TANG Xun, HONG Yu, ZHANG Tianjiao, LI Yanchao. Effects of external turbulence intensity on ethylene explosion characteristics[J]. Explosion And Shock Waves. doi: 10.11883/bzycj-2026-0273
Citation:
TANG Xun, HONG Yu, ZHANG Tianjiao, LI Yanchao. Effects of external turbulence intensity on ethylene explosion characteristics[J]. Explosion And Shock Waves. doi: 10.11883/bzycj-2026-0273
TANG Xun, HONG Yu, ZHANG Tianjiao, LI Yanchao. Effects of external turbulence intensity on ethylene explosion characteristics[J]. Explosion And Shock Waves. doi: 10.11883/bzycj-2026-0273
Citation:
TANG Xun, HONG Yu, ZHANG Tianjiao, LI Yanchao. Effects of external turbulence intensity on ethylene explosion characteristics[J]. Explosion And Shock Waves. doi: 10.11883/bzycj-2026-0273
This study aims to clarify the influence of external turbulence on ethylene-air explosion characteristics. Experiments were performed in a constant-volume combustion chamber equipped with a fan-generated turbulence system, high-speed schlieren imaging, and pressure acquisition devices. The effects of turbulence intensity (u′ = 0.00-0.60 m/s) and equivalence ratio (Φ = 0.6-2.0) on flame morphology, propagation velocity, explosion overpressure, and pressure rise rate were systematically investigated. The results indicate that increasing turbulence intensity promotes flame surface wrinkling and accelerates flame propagation, with the most significant enhancement observed at u′ = 0.44-0.60 m/s. The normalized turbulent flame propagation velocity exhibits self-similar behavior with increasing turbulent Reynolds number, and Ka- and Da-based correlations accurately describe the acceleration process with R2 values above 0.91. Moreover, higher turbulence intensity increases the maximum explosion overpressure and pressure rise rate by enhancing fuel-air mixing and reducing heat loss. A physics-guided neural network model incorporating initial condition, peak, and smoothness constraints was further developed to predict overpressure evolution, achieving improved physical consistency and prediction accuracy compared with the XGBoost model. These findings provide quantitative insights into turbulence-enhanced ethylene explosion hazards and support safety assessment of ethylene-related industrial processes.