Your search resulted in 179 documents. Displaying 25 entries per page.
A multi-dataset validation study of moisture prediction in Norway spruce wood exposed outdoors
2025 - IRG/WP 25-41029
Wood used in outdoor construction undergoes continuous cycles of wetting and drying, resulting in fluctuating moisture contents that directly influence its long-term durability. Excess moisture above a critical threshold leads to deterioration by fungal decay, limiting the service life of the structure. Service life models thus rely on accurate predictive models of moisture behaviour. However, cap...
J Niklewski, C Brischke
Quantitative Prediction of Latent Deterioration in Wood Coatings Using Mid-Infrared Spectroscopy and Machine Learning
2025 - IRG/WP 25-41038
Wood coatings play a vital role in prolonging the lifespan of timber structures by protecting them from environmental degradation. However, conventional evaluation methods rely on visual inspections, which cannot detect latent deterioration before visible damage occurs. This study integrates attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy with partial least squares ...
Y Teramoto
Colorimetric performance of temperate wood species under tropical weathering
2025 - IRG/WP 25-41041
The appearance of wood, including its color and texture, is one of the most important features for its application as solid products, such as furniture, cladding, and terrace decking. Weathering can cause significant changes in the color of wooden products in outdoor applications, influencing their market acceptance and long-term performance. This study evaluated the colorimetric performance of fo...
K da Silva Pereira, S J da Costa Lima, M F C Santos, L Emmerich, C Brischke, D C Batista
Development of an Early Degradation Diagnosis Technology for Wood Coatings Using Mid-Infrared Spectroscopy and Machine Learning
2025 - IRG/WP 25-41047
Accurately predicting the degradation state of wood coatings is challenging, and as the coating deteriorates, it becomes a major factor accelerating the degradation of the wood itself. In this study, we aimed to develop a diagnostic technology that combines mid-infrared spectroscopy and machine learning to assess latent coating degradation, which cannot be detected visually, and to enable appropri...
K Nishimura, T Ito, S Isaji, T Takano, H Ohki, Y Teramoto