Explosive protection mechanism of aircraft fuel tank cooling based on minimum ignition energy

Abstract To investigate the cooling and explosion prevention mechanism of aircraft fuel tanks, this study develops an intelligent quantitative model based on Minimum Ignition Energy. The model integrates Back Propagation Neural Networks, Light Gradient Boosting Machine, Grey Wolf Optimizer, and Entropy Weight Technique for Order Preference by Similarity to an Ideal Solution. It estimates Minimum Ignition Energy together with temperature and concentration distributions, optimizes cooling conditions, and assesses explosion safety, thus uncovering the connections between them. The results show that the proposed model achieves root mean square errors of 0.020 mJ and 0.12 °C、0.15%VOL in prediction. The scheme based on Grey Wolf Optimizer increases Minimum Ignition Energy by 67.94% and maintains the maximum fuel tank temperature within 35 °C to 45 °C. Meanwhile, explosion safety is improved by 281.31% compared with the non-cooling condition, and the score dispersion is only 0.021. This shows that the cooling and explosion prevention of aircraft fuel tanks occur through lowering the temperature of the fuel tank, preventing vaporization, and raising the Minimum Ignition Energy of the fuel-air mixture. The proposed model makes possible the process of prediction, optimization, and evaluation simultaneously, ensuring that there will be a scientific, reliable, and objective basis and technique for the design of parameters of aircraft fuel tank cooling and explosion protection systems.