PREDICTING THE FIRE EXTINGUISHING TIME OF EXPLOSIVE COMPONENTS USING FIRE EXTINGUISHING HYDROGELS
Abstract and keywords
Abstract (English):
. Using methods of regression analysis and neural network research, it was possible to preserve the physical properties of water-gene compositions and ensure a minimum time for extinguishing a fire in a model fire with components of industrial explosives. Neural network modeling was performed in the STATISTICA Application 10 program. The maximum discrepancy between the results of the neural network model and experimental data is 0,18 %. Regression analysis was performed in the REGRAN program. The maximum error in target results was 4,4 %. Analysis of experimental data and mathematical modeling results showed that the most significant properties of fire extinguishing agents based on hydrogels, providing minimal extinguishing time, are density and surface tension. The concentrations of the gelling agent were determined at which the water-gel composition acquires optimal physical properties for extinguishing a model outbreak of a component of an industrial explosive. Recommendations have been developed for creating hydrogel formulations with desired properties.

Keywords:
regression analysis, neural network modeling, firefighting, industrial explosives
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References

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