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

Conference paper (2016)

Authors

Andriy Kovryga Technische Universität München
Peter Stapel Technische Universität München
J.W.G. van de Kuilen Steel & Composite Structures - CEG , Technische Universität München
Research Group
Steel & Composite Structures (CEG) (TU Delft)
Copyright: © 2016 Andriy Kovryga, Peter Stapel, J.W.G. van de Kuilen
Evolutionary algorithm Yield NSGA-II Characteristic strength DIN 4074 Visual strength grading
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Published Date

2016

Language

English

Faculty

Civil Engineering & Geosciences

Department

Engineering Structures

Research Group

Steel & Composite Structures

Abstract

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 reliable way. The optimization routine is applied to optimize the boundaries of the visual grading criteria given in DIN 4074-1 and DIN 4074-5. Destructive and non-destructive test data of 1515 specimens of Norway spruce (Picea abies) and 704 specimens of European beech (Fagus sylvatia) tested in tension were analysed. The optimization aims at: a) a maximization of the yield; 2) grade timber to the desired strength classes. Using this optimization routine for both beech and spruce higher yield figures compared to the grading according to DIN 4074 can be obtained while the desired characteristic strength are being reached.