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Nam, S., 2007. Intermediate-Scale Fire Test ? Stepping Stone For Prediction Of Material Flamability In Real-Scale Fire Through Bench-Scale Fire Test Data. AOFST 7
ABSTRACT
Intermediate-scale fire tests were conducted in this study to predict flammability of wall panels in full-scale fire, which might be misinterpreted in bench-scale fire tests. The scale of the tests was large enough for the testing materials reveal their true behavior in full-scale fire but still small enough to provide substantial savings in the costs of testing. The 4.9 m high parallel panel configuration, in which two vertically erected panels facing each other so that they can continuously feed heat fluxes each other while they are burning, was adopted as the intermediate-scale tests simulating the 25 and the 50 ft corner tests. The corner tests have been used to evaluate fire hazards of wall/ceiling panels and other similar building materials for decades using fire in large corner settings. In order for the parallel panel tests to provide proper interpretation of corner test results, the view factors for the radiative heat transfer and the heat flux to the testing wall panels in the parallel panel tests were kept the same as those in the corner tests. The heat release rates from the burning panels in the parallel panel tests were used to predict the outcome of the corner tests. It seemed that the heat release rate measurements can be adopted as more reliable criteria for the pass/fail of the corner tests than the current visual observations in highly smoky environment. The predictions by the intermediate-scale tests resulted in an excellent match with the outcome of the 25 and the 50 ft corner tests. In the process of developing a physical model that would describe material behaviors in fires by utilizing bench-scale test data, reliable intermediate-scale tests will be instrumental by providing an affordable validation tool; thus they serve as a stepping stone in a journey to reach a goal of predicting outcome of full-scale fire tests by analyzing bench-scale test data.
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