Optimum design for smoke-control system in buildings considering robustness using CFD and Genetic Algorithms

In fire-prevention designs for buildings, the major concerns are ensuring safe evacuation in the event of a fire and preventing the fire from spreading. Fire inevitably involves many uncertainties, such as the site of the fire source, whether or not a window is open, erroneous operation of prevention systems, and so on, which increases the risk leading to a large disaster. It is very important to consider these uncertainties to design a safe fire-prevention system. In this research, the optimum design method considering the robustness of smoke-control systems in buildings is developed using an approach that couples Computational Fluid Dynamics (CFD) with Genetic Algorithms (GA). The general optimum design and robust design for a vestibule pressurization smoke-control system in an office are conducted. As a result, although the airflow rate through the doorway of the vestibule, intended to ensure that smoke does not escape into the vestibule during evacuation, is a little lower than the general optimum design, the safety performance of the system is more stable in the robust case. The optimum design method proved to be useful in terms of the fire-prevention system design. The approach will be conducted for other urban safety design.