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Experimental and theoretical study on low-frequency combustion instabilities in mechanically ventilated compartment fires

​Maxime Mense has defended his thesis on 12th November 2018 in Marseille, France.

Document type > *Mémoire/HDR/Thesis

Keywords >

Research Unit > IRSN/PSN-RES/SA2I/LEF

Authors > MENSE Maxime

Publication Date > 12/11/2018

Summary

​During liquid hydrocarbon fire tests in the IRSN's mechanically ventilated DIVA device, a low-frequency (LF) oscillatory phenomenon, typically of a few mHz, was observed. This phenomenon manifests itself by large variations of the average pressure in the room, which can lead to a loss of confinement and thus promote the spread of fire and the release of pollutants beyond the local. It is accompanied by intermittent displacements of the flame outside the fuel pan. The fine study of this phenomenon consisted in designing a 1:4 scale model of the DIVA device, allowing us to carry out a very large number of tests, varying the room air change rate, the diameter of the fuel pool, the type of fuel, the ventilation configuration and the type of wall materials. The analysis of the results obtained allowed us to identify different combustion regimes, to describe the mechanisms responsible for the appearance of the LF oscillations, and to characterize the properties of these oscillations (frequency and amplitude). The occurrence and persistence of LF oscillations essentially depend on the precarious equilibrium between the supply of fresh air and the supply of fuel vapors which results from the heat flux received at its surface. An exploratory numerical study using the CFD code SAFIR was then conducted using both the experimentally measured evaporation rate and that calculated using an evaporation model. The model does not correctly describe the displacements of the flame outside the fuel pan. However, it satisfactorily reproduces the LF oscillatory fire behavior, especially its dominant frequency. This study has helped to understand the oscillatory phenomenon by providing information on local quantities inaccessible by experience, and to explore the predictive capability of this CFD modeling.

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