Multi-Scenario Fire Performance Assessment of ETFE (EthylenTetraFluoroEthylen) Cushion Facades via Artificial Intelligence: Integrating Active and Passive Fire Safety Measures
Yasemin Bal, Didem Güneş YılmazETFE (EthylenTetraFluoroEthylen) cushion facade systems are increasingly adopted in contemporary architecture due to their lightweight properties and design flexibility. However, their thin, meltable structures present persistent uncertainties in fire safety. Specifically, the quantitative effects of fire origin, facade location, and passive–active fire protection measures on structural integrity, toxicity, and secondary fire risks remain underexplored. This study evaluates the fire performance of 15 ETFE cushion facade typologies under 135 scenarios, including fires originating externally, internally, and within the cushion, across middle, corner, and recessed facade locations. Simulations are conducted using artificial intelligence-based code generation to address the limitations of conventional fire modeling. Fire behavior is quantified via time to structural failure, burning duration, CO toxic gas production, dripping onset and mass, and normalized fire and dripping performance indices. Results show that passive measures provide limited structural delay and often increase burning duration and toxicity. Conversely, active systems demonstrate more balanced, scenario-dependent performance, reducing fire intensity, toxic gas emission, and melt-induced secondary risks. These findings highlight that effective fire safety in ETFE cushion facades requires holistic, location-sensitive and scenario-sensitive integration of passive and active measures rather than reliance on singular strategies, ensuring property protection and life safety in buildings.