Dynamic industrial risk assessment with computational fluid dynamics: Application to turbocompressor jet fire scenarios

Abstract

The Gas Compression Station R'mel 4 in Algeria is a critical component of the natural gas transmission network and a high‐risk industrial facility due to dense equipment and flammable gases under high pressure. This study analyzes a critical jet fire scenario involving a turbocompressor using a dynamic industrial risk assessment (DIRA) approach coupled with computational fluid dynamics (CFD). This methodology simulates the spatio‐temporal propagation of thermal radiation and evaluates the influence of complex geometries and obstacles on heat flux distribution. The analysis determines the magnitude and spatial extent of thermal fluxes, critical distances to equipment and occupied areas, and exposure durations. Dynamic modeling enables accurate identification of vulnerable zones and quantification of potential impacts on personnel. Compared with conventional static methods, which rely on simplified and conservative assumptions, the dynamic approach produces more realistic and spatially differentiated results. Traditional methods tend to classify certain areas as unacceptable risk zones, whereas dynamic simulation shows that hazard levels remain within acceptable limits under realistic conditions. By improving risk characterization, the DIRA_CFD approach supports optimized mitigation strategies, enhances decision‐making, and strengthens proactive safety management in high‐risk industrial installations, and improves overall industrial resilience and operational safety performance in complex environments and globally applicable.