical and optical properties of the paper. A dataset of properties of paper handsheets produced with pulps of Acacia dealbata, Acacia melanoxylon, and Eucalyptus globulus beaten at 500, 2500, and 4500 revolutions was used. Unsupervised classification techniques were combined to assess the need to perform separated prediction models for each species, and multivariable regression techniques were used to establish such prediction models. It was possible to develop models with a high goodness of fit using paper density as the independent variable (or predictor) for all variables except tear index and zero-span tensile strength, both dry and wet.
O género Acácia inclui numerosas espécies, algumas economicamente importantes, que ocorrem naturalmente em zonas áridas na Austrália, Ásia, África e América. Em Portugal espécies destes género foram introduzidas no início do século XX, em solos secos e arenosos ao longo da costa. A Acacia melanoxylon apesar de bem adaptada às condições ecológicas do país, não tem sido aproveitada, em parte devido ao desconhecimento das suas propriedades.
