Study on Instantaneous Leak Diffusion Characteristics of Heavy Gas Under Wind Speed Control and Modification of Cloud Cluster Radius Prediction Model

The diffusion process of heavy gas during instantaneous leakage is significantly influenced by wind speed. Accurately characterizing the coupling relationship between wind speed and heavy gas diffusion is crucial for accident risk assessment and emergency response. Based on the Thorney Island 008 test, this study employs computational fluid dynamics (CFD) numerical simulation to construct a gas leakage diffusion model. Through grid independence verification and comparison with measured data, the optimal simulation scheme is determined. Design five wind speed conditions of 0.5 m/s, 1 m/s, 3 m/s, 6 m/s, and 10 m/s to investigate the division of heavy gas dispersion phases, the cloud radius modification model, and the spatiotemporal distribution characteristics of downwind concentrations. The study clearly identifies that heavy gas leakage dispersion can be divided into three stages: gravity diffusion, density stratification, and passive diffusion. By introducing a dimensionless wind speed correction term to improve the cloud plume radius prediction model, the validation results show that the calculated values from the modified model align with the trend observed in CFD simulations. Under all wind speed conditions, the maximum relative error remains within 10%. Downwind gas concentration distribution characteristics reveal that in the near-source areas (25 m, 100 m), higher wind speeds correlate with higher peak gas concentrations and shorter peak arrival times. Conversely, in the mid- and far-field zones (200–500 m), lower wind speeds are associated with higher peak gas concentrations and longer peak arrival times. The cloud radius modification model proposed in this study enables the prediction of heavy gas cloud radii under varying wind speeds within specific conditions. The revealed characteristics of the diffusion phase and the spatiotemporal distribution patterns of gas concentrations provide scientific basis for risk zoning and emergency response planning in heavy gas leakage incidents.