Sökning: "machine grading"
Visar resultat 1 - 5 av 18 avhandlingar innehållade orden machine grading.
1. Studies of the fibre direction and local bending stiffness of Norway spruce timber : for application on machine strength grading
Sammanfattning : Machine strength grading is a production process in the sawmill industry used to grade sawn timber boards into different strength classes with specific characteristic values of the bending strength, modulus of elasticity (MOE) and density. These properties are called grade determining properties. LÄS MER
2. Integrated strength grading
Sammanfattning : This work comprises strength grading for structural timber according to European standards and prediction of grade-determining properties by various technologies and in various stages of the sawmilling process. The detection technologies applied on logs were outer shape scanning, laser scattering, x-ray scanning and resonance analysis. LÄS MER
3. Thermally Modified Timber : Novel Aspects of Bending Behaviour Towards Grading and Structural Applications
Sammanfattning : Thermally modified timber (TMT) has gained market share in Europe as an environmentally friendly and durable building material. Unfortunately, TMT products are currently prohibited for use in structural applications as there is insufficient data to estimate the loss in strength due to thermal modification. LÄS MER
4. Modelling the Variability of Bending Strength in Structural Timber - Length and Load Configuration Effects
Sammanfattning : The load carrying capacity of a beam of structural timber is dependent both on the span of the beam and the type of loading. The longer the beam and the more uniform the moment distribution, the lower the load carrying capacity. This phenomenon is due to the variability of material properties within a piece of timber. LÄS MER
5. Patterns in big data bioinformatics : Understanding complex diseases with interpretable machine learning
Sammanfattning : Alterations in the flow of genetic information may lead to complex diseases. Such changes are measured with various omics techniques that usually produce the so-called “big data”. Using interpretable machine learning (ML), we retrieved patterns from transcriptomics data sets. LÄS MER