Real-Time Egress Model for Multiplex Buildings under Fire Based on Artificial Neural Network
| Autor: | Hae-Chang Cho, Inwook Heo, Sun-Jin Han, Khaliunaa Darkhanbat, Kang Su Kim |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Technology
Computer science QH301-705.5 egress model QC1-999 Real-time computing 0211 other engineering and technologies 020101 civil engineering 02 engineering and technology available safe egress time (ASET) 0201 civil engineering 021105 building & construction General Materials Science Biology (General) Visibility Instrumentation QD1-999 Fluid Flow and Transfer Processes Artificial neural network Process Chemistry and Technology Physics General Engineering multiplex building artificial neural network (ANN) Toxic gas Engineering (General). Civil engineering (General) Computer Science Applications Chemistry Margin of safety TA1-2040 fire |
| Zdroj: | Applied Sciences Volume 11 Issue 14 Applied Sciences, Vol 11, Iss 6337, p 6337 (2021) |
| ISSN: | 2076-3417 |
| DOI: | 10.3390/app11146337 |
| Popis: | When fire occurs in a large multiplex building, the direction of smoke and flames is often similar to that of the evacuation of building occupants. This causes evacuation bottlenecks in a specific compartment, especially when the occupant density is very high, which unfortunately often leads to many fatalities and injuries. Thus, the development of an egress model that can ensure the safe evacuation of occupants is required to minimize the number of casualties. In this study, the correlations between fire temperature with visibility and toxic gas concentration were investigated through a fire simulation on a multiplex building, from which databases for training of artificial neural networks (ANN) were created. Based on this, an ANN model that can predict the available safe egress time was developed, and it estimated the available safe egress time (ASET) very accurately. In addition, an egress model that can guide rapid and safe evacuation routes for occupants was proposed, and the rationality of the proposed model was verified in detail through an application example. The proposed model provided the optimal evacuation route with the longest margin of safety in consideration of both ASET and the movement time of occupants under fire. |
| Databáze: | OpenAIRE |
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