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Prediction of fire classification for wood based products. A multivariate statistical approach based on the cone calorimeter
Authors:Anne Steen‐Hansen  Bjarne Kristoffersen
Affiliation:1. Department of Civil and Transport Engineering, H?gskoleringen 7, Norwegian University of Science and Technology (NTNU), NO‐7491 Trondheim, Norway;2. SINTEF NBL, Norway
Abstract:Wood has long traditions as a building material, and is often used in construction elements, and as interior and exterior surfaces in the Nordic countries. In most applications, there are reaction to fire requirements to products used as surfaces, e.g. in escape routes and larger public spaces. Most wood products will therefore have to be treated with fire retardant (FR) agents to fulfil the strict requirements to properties connected to heat release and flame spread. Unfortunately, FR agents usually also increase the smoke production, as they cause a more incomplete combustion of the wood. The wood product manufacturers seek to find the optimal amount of FR additives where both heat release and smoke production in the classifying test are within the requirements given in the building regulations. This paper describes models for prediction of the European reaction to fire classes of wood products. The models are based on multivariate statistical analysis, and use test results from the cone calorimeter test as input. The presented models are, with very good precision, able to predict which Euroclass and additional smoke class a wood based product would obtain if it were to be tested in the single burning item test. Copyright © 2006 John Wiley & Sons, Ltd.
Keywords:reaction to fire  cone calorimeter  single burning item  prediction model  multivariate statistics  classification
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