Visual and machine strength gradings of Scots and red pine structural timber pieces from Türkiye

Fatih Kurul, Nusret As
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Abstract

Scots (Pinus sylvestris L.) and red pine (Pinus brutia Ten.) structural timbers (540 pieces) from Türkiye were first visually graded according to TS 1265 (2012). Then, non-destructive tests were conducted using vibration and time of flight (ToF) methods, followed by destructive tests on a four-point bending test setup according to EN 408 (2012). The vibration method showed a higher correlation than ToF with strength and stiffness. The dynamic modulus of elasticity (MOEd) obtained by the vibration method was 12.3% and 15.4% lower in Scots and red pine, respectively, compared to the ToF method. Mechanical testing determined local MOE was 14% and 15% higher than global MOE for Scots and red pine, respectively. An alternative formula to the existing conversion formula in EN 384 (2018) was derived. The average bending strength of red pine was 7% higher than Scots pine. For visual strength grading, local and global MOE in Scots pine, class 1, 2, and 3 structural timbers were assigned to C35, C27, and C22, respectively. Red pine was assigned to C40, C27, and C24 for local MOE and C35, C24, and C22 for global MOE. In machine strength grading, the grade combination was C40-C30-C22-C16-R for both species. The best results were achieved in settings where vibration method and local MOE were used together. Machine strength grading achieved higher efficiency than visual strength grading.
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图尔基耶苏格兰和红松结构木材的目测和机械强度分级
首先根据 TS 1265(2012)标准对来自土耳其的苏格兰松(Pinus sylvestris L.)和红松(Pinus brutia Ten.)结构木材(540 块)进行目测分级。然后,使用振动和飞行时间(ToF)方法进行了非破坏性测试,随后根据 EN 408(2012)在四点弯曲测试装置上进行了破坏性测试。振动法与强度和刚度的相关性高于飞行时间法。与 ToF 方法相比,振动方法获得的苏格兰松木和红松的动态弹性模量(MOEd)分别低 12.3% 和 15.4%。机械测试确定的苏格兰松木和红松的局部 MOE 分别比整体 MOE 高 14% 和 15%。得出了 EN 384(2018)中现有转换公式的替代公式。红松的平均抗弯强度比苏格兰松高 7%。对于苏格兰松木的视觉强度分级、局部和整体 MOE,1 级、2 级和 3 级结构木材分别被定为 C35、C27 和 C22。红松的局部 MOE 为 C40、C27 和 C24,整体 MOE 为 C35、C24 和 C22。在机器强度分级中,两种树种的等级组合均为 C40-C30-C22-C16-R。在同时使用振动法和局部暴露限的情况下,结果最好。机器强度分级的效率高于目测强度分级。
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