An evaluation model for fire resistance heat transfer of multi-layer floor assembly structure of rail vehicles

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The high-temperature heat transfer performance of rail vehicle floor assembly is an important parameter to study whether the vehicle can resist external fire. The traditional method cannot measure the heat transfer parameters of the aluminum profile sprayed with fireproof paint in the floor assembly. This paper proposes a model for calculating the equivalent density and specific heat capacity of aluminum profiles after the fire. The equivalent density and specific heat capacity can be obtained by using this calculation method. A deep neural network method was used to predict the thermal conductivity of the component, which was 0.6 W / (m·K), combined with the 30-minute fire resistance test data of aluminum profiles with fireproof paint. Using the obtained thermal physical parameters, the finite element calculation and test were carried out for the floor assembly with 5 mm, 10 mm and 15 mm three kinds of thickness heat-insulating cotton. It is found that the calculated prediction results are close to the test results and have a strong correlation. Pearson correlation coefficients of three kinds of heat-insulating cotton with different thickness are 0.964, 0.98 and 0.978 respectively. After obtaining the thermal physical parameters, the finite element model can effectively predict the back fire surface temperature of multi-layer floor assembly and guide vehicle floor design. In this paper, a calculation model for fire resistance heat transfer of the floor assembly of rail vehicles is proposed, which is of great significance for accurate and rapid design of the floor assembly of rail vehicles.