The ISO room corner test is used for classification of surface materials in a number of countries, and as the reference scenario test for the new European single burning item test, its importance increases even more. Time to flashover may be regarded the most important result from the room corner test. In this paper we describe three different calculation models for predicting in which period of testing time flashover in the room corner test will occur. The predictions are all based on test results from the cone calorimeter. The models are a modified version of the Wickstr. o om/G. o oransson model, the model by .O Ostman/Tsantaridis and a model based on multivariate statistical analysis. The three models were applied to a data set containing test results from 57 different products. We found that the modified Wickstr. o om/G. o oransson model and the statistical model generally calculated time to flashover with high precision. The .O Ostman/Tsantaridis model was excellent in prediction of time to flashover within 10 min of testing time, but performed poorer for time to flashover above 10 min. Based on these analyses, a simple, but efficient method for predicting the interval of time when flashover occurs is suggested.

Fire retardants may considerably improve the 5re properties of wood products, but the durability, e.g. in exterior applications, has not been addressed fully. This paper reviews the existing knowledge and experience mainly from the USA with the aim of supporting further development in Europe. The review is concentrated on pressure impregnated 5re retardant treated wood products which have the best opportunities for increased durability.

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Building materials and their durability and ageing are essential to the performance of buildings and their building physical aspects over time. Accelerated climate ageing investigations are carried out in order to study the durability of various building materials in a substantial shorter time span than natural weather ageing would have allowed. Climate parameters like temperature including freezing/thawing cycles, relative air humidity, water spray amount, solar and/or ultraviolet radiation and exposure duration are controlled in different climate ageing apparatuses. Various ageing processes in the building materials, ageing both by natural and accelerated climate exposure, may be studied in an attenuated total reflectance (ATR) Fourier transform infrared (FTIR) radiation analysis following the decomposition and/or formation of chemical bonds in these building materials and products.The ATR-FTIR experimental method represents a powerful measurement tool on various materials. This method may be applied on both solid state materials, liquids and gases with none or only minor sample preparations, also including materials which are non-transparent to infrared radiation. Such a facilitation is made possible by pressing the sample directly onto various crystals with high refractive indices, e.g. diamond, in a special reflectance setup. Thus ATR saves time and enables the study of materials in a pristine condition, i.e. the comprehensive sample preparation by pressing thin KBr pellets as in traditional FTIR transmittance spectroscopy is avoided.However, the ATR-FTIR analysis of different building material samples exhibit various levels of experimental difficulties. In this investigation we have studied the FTIR spectra of climate weathered wood, wood rot, mould fungus on wood, mould fungus on plaster board and plastic degradation by ultraviolet radiation. Both qualitative and quantitative results may be obtained by an ATR-FTIR analysis using regular recordings of FTIR spectra. In order to determine the ageing progress and assess the effective lifetime of materials, components or products, FTIR spectra should be recorded both before, during and after the climate ageing. Hence, FTIR may be developed as an important tool to track the condition of various materials, components and products during the lifetime of a building, and thereby be applied as a tool for condition assessment, selection of maintenance intervals and service life prediction of buildings.

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