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Fire
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Fire Numerical Simulation, Second Volume
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Fire Numerical Simulation, Second Volume

A special issue of Fire (ISSN 2571-6255).

Deadline for manuscript submissions: 24 September 2025 | Viewed by 2380

Special Issue Editors

Prof. Dr. Yanming Ding

E-Mail Website
Guest Editor
Faculty of Engineering, China University of Geosciences, Wuhan, China
Interests: CFD simulation; fire; pyrolysis; biomass energy; FireFOAM
Special Issues, Collections and Topics in MDPI journals
Dr. Kazui Fukumoto

E-Mail Website
Guest Editor
State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei, China
Interests: computational fluid dynamics; fire; combustion; heat and mass transfer
Special Issues, Collections and Topics in MDPI journals
Dr. Jiaqing Zhang

E-Mail Website
Guest Editor
Electric Power Research Institute, State Grid Anhui Electric Power Co., Ltd., 299 Ziyun Road, Economic and Technological Development Zone, Hefei 230601, China
Interests: electric fire; cable fire; fire safety of UHV converter station/substation; fire safety issues in energy utilization; fire numerical simulation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Fire numerical simulation plays an important role in fire research. It takes advantage of the advances in mathematics, modeling and computing to capture the underlying physics of complex fire problems and predict fire behaviors at various scales. In addition to experiments, fire numerical simulation allows us to further understand fire and to prevent and contain it. Recently, with the development of the numerical simulation method and computing power, fire numerical simulation has faced new opportunities and challenges.

This Special Issue aims to present the recent state-of-art of fire numerical simulation, the development of fire sub-models and new physics findings based on fire numerical simulations.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Current development and application of fire numerical simulation tools;
  • Newly developed fire sub-models;
  • Physics findings based on fire numerical simulation;
  • Case studies with fire numerical simulation to reproduce the real fire scenarios;
  • Evacuation and human behavior numerical simulation in fires;
  • Fire suppression numerical simulation;
  • Numerical simulation regarding fire resistance of structures;
  • Wildland fire-induced geological disaster numerical simulation.

We look forward to receiving your contributions.

Prof. Dr. Yanming Ding
Dr. Kazui Fukumoto
Dr. Jiaqing Zhang
Guest Editors

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. Fire is an international peer-reviewed open access monthly 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 simulation
  • fire sub-models
  • fire spread
  • smoke spread
  • fire suppression
  • FireFOAM
  • FDS
  • CFAST

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Further information on MDPI's Special Issue polices can be found here.

Related Special Issue

Published Papers (3 papers)

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Research

18 pages, 6200 KiB  
Article
Freeze Thickness Prediction of Fire Pipes in Low-Temperature Environment Based on CFD and Artificial Neural Network
by Yubiao Huang, Jiaqing Zhang, Yu Zhong, Yi Guo and Yanming Ding
Fire 2025, 8(2), 65; https://doi.org/10.3390/fire8020065 - 5 Feb 2025
Abstract
In cold regions, fire pipes are highly susceptible to freezing, which can obstruct water flow and lead to pipe ruptures. Accurately predicting the freeze thickness is crucial to maintaining the functionality of fire protection systems. Traditional methods for predicting fire pipe freezing often [...] Read more.
In cold regions, fire pipes are highly susceptible to freezing, which can obstruct water flow and lead to pipe ruptures. Accurately predicting the freeze thickness is crucial to maintaining the functionality of fire protection systems. Traditional methods for predicting fire pipe freezing often rely on simplified models or time-consuming simulations, which limits their accuracy in complex environments. A model for predicting the freeze thickness of fire pipes under low-temperature conditions was developed by integrating Computational Fluid Dynamics with an Artificial Neural Network (ANN). The CFD model was validated to generate data for training and optimizing an ANN based on collected experimental data. The CFD results demonstrate a nonlinear relationship between the freeze thickness of the fire pipe, ambient temperature, and time. Afterwards, the optimal ANN topology, determined through hyperparameter tuning, was found to consist of 12 neurons, the trainlm training function, and tansig–purelin activation functions. Eventually, the ANN model achieved high prediction accuracy with a mean squared error (MSE) of 6.62 × 10−4 on the test set and a regression coefficient R greater than 0.98 across all datasets. Furthermore, the ANN model agrees closely with the simulated data, not only for trained temperature conditions (−5 °C to −50 °C) but also for unseen temperature conditions (−55 °C and −60 °C), indicating excellent generalization performance. Full article
(This article belongs to the Special Issue Fire Numerical Simulation, Second Volume)
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Figure 1

Figure 1
<p>The schematic diagram of the experimental system (<b>a</b>) and fire pipe (<b>b</b>): Yellow lines: pipe front view. Arrows: The identifier. Red dots: Thermocouples.</p> Full article ">Figure 2
<p>Modeling schematic of the parts, dimensions, and measurement positions for CFD analysis.</p> Full article ">Figure 3
<p>Comparison of experimental data with simulation results at different temperatures to determine the convective heat transfer coefficient.</p> Full article ">Figure 4
<p>Fitting results of convective heat transfer coefficients at different temperature differences.</p> Full article ">Figure 5
<p>The schematic topological architecture of the ANN.</p> Full article ">Figure 6
<p>Freezing process of fire pipe at different times at −35 °C.</p> Full article ">Figure 7
<p>Temperature distribution inside the fire pipe at different times at −35 °C.</p> Full article ">Figure 8
<p>Schematic of freeze thickness.</p> Full article ">Figure 9
<p>Freeze thickness with time at different temperatures.</p> Full article ">Figure 10
<p>Comparison of freeze thickness at different times of −10 °C (<b>a</b>), −20 °C (<b>b</b>), −25 °C (<b>c</b>), and −40 °C (<b>d</b>).</p> Full article ">Figure 11
<p>Performance of the selected topology.</p> Full article ">Figure 12
<p>Regression of training, validation, and test data for the selected topology (neuron number: 12, training function: <span class="html-italic">trainlm</span>, activation function: <span class="html-italic">tansig–purelin</span>).</p> Full article ">Figure 13
<p>Comparison of predicted results with simulated data different from the training data.</p> Full article ">
21 pages, 19177 KiB  
Article
Numerical Simulation Study on the Response of Ship Engine Room Structure Under Fire Based on Thermo-Mechanical Coupling Model
by Yuechao Zhao, Zeya Miao, Shouye Wang and Dihao Ai
Fire 2024, 7(12), 480; https://doi.org/10.3390/fire7120480 - 17 Dec 2024
Viewed by 714
Abstract
Ship structures may collapse or be severely deformed during a fire. To precisely assess the post-fire structural integrity of ships, in this study, a thermal–mechanical coupling data interface was created, employing a significant eddy simulation algorithm for fire dynamics and a technique to [...] Read more.
Ship structures may collapse or be severely deformed during a fire. To precisely assess the post-fire structural integrity of ships, in this study, a thermal–mechanical coupling data interface was created, employing a significant eddy simulation algorithm for fire dynamics and a technique to analyze the structural thermal–mechanical coupling reaction. PyroSim was utilized to build a fire scenario, exporting 3D data through the device’s own program, and then the ANSYS thermal–mechanical coupling model was employed to study the spatial temperature distribution under fire-induced conditions. Data from the three-dimensional spatial temperature field served as the boundary condition for the determination of the structural temperature burden. Building on this, an analysis was conducted on the structural response of the intricate two-story interior compartment under fire conditions. The results showed that the location of the fire source and the structural distribution of the mechanical equipment inside the cabin had a great influence on the temperature and combustion heat, followed by the ventilation conditions, while the temperature variations in the parallel dual fuel tanks were greatly influenced by the stack effect. By comparing the stress and strain of the two-layer cabin under normal and fire conditions, the damage and mechanisms associated with important positions in the cabin under fire conditions were revealed. Full article
(This article belongs to the Special Issue Fire Numerical Simulation, Second Volume)
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Figure 1

Figure 1
<p>Method for assigning temperature data to FEM models.</p> Full article ">Figure 2
<p>Geometry and boundary conditions.</p> Full article ">Figure 3
<p>The mesh sensitivity analysis.</p> Full article ">Figure 4
<p>Comparison of simulation combustion and experiment [<a href="#B27-fire-07-00480" class="html-bibr">27</a>]: (<b>a</b>) at 65 s; (<b>b</b>) at 81 s.</p> Full article ">Figure 5
<p>Heat release rate cloud diagram of PyroSim simulation: (<b>a</b>) at 60 s; (<b>b</b>) at 75 s.</p> Full article ">Figure 6
<p>Thermocouple gas temperature.</p> Full article ">Figure 7
<p>Verification model: (<b>a</b>) heat flux change; (<b>b</b>) temperature change.</p> Full article ">Figure 8
<p>Verification model mechanical analysis results: (<b>a</b>) stress; (<b>b</b>) deformation.</p> Full article ">Figure 9
<p>Fire source location information.</p> Full article ">Figure 10
<p>The cabin model used in PyroSim.</p> Full article ">Figure 11
<p>SolidWorks two-story cabin model.</p> Full article ">Figure 12
<p>Heat release at the combustion location: (<b>a</b>) heat flow versus time; (<b>b</b>) heat flux as shown in ANSYS.</p> Full article ">Figure 13
<p>Temperature and heat flow variation curves in the oil tank and engine gallery over time: (<b>a</b>) Temperature variation curve over time; (<b>b</b>) ANSYS demonstration of temperature variation area and thermocouple location.</p> Full article ">Figure 14
<p>FDS combustion gas cloud map: (<b>a</b>) No geometry model; (<b>b</b>) With geometric model.</p> Full article ">Figure 15
<p>Temperature changes at four viewing angles: up, down, left, and right.</p> Full article ">Figure 16
<p>Wall temperature at the upper viewing angle.</p> Full article ">Figure 17
<p>Temperature changes over time for three different powers.</p> Full article ">Figure 18
<p>Heat energy of the engine.</p> Full article ">Figure 19
<p>Bottom deck temperature.</p> Full article ">Figure 20
<p>Stress and strain at the combustion location shown by removing part of the engine: (<b>a</b>) stress; (<b>b</b>) strain.</p> Full article ">Figure 21
<p>Strain and stress conditions of the cabin: (<b>a</b>) strain; (<b>b</b>) stress.</p> Full article ">Figure 22
<p>Distribution of stress and deformation field on the nacelle bottom deck in ANSYS: (<b>a</b>) strain; (<b>b</b>) stress.</p> Full article ">
13 pages, 3709 KiB  
Article
Simulations on Evacuation Strategy and Evacuation Process of the Subway Train Under the Fire
by Xingji Wang, Bin Liu, Weilian Ma, Yuehai Feng, Qiang Li and Ting Sun
Fire 2024, 7(12), 464; https://doi.org/10.3390/fire7120464 - 6 Dec 2024
Cited by 1 | Viewed by 794
Abstract
This study focuses on the safe evacuation strategy and evacuation process in the subway train under the fires. The subway station evacuation mode should be adopted if the power system of a subway train is normal on fire. While, the tunnel evacuation mode [...] Read more.
This study focuses on the safe evacuation strategy and evacuation process in the subway train under the fires. The subway station evacuation mode should be adopted if the power system of a subway train is normal on fire. While, the tunnel evacuation mode should be adopted if the power system of the train fails because of the effects of fire. Under the tunnel evacuation mode, the direction of tunnel smoke should be opposite to that of most passengers, and passengers should be evacuated toward the fresh wind. By using the numerical simulation software Pathfinder and PyroSim, the passenger evacuation time under different conditions is calculated, and the safety of the evacuation process is evaluated. The results show that the evacuation time of the station evacuation mode is obviously shorter than that of the tunnel evacuation mode. With the same conditions, the evacuation time of the tunnel evacuation mode is 2193 s, which is about four times as much as the evacuation time of the station evacuation mode (526 s). The total evacuation time increases with the total number of passengers and the proportion of older people and children. Under an oil pool fire, which is an extreme fire condition, the fire environment inside the train may reach a level threatening the passengers’ safety before the evacuation is complete, even before the door opens; therefore, special attention should be paid to the safety issues in stage from the fire begins to the evacuation complete. Full article
(This article belongs to the Special Issue Fire Numerical Simulation, Second Volume)
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Figure 1

Figure 1
<p>Nine typical evacuation modes under the tunnel evacuation conditions (<span class="html-italic">s</span>: evacuate distance that passengers need to walk to the safety exit; <span class="html-italic">l</span>: length of the tunnel between the two contact channels).</p> Full article ">Figure 2
<p>Simulation models of the subway train, the tunnel, and the platform of the subway station.</p> Full article ">Figure 3
<p>Evacuation process in the subway train and the platform in Case 1 (Unit: person/m<sup>2</sup>).</p> Full article ">Figure 4
<p>Curve of the evacuation passengers versus time in Cases 1 to 3.</p> Full article ">Figure 5
<p>Temperature profiles inside the subway train in the baggage and oil pool fire conditions before the door opened (Range: the fire carriage and its adjacent carriages; Unit: °C).</p> Full article ">Figure 6
<p>Distribution of the passengers inside the carriages under different personnel densities.</p> Full article ">Figure 7
<p>Evacuation process for passengers in a subway train and the tunnel in Case 4 (Unit: People/m<sup>2</sup>).</p> Full article ">Figure 8
<p>Curve of the evacuation passengers versus time in Case 4.</p> Full article ">Figure 9
<p>Smoke movement and temperature distribution in a tunnel for luggage fire and oil pool fire with different smoke exhaust conditions.</p> Full article ">Figure 10
<p>The curve of evacuees versus time in Cases 5 to 9.</p> Full article ">
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