A fire egress system is one of the most critical aspects of fire emergency evacuation, which is the cornerstone technology of building fire safety. The high-rise teaching buildings on campus, where vast crowds of people gather, need to be qualified for rapid evacuation in the event of a fire especially. Conventional teaching building egress system design places more emphasis on individual elements (e.g., stairwells, evacuation doors, and evacuation walkways) rather than on their co-regulation as a whole. Furthermore, there are not enough holistic and effective optimal design strategies, which is because most of the existing studies rely on experiments or simulations and often suffer from a lack of sufficient data to fully reveal the interactions of individual variables. In this study, the co-effectiveness of stairwells, walkways, and room doors in reducing total evacuation time was investigated by simulation and machine learning. We selected a typical high-rise teaching building as an example and integrated two simulation software, Pyrosim and Pathfinder, to compare the available safe evacuation time (ASET) and required safe evacuation time (RSET). Then, a framework consisting of five factors—stair flight width (SFW), stairwell door width (SDW), corridor width (CW), room door width (RDW), and location of the downward stair flight (LDSF)—was established for the optimization through statistical analysis of big data obtained by the preferred machine learning algorithm. Results indicate that (1) By modifying just one factor (SFW), the total evacuation time (TET) can be reduced by at most 12.1%, with the mortality rate dropping from 26.5% to 9.5%; (2) although ASET could not be achieved either, among 4000 cases of multi-factor combinations, a maximum TET improvement degree, 29.5%, can be achieved for the evacuation optimization compared to baseline model, with a consequent reduction in mortality to 0.15%; (3) it shows that the emphasis of the egress system optimization is on the geometric features of the evacuation stairwell; furthermore, the multi-factor combination approaches have better compromised evacuation performances than the single-factor controlled schemes. The research results can be applied as rational design strategies to mitigate fire evacuation issues in high-rise teaching buildings and, in addition, the methodology suggested in this paper would be suitable to other building types.
Building evacuation safety has been one of the focal points of researchers, and there is a wealth of research findings for certain places (e.g., buildings with a high population density) or for particular research subjects (e.g., the physically challenged ethnic group). However, current publications are relatively rare in analyzing the features of physically impaired individuals in crowded places and their impact on the effectiveness of the whole evacuation process, including non-disabled people. Additionally, only such studies tend to concentrate on the behavioral characteristics of disabled people, which lack exploring and comparing evacuation optimization strategies and evaluation of comprehensive evacuation performance. This paper proposed a computer simulation-based method that combined horizontally phased evacuation and vertically phased evacuation, supplemented with the use of handicapped ramps and a reasonable arrangement of class locations, to achieve the optimal evacuation performance of a teaching building with special consideration of the heterogeneous population. And then, a simulated building model was constructed to test and compare the effectiveness and applicability of these approaches through 33 evacuation scenario studies. The results found that (1) component design can improve evacuation effectiveness, with the arrangement of ramps and the location of stair doors successfully reducing evacuation time by 12% and 6.6%, respectively; (2) a combination of two ramps and separate handicap access can decrease evacuation time by 18%; (3) the horizontal-phased evacuation approach drops evacuation time by 7.1%, but the vertical-phased evacuation strategy is not very efficient. When the two are successfully combined, evacuation time is further reduced to 9.2%; and (4) based on the above measures, the evacuation time can be finally shortened by 19% if the veteran teachers are concentrated in the classrooms on the lower floors. These obtained conclusions will provide significant reference and methodological support for the safe evacuation of other similar buildings with heterogeneous populations.
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