Research Article
Year 2014,
Volume: 10 Issue: 2, 11 - 17, 29.01.2017
Abstract
In this study; bending properties of Black pine wood (Pinus nigra A.) were predicted using stress – wave method and compared with static bending tests. By using the density, moisture, and dimensions of the samples in MTG Timber Grader device, dynamic modulus of elasticity values were determined. And then, samples were subjected to 3 point bending test. Modulus of elasticity and bending strengths were calculated using load – deformation curves. Regression models were developed to interpret relationships between dynamic modulus elasticity and bending properties. Results showed that there is a high regression coefficient 0.74 between dynamic modulus of elasticity and static modulus of elasticity. Regression coefficient between dynamic modulus of elasticity and static bending strength was measured as 0.42 and regression coefficient between static modulus of elasticity and static bending strength was measured as 0.53. Results indicate that modulus of elasticity for Black pine lumber can be predicted using stress wave method, but more tests should be conducted in order to interpret bending strength.
References
- Alptekin C Ü, 1986. Karaçam’ın (Pinus nigra ssp. pallasiana Lamb. Holmboe) Coğrafik Varyasyonları, İ.Ü. Fen Bilimleri Enstitüsü, Doktora Tezi (Yayınlanmamış), 170 s.,İstanbul,
- ASTM D 198. 2003. Standard test methods of static tests of lumber in structural sizes. Annual Book of ASTM Standards,” West Conshohocken, PA, USA,
- Barrett J D, Lam F and Chen Y. 2008. Comparison of machine grading methods for Canadian hemlock, In: Proceedings of 10th WCTE Miyazaki, Japan,
- Biechele T, Chui Y H and Gong M. 2010. Assessing stiffness on finger-jointed timber with different non-destructive testing techniques, In: The Future of Quality Control for Wood & Wood Products, 4-7th May 2010, The Final Conference of COST Action E53, Edinburgh,
- Bucur V. 2006. Acoustics of Wood, Springer-Verlag, Berlin,
- Dıvós F and Tanaka T. 2005. Relation between static and dynamic modulus of elasticity of wood, Acta Silv. Lign. Hung. 1, 105-110,
- Esteban L G, Fernandez F G and de Palacios P. 2009. MOE prediction in Abies pinsapo Boiss. timber: Application of an artificial neural network using non-destructive testing, Computers and Structures 87, 1360-1365,
- Galligan W L and McDonald K A. 2000. Machine grading of lumber. Practical concerns for lumber producers, General Technical Report FPL-GTR-7, USDA Forest Service,
- Guntekin E, Emiroglu Z G and Yılmaz T. 2013. Prediction of bending properties for Turkish Red Pine Lumber using Stress Wave Method. BioResources 8(1): 231-237,
- Guntekin E, Ozkan S and Yilmaz T. 2014. Prediction of Bending Properties For Beech Lumber Using Stress Wave Method. Maderas. Ciencia y tecnología 16(1): 93-98,
Year 2014,
Volume: 10 Issue: 2, 11 - 17, 29.01.2017
Abstract
Bu çalışmada karaçam (Pinus nigra A.) kerestesinde eğilme özellikleri stres dalga yöntemi kullanılarak tahmin edilmiş ve statik eğilme testleri ile karşılaştırılmıştır. Çalışmanın ilk aşamasında, kerestelerin yoğunluk, rutubet ve ebatları MTG kereste sınıflandırma cihazına girilerek dinamik elastikiyet modülü (Edyn) değerleri okunmuştur. Çalışmanın ikinci aşamasında ise kerestelere üç nokta eğilme testleri uygulanmıştır. Statik elastikiyet modülü (Estat) ve eğilme direnç (ED) değerleri eğilme testlerinden elde edilen yük – deformasyon eğrileri yardımıyla hesaplanmıştır. Regresyon modelleri kullanılarak Edyn ile eğilme özellikleri arasındaki ilişkiler ortaya konmuştur. Çalışma sonuçlarına göre Edyn ile Estat arasında elde edilen regresyon katsayısı 0.74 bulunurken Edyn ile ED ve Estat ile ED arasında elde edilen regresyon katsayıları sırasıyla 0.42 ve 0.53 olmuştur. Çalışma sonuçlarına göre Karaçam kerestesinde elastikiyet modülü stres dalga yöntemiyle tahmin edilebilir ancak eğilme direnci için daha fazla teste ihtiyaç duyulmaktadır.
Keywords
References
- Alptekin C Ü, 1986. Karaçam’ın (Pinus nigra ssp. pallasiana Lamb. Holmboe) Coğrafik Varyasyonları, İ.Ü. Fen Bilimleri Enstitüsü, Doktora Tezi (Yayınlanmamış), 170 s.,İstanbul,
- ASTM D 198. 2003. Standard test methods of static tests of lumber in structural sizes. Annual Book of ASTM Standards,” West Conshohocken, PA, USA,
- Barrett J D, Lam F and Chen Y. 2008. Comparison of machine grading methods for Canadian hemlock, In: Proceedings of 10th WCTE Miyazaki, Japan,
- Biechele T, Chui Y H and Gong M. 2010. Assessing stiffness on finger-jointed timber with different non-destructive testing techniques, In: The Future of Quality Control for Wood & Wood Products, 4-7th May 2010, The Final Conference of COST Action E53, Edinburgh,
- Bucur V. 2006. Acoustics of Wood, Springer-Verlag, Berlin,
- Dıvós F and Tanaka T. 2005. Relation between static and dynamic modulus of elasticity of wood, Acta Silv. Lign. Hung. 1, 105-110,
- Esteban L G, Fernandez F G and de Palacios P. 2009. MOE prediction in Abies pinsapo Boiss. timber: Application of an artificial neural network using non-destructive testing, Computers and Structures 87, 1360-1365,
- Galligan W L and McDonald K A. 2000. Machine grading of lumber. Practical concerns for lumber producers, General Technical Report FPL-GTR-7, USDA Forest Service,
- Guntekin E, Emiroglu Z G and Yılmaz T. 2013. Prediction of bending properties for Turkish Red Pine Lumber using Stress Wave Method. BioResources 8(1): 231-237,
- Guntekin E, Ozkan S and Yilmaz T. 2014. Prediction of Bending Properties For Beech Lumber Using Stress Wave Method. Maderas. Ciencia y tecnología 16(1): 93-98,
There are 10 citations in total.
Details
| Journal Section | İç Anadolu’da Ağaçlandırma Çalışmaları |
|---|---|
| Authors | |
| Publication Date | January 29, 2017 |
| Published in Issue | Year 2014 Volume: 10 Issue: 2 |
........