使用灭火水凝胶预测爆炸性成分的灭火时间

Taras Vorontsov, Aleksey Ivanov
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摘要

.利用回归分析和神经网络研究方法,可以在使用工业炸药成分的模型火灾中保持水-基因组合物的物理特性,并确保最短的灭火时间。神经网络建模是在 STATISTICA Application 10 程序中进行的。神经网络模型结果与实验数据之间的最大差异为 0.18%。使用 REGRAN 程序进行了回归分析。目标结果的最大误差为 4.4 %。对实验数据和数学建模结果的分析表明,基于水凝胶的灭火剂在提供最短灭火时间方面最重要的特性是密度和表面张力。确定了胶凝剂的浓度,在该浓度下,水凝胶成分可获得最佳物理特性,用于扑灭工业炸药成分的模型爆炸。此外,还提出了创建具有所需特性的水凝胶配方的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PREDICTING THE FIRE EXTINGUISHING TIME OF EXPLOSIVE COMPONENTS USING FIRE EXTINGUISHING HYDROGELS
. 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.
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