Properties of solid wood and laminated wood lumber manufactured by cold pressing and heat treatment

Kwon, Jin Kyung; Shin, Rang-Ho; Ayrılmış, Nadir; Han, Tae Hyung

doi:10.1016/j.matdes.2014.05.032

Cited by 20 publications

(12 citation statements)

References 14 publications

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“…Forestry sector represents 1,1% of the gross national product in Brazil (IBA, 2014), and the biomass produced can be used for cellulose pulp (PIRRALHO et al, 2014), energy (SOARES et al, 2014;ZANUNCIO et al, 2014a), panels CARVALHO et al, 2014b), and lumber production (KWON et al, 2014;SALCA;HIZIROGLU, 2014). In all these sectors, wood drying is necessary.…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Networks as a New Tool for Assessing and Monitoring Wood Moisture Content

et al. 2016

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-Drying of wood is necessary for its use and moisture control is important during this process. The aim of this study was to use artificial neural networks to evaluate and monitor the wood moisture content during drying. Wood samples of 2 × 2 × 4 cm were taken at 1.3 m above the ground, outside of radial direction, from seven 2-year-old materials and three 7-year-old materials. These samples were saturated and drying was evaluated until the equilibrium moisture content, then, the artificial neural networks were created. The materials with higher initial moisture reached equilibrium moisture content faster due to its higher drying rate. The basic density of all wood materials was inversely proportional at the beginning and directly proportional to the moisture at the end of drying. All artificial neural networks used in this work showed high accuracy to estimate the moisture, however, the neural network based on the basic density and drying days was the best. Therefore, artificial neural networks can be used to control the moisture content of wood during drying.Keywords: Eucalyptus urophylla × Eucalyptus grandis; Drying; Modeling.REDES NEURAIS ARTIFICIAIS COMO NOVA FERRAMENTA PARA AVALIAÇÃO E MONITORAMENTO DA UMIDADE DA MADEIRA RESUMO -A secagem da madeira é necessária para sua utilização e o controle da umidade é fundamental durante este processo. O objetivo deste trabalho foi utilizar redes neurais artificiais para avaliar e monitorar a umidade da madeira durante a secagem. Amostras de 2 x 2 x 4 cm foram retiradas a 1,3 metros acima do solo na parte externa no sentido radial de sete materiais de dois anos e três de sete anos de Eucalyptus urophylla x Eucalyptus grandis. Essas amostras foram saturadas e sua secagem avaliada até a umidade de equilíbrio, logo após, foram criadas as redes neurais artificiais. Os materiais com maior umidade inicial atingiram a umidade de equilíbrio mais rápido, devido a maior taxa de secagem. A densidade básica da madeira de todos os materiais foi inversamente proporcional no inicio e diretamente proporcional à umidade no final da secagem. A rede neural artificial baseada na densidade básica e nos dias de secagem apresentou alta precisão para avaliar e monitorar a umidade da madeira. Portanto, as redes neurais artificiais podem ser utilizadas para controle da umidade da madeira durante a secagem.Palavras-chave: Eucalyptus urophylla × Eucalyptus grandis; Modelagem; Secagem. 544Revista Árvore, Viçosa-MG, v.40, n.3, p.543-549, 2016 ZANUNCIO, A.J.V. et al.

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Section: Introductionmentioning

confidence: 99%

Artificial Neural Networks as a New Tool for Assessing and Monitoring Wood Moisture Content

et al. 2016

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“…Nevertheless, the drawback of using plantation timbers is mostly related to their low density, mechanical strength, and dimensional stability [6]. Densification has been reported for over a century as an efficient method for enhancing wood mechanical properties by reducing porosity and increasing density [7]. Densification is proven to improve mechanical properties such as modulus of elasticity (MOE), surface hardness, and mechanical strength of wood, especially for low-density…”

Section: Introductionmentioning

confidence: 99%

Functionalized Surface Layer on Poplar Wood Fabricated by Fire Retardant and Thermal Densification. Part 1: Compression Recovery and Flammability

Chu

Avramidis

et al. 2019

Forests

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To enhance compression stability and fire retardancy of densified wood, a new modification method i.e., combined nitrogen–phosphorus (NP) fire retardant pre-impregnation with surface thermo-mechanical densification is used to fabricate a certain thickness of functionalized surface layer on poplar. This combined treated wood is investigated via vertical density profile (VDP), and the compression stability is revealed by both soaking test and cone analysis. Results demonstrate that the combined treatment hardened the surface of wood and reformed the interface combination of the NP with the wood cell wall, thus making the surface tissue more close-grained. Fire retardancy was also enhanced; the total heat release and CO generation values decreased by 21.9% and 68.4%, respectively, when compared with that of solely NP-treated wood. Moreover, surface hardness increased by 15.8%, and the recovery of surface hardness and thickness were 56.8% and 77.2% lower than that of simply densified wood. It appears that this NP-involved thermal densification could be considered as an alternative approach to enhance both the compression stability and fire resistance of wood.

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“…Furthermore, densifi cation is a way of utilizing low-density wood species instead of high density species in applications of higher value (Kariz et al, 2017). The mechanical properties and dimensional stability of low-density wood can be improved by the heat-treatment in modifi cation chamber followed by densifi cation process (Kwon et al, 2014). This will give a signifi cant advantage to the densifi ed wood for structural applications, which require stiffness, hardness, strength in building industry.…”

Section: Introduction 1 Uvodmentioning

confidence: 99%

Surface roughness and wettability of surface densified heat-treated Norway spruce (Picea abies L. Karst.)

et al. 2019

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Surface roughness and wettability of the heat-treated and then surface densified spruce (Picea abies L. Karst.) wood were measured to determine the effect of densification and heat-treatment on wood surface properties. The process of heat-treatment with an initial vacuum was performed in a vacuum chamber on oven dried lamellas with dimensions of 630 mm (longitudinal direction) x 45 mm (tangential direction) x 25 mm (radial direction). The lamellas were heat-treated at four different temperatures which were 170 °C, 190 °C, 210 °C and 230 °C. Control specimens were not exposed to heat-treatment. The lamellas were first heated to 100 °C, the creation of a vacuum taking 30 min at this temperature, and then heated to the desired temperature, and treated at this constant temperature for 3 h. The lamellas were then cooled down by using coils with cold water inside the chamber. Surface densification of lamellas with compression from 22 mm to 15 mm thickness was made by press platens heated at 150 °C and held in that position for 60 s. After the 1 min, the heated platen was cooled to 90 °C, whilst the specimen remained under compression to minimize immediate spring back. The total time of compression was 2 min (30 s closing, 60 s pressing and approx. 30 s cooling). In the treatment groups, the optimum treatment temperature on the one-side densified wood specimens was found to be 170 °C based on the surface roughness and wettability values. Surface densification significantly decreased the surface roughness of the wood specimens. The surface quality of wood can be improved when the wood is exposed to the heat-treatment and then surface densification.

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Properties of solid wood and laminated wood lumber manufactured by cold pressing and heat treatment

Cited by 20 publications

References 14 publications

Artificial Neural Networks as a New Tool for Assessing and Monitoring Wood Moisture Content

Artificial Neural Networks as a New Tool for Assessing and Monitoring Wood Moisture Content

Functionalized Surface Layer on Poplar Wood Fabricated by Fire Retardant and Thermal Densification. Part 1: Compression Recovery and Flammability

Surface roughness and wettability of surface densified heat-treated Norway spruce (Picea abies L. Karst.)

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