Your search resulted in 53 documents. Displaying 25 entries per page.
Optimization via artificial intelligence of intumescent coatings for wood substrates
2023 - IRG/WP 23-40987
The development of new materials requires a large amount of experiments representing a major issue to innovate. This is particularly true for complex material formulations such as flame retarded materials that could contain a number of ingredients. Artificial Intelligence based optimization (more precisely Bayesian optimization) techniques appear to be efficient methods to optimize complex systems...
E Verret, S Duquesne, A Collin
Securing Flame Retardancy in Wood: Durability After Artificial and Natural Weathering Test
2025 - IRG/WP 25-20738
The outdoor use of wood is often limited by challenges such as dimensional instability, vulnerability to fungal decay, and high flammability. Traditional flame retardant treatments improve fire resistance but suffer from significant leaching under environmental exposure, reducing their long-term effectiveness. This study introduces an innovative solution by integrating flame retardants with DMDHEU...
M Wu, L Martin, H Militz
AI Models for Accelerating Wood Protection Testing: Development of Predictive Tools Based on Long-Term Field Test Data
2025 - IRG/WP 25-41023
In this study, we present the development of DecAI, an artificial intelligence (AI) model designed to optimise and accelerate performance evaluations of wood protection products in the European EN 330:2014 "Field test: L-joint method." The Danish Technological Institute (DTI) compiled a dataset of over 100,000 data points from approx.10,000 L-joint samples collected over +15 years at field sites i...
J Stenbaek, B Noufel, L Glade, P Bisgaard