Yield optimization and surface image-based strength prediction of beech

Wood is a strongly anisotropic and heterogeneous material with natural defects that are affecting the uniform scatter of the fiber patterns. European beech (Fagus sylvatica) is the species, used for this study. The logs of these species have generally complicated shapes with frequent curvatures, which is in contrast to most of the softwood...

Strength grading of hardwoods using transversal ultrasound

Detection of local wood inhomogeneities is important for accurate strength and stiffness prediction. In hardwood specimens, visual characteristics (e.g. knots or fibre deviation) are difficult to detect, either with a visual surface inspection or by the machine. Transversal ultrasound scan (TUS) is a non-destructive evaluation method with high...

Machine strength and stiffness prediction with focus on different acoustic measurement methods

Strength grading is an important step for the production of homogenous and high-quality solid wood material. In particular, for hardwoods, the use of non-visible characteristics is indispensable. Dynamic MOE (MOEdyn) is an important parameter widely used for grading of softwoods and applicable to hardwoods as well. There are two common ways to...

Tensile strength classes for hardwoods

Generally, for structural timber the main properties are listed in a strength class system. In Europe EN 338 (2016) lists available strength class and their respective characteristic properties. Depending on the product application the bending or the tension properties are of main interest. For glulam lamellas, tension classes are preferred as...

Optimizing characteristic properties of visually graded soft- and hardwoods lamellas for the glulam production

For the production of lamellas for GLT or CLT visually or machine strength graded timber is required. Visual grading allows only for a limited number of classes while reject rates tend to be high. The present paper shows the potential of an evolutionary algorithm NSGA-II optimizing the boundaries of multiple visual grading criteria in a...