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Advanced Analysis and Technology in Fire Science and Engineering - 2nd Edition

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Industrial Technologies".

Deadline for manuscript submissions: 30 May 2025 | Viewed by 5160

Special Issue Editor

Dr. Cheol-Hong Hwang

E-Mail Website
Guest Editor
Department of Fire and Disaster Prevention, Daejeon University, Daejeon 34520, Republic of Korea
Interests: combustion; fuels; pollutant emission; modeling and simulation; measurements; fire safety
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue aims to publish high-quality works obtained from experimental, theoretical, and computational investigations on the fundamentals and applications of fire science and engineering. Since the field of fire science and engineering covers a very wide range from fundamental research to practical application, there are not enough specialized journals where relevant researchers can share in-depth research results. This Special Issue is open to research that can help to better explain complex fire phenomena and ultimately contribute to fire safety design. Potential topics include (but are not limited to) experimental, theoretical, and numerical simulation studies of fire physics and chemistry, fire dynamics, measurements in fire environments, fire detection and suppression system, fire safety design and management, an assessment of fire risk and fire investigation, etc.

We welcome the submission of original works, reviews, and short communications that provide novel insights related to the multidisciplinary fire science and engineering research fields.

Prof. Dr. Cheol-Hong Hwang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • fire chemistry and physics
  • fire dynamics
  • measurement in fire environments
  • fire detection and suppression system
  • fire safety design and management
  • assessment of fire risk
  • fire investigation

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Published Papers (5 papers)

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Research

29 pages, 5198 KiB  
Article
Distributed Fire Classification and Localization Model Based on Federated Learning with Image Clustering
by Jiwon Lee, Jeongheun Kang, Chun-Su Park and Jongpil Jeong
Appl. Sci. 2024, 14(20), 9162; https://doi.org/10.3390/app14209162 - 10 Oct 2024
Viewed by 934
Abstract
In this study, we propose a fire classification system using image clustering based on a federated learning (FL) structure. This system enables fire detection in various industries, including manufacturing. The accurate classification of fire, smoke, and normal conditions is an important element of [...] Read more.
In this study, we propose a fire classification system using image clustering based on a federated learning (FL) structure. This system enables fire detection in various industries, including manufacturing. The accurate classification of fire, smoke, and normal conditions is an important element of fire prevention and response systems in industrial sites. The server in the proposed system extracts data features using a pretrained vision transformer model and clusters the data using the bisecting K-means algorithm to obtain weights. The clients utilize these weights to cluster local data with the K-means algorithm and measure the difference in data distribution using the Kullback–Leibler divergence. Experimental results show that the proposed model achieves nearly 99% accuracy on the server, and the clustering accuracy on the clients remains high. In addition, the normalized mutual information value remains above 0.6 and the silhouette score reaches 0.9 as the rounds progress, indicating improved clustering quality. This study shows that the accuracy of fire classification is enhanced by using FL and clustering techniques and has a high potential for real-time detection. Full article
(This article belongs to the Special Issue Advanced Analysis and Technology in Fire Science and Engineering - 2nd Edition)
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14 pages, 2254 KiB  
Article
Risk Assessment of Hydrogen Cyanide for Available Safe Egress Time in Fire Simulation
by Oh-Soo Kwon, Ho-Sik Han and Cheol-Hong Hwang
Appl. Sci. 2024, 14(16), 6890; https://doi.org/10.3390/app14166890 - 6 Aug 2024
Viewed by 721
Abstract
The majority of fatalities in building fires are attributed to asphyxiation caused by toxic gases. Hydrogen cyanide (HCN) is one of the toxic gases that can be released during a fire, posing a lethal risk to humans even at low concentrations. However, analysis [...] Read more.
The majority of fatalities in building fires are attributed to asphyxiation caused by toxic gases. Hydrogen cyanide (HCN) is one of the toxic gases that can be released during a fire, posing a lethal risk to humans even at low concentrations. However, analysis of the risk posed by HCN in fire risk assessments using fire simulations is relatively rare. This study conducted fire simulations to examine the potential risks of HCN to occupants during a fire. The simulations considered various fire conditions in residential buildings by varying fuel types, fire growth rates, and HCN yields. The relative risk score (RRS) was derived based on the time to reach the threshold values of parameters considered critical for life safety. The results of the fire simulations indicated that the RRS for HCN was approximately 20–40 points higher than that of O2, CO, and CO2, reaching a maximum of 92 points. However, the risk posed by HCN was found to be limited in comparison to the risks associated with temperature and visibility. Nevertheless, considering that the primary cause of fatalities in fires is asphyxiation due to toxic gases, HCN must be regarded as a critical factor in fire risk assessments. Additionally, since HCN yield values can increase up to nine times depending on temperature and ventilation conditions, the risk posed by HCN could be significantly higher. Full article
(This article belongs to the Special Issue Advanced Analysis and Technology in Fire Science and Engineering - 2nd Edition)
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27 pages, 3790 KiB  
Article
Identification and Discrimination of Petrol Sources by Nuclear Magnetic Resonance Spectroscopy and Machine Learning in Fire Debris Analysis
by Yanita Yankova, Silvia Cirstea, Michael Cole and John Warren
Appl. Sci. 2024, 14(12), 5177; https://doi.org/10.3390/app14125177 - 14 Jun 2024
Viewed by 693
Abstract
Petrol is considered the most common fire accelerant. However, the identification and classification of petrol sources through the years has proven to be a challenging field in the investigation of fire debris analysis. This research explored the possibility of identifying petrol sources by [...] Read more.
Petrol is considered the most common fire accelerant. However, the identification and classification of petrol sources through the years has proven to be a challenging field in the investigation of fire debris analysis. This research explored the possibility of identifying petrol sources by high-field NMR methods accompanied by ML (machine learning). The automated identification and classification of petrol brands were achieved for first time based on the ML classification model developed in this research. A hierarchical classification model was constructed using local classifiers to categorize neat or weathered petrol into its sources. Full article
(This article belongs to the Special Issue Advanced Analysis and Technology in Fire Science and Engineering - 2nd Edition)
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23 pages, 7796 KiB  
Article
The Effect of Inclined Conditions on the Consequences of Fires Caused by Spilled Flammable Liquids: Development of Inclined Spreading Extent Formulae
by Daeyu Baeg, Hyunho Lee, Seungyul Lee and Jung Kwan Seo
Appl. Sci. 2024, 14(2), 745; https://doi.org/10.3390/app14020745 - 15 Jan 2024
Viewed by 1012
Abstract
The accidental spillage of flammable liquids on in-service ships and offshore installations may lead to pool fires, which are likely to spread over a particularly large area in large compartments under ship motion, resulting in extensive damage. However, the effect of the spreading [...] Read more.
The accidental spillage of flammable liquids on in-service ships and offshore installations may lead to pool fires, which are likely to spread over a particularly large area in large compartments under ship motion, resulting in extensive damage. However, the effect of the spreading extent of liquid fuel due to inclined ship motion on pool fire consequences has not been considered in the existing literature. Thus, in this study, fuel discharge experiments were conducted to investigate the spreading behaviour under different substrate inclination angles and discharge rates. The experimental results were analysed to derive closed-form expressions to predict the spreading extent of liquid fuel in large compartments. Additionally, the effects of surface inclination on fire consequences were investigated using the Fire Dynamics Simulator in terms of the heat release rate. The findings can provide guidance for effective fire safety design and establishing a realistic fire modelling methodology for ships and offshore installations. Full article
(This article belongs to the Special Issue Advanced Analysis and Technology in Fire Science and Engineering - 2nd Edition)
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14 pages, 5614 KiB  
Article
Configuration Approaches of CFAST for Prediction of Smoke and Heat Detector Activation Times in Corridor Fires
by Hyo-Yeon Jang and Cheol-Hong Hwang
Appl. Sci. 2023, 13(24), 13161; https://doi.org/10.3390/app132413161 - 11 Dec 2023
Cited by 1 | Viewed by 1210
Abstract
In performance-based design for domestic buildings, there is a growing need for real-time comparison between the Available Safe Egress Time and Required Safe Egress Time through the integration of fire and evacuation simulations. Therefore, the utilization of the Consolidated Model of Fire and [...] Read more.
In performance-based design for domestic buildings, there is a growing need for real-time comparison between the Available Safe Egress Time and Required Safe Egress Time through the integration of fire and evacuation simulations. Therefore, the utilization of the Consolidated Model of Fire and Smoke Transport (CFAST) has been discussed as an alternative to the Fire Dynamics Simulator (FDS), which has high computational costs; requires sufficient experience in the numerical calculation of fire dynamics, along with various input parameters; and has limitations in coupling with evacuation simulations. In this study, the prediction performance of CFAST for the activation times of smoke and heat detectors was evaluated. Specifically, it is essential to configure the mass movement between adjacent computational regions for smoke concentration. For achieving adequate predictive performance, the temperature should be determined according to the ceiling jet velocity generated by the fire source. Therefore, a method for setting a computational domain that can produce reasonable prediction results while considering the characteristics of CFAST for different types of smoke and heat detectors is proposed. Full article
(This article belongs to the Special Issue Advanced Analysis and Technology in Fire Science and Engineering - 2nd Edition)
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