Configuration Approaches of CFAST for Prediction of Smoke and Heat Detector Activation Times in Corridor Fires  
[PERSON]  
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[PERSON]  
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Footnote 2: email: {Hyo-Yeon-Jing-2019-1  
Multiple user-demanded input factors, such as the visibility, CO and CO\({}_{2}\) concentrations, and soot yields resulting from fire phenomena, are crucial for alignment with fire safety standards. Experimental measurements and databases for the heat release rate (HRR), CO yield, and soot yield of various combustible materials under different fire conditions have been reported [10]. Additionally, physically measured input factors from experiments have been employed to accurately predict fire detector activation times in PBD for building RSET [11; 12]. Despite utilizing seemingly similar fire scenarios, the diversity in input factors at the discretion of PBD practitioners leads to significantly different risk evaluations. Moreover, the grid size significantly affects the accuracy of the numerical solutions, indicating the importance of varied numerical experiences for the reliable interpretation of results.  
CFAST is a zone model applied as a representative fire modeling tool that divides a fire region into an upper hot layer and a lower cold layer. It assumes uniform properties by considering the relationship between the heat and mass flows across their boundaries. It assumes that each zone is a single control volume and uses mass and energy conservation laws to consider changes over time through empirical correlations. There is an entry barrier because of the requirement for an understanding of fire dynamics to conceptually simplify the fire behavior. The tool has excellent predictive performance for small calculation domains but may exhibit reduced reliability for larger or irregularly shaped areas because of its requirement for similar compartment dimensions [13]. However, it offers ease of operation with minimal education, compatibility with low-performance computers, and minimal computational cost. Compared with other analytical tools, it is known for its rapid calculations and superior predictive performance for small calculation domains. Fire engineers and researchers have verified the accuracy of CFAST through experiments and reported cost-effective outcomes [14; 15; 16]. Thus, CFAST provides a straightforward means to understand fire dynamics trends and obtain clear results despite its simplifying assumptions.  
This study is part of a project aimed at developing a program for fire safety managers to create evacuation plans for buildings in the event of a fire. To assess the ASET and RSET within the same domain in real time through fire and evacuation simulations, the suitability of relatively simple analysis tools such as CFAST was examined. Even with limited knowledge of fire engineering and models, we hope to provide a setup method for predicting the appropriate activation times of smoke and heat detectors when modeling a corridor fire. The assumption of uniform physical quantities in zone modeling for each zone emphasizes caution in fire modeling in areas with high horizontal aspect ratios, such as corridors [13]. Therefore, we reviewed the empirical correlations applied to predict the activation times of smoke and heat detectors in CFAST. Despite identical computational areas, the physics predicted by CFAST can yield varying results depending on the setup, offering design strategies with good predictive performance for the smoke and heat detector activation times.