Journal Description
Fire
Fire
is an international, peer-reviewed, open access journal about the science, policy, and technology of fires and how they interact with communities and the environment, published monthly online by MDPI. The Global Wildland Fire Network is affiliated with Fire.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), AGRIS, PubAg, and other databases.
- Journal Rank: JCR - Q1 (Forestry) / CiteScore - Q2 (Forestry)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 15 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Paper Types: in addition to regular articles we accept Perspectives, Case Studies, Data Descriptors, Technical Notes, and Monographs.
Impact Factor:
3.0 (2023);
5-Year Impact Factor:
3.4 (2023)
Latest Articles
Experiments on a Mine System Subjected to Ascensional Airflow Fire and Countermeasures for Mine Fire Control
Fire 2024, 7(7), 223; https://doi.org/10.3390/fire7070223 (registering DOI) - 29 Jun 2024
Abstract
The disorder and disaster evolution characteristics of ascensional airflow fires in mine ventilation systems has been the focus of mine fire research. In this work, through repeated experiments, the variation characteristics of the temperature and air volume in the main and side branches
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The disorder and disaster evolution characteristics of ascensional airflow fires in mine ventilation systems has been the focus of mine fire research. In this work, through repeated experiments, the variation characteristics of the temperature and air volume in the main and side branches of an ascensional airflow fire were obtained under different ventilation capacities. Using the TF1M(3D) software to solve the problems of mine physical ventilation and combined with the analysis of an example, the variation in the ascensional airflow fire and the process of disordered airflow in the ventilation system in an entire area mine were described in detail. Fire combustion served as the power source for uncontrolled energy release, and its fire pressure interacted with the thermal resistance of the mine ventilation, directly causing airflow disorder. As the fire intensified, the ascensional airflow fire caused the airflow in the side branch to decrease, stagnate, or reverse. Improving the fan supply capacity can not only help reduce the increase in the ventilation thermal resistance of the side branch but also help avoid the airflow reversal of the side branch. From the regular variation characteristics, the theoretical results were found to be in good agreement with the experimental results.
Full article
(This article belongs to the Section Fire Risk Assessment and Safety Management in Buildings and Urban Spaces)
Open AccessArticle
Indigenous Fire Data Sovereignty: Applying Indigenous Data Sovereignty Principles to Fire Research
by
Melinda M. Adams
Fire 2024, 7(7), 222; https://doi.org/10.3390/fire7070222 (registering DOI) - 28 Jun 2024
Abstract
Indigenous Peoples have been stewarding lands with fire for ecosystem improvement since time immemorial. These stewardship practices are part and parcel of the ways in which Indigenous Peoples have long recorded and protected knowledge through our cultural transmission practices, such as oral histories.
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Indigenous Peoples have been stewarding lands with fire for ecosystem improvement since time immemorial. These stewardship practices are part and parcel of the ways in which Indigenous Peoples have long recorded and protected knowledge through our cultural transmission practices, such as oral histories. In short, our Peoples have always been data gatherers, and as this article presents, we are also fire data gatherers and stewards. Given the growing interest in fire research with Indigenous communities, there is an opportunity for guidance on data collection conducted equitably and responsibly with Indigenous Peoples. This Special Issue of Fire presents fire research approaches and data harvesting practices with Indigenous communities as we “Reimagine the Future of Living and Working with Fire”. Specifically, the article provides future-thinking practices that can achieve equitable, sustainable, and just outcomes with and for stakeholders and rightholders (the preferred term Indigenous Peoples use in partnerships with academics, agencies, and NGOs). This research takes from the following key documents to propose an “Indigenous fire data sovereignty” (IFDS) framework: (1) Articles declared in the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP) as identified by the author and specified in Indigenous-led and allied Indigenous fire research in Australia, Canada, and the U.S.; (2) recommendations specific to cultural fire policy and calls for research in the 2023 Wildland Fire Mitigation and Management Commission report; (3) research and data barriers and opportunities produced in the 2024 Good Fire II report; and threads from (4) the Indigenous Fire Management conceptual model. This paper brings together recommendations on Indigenous data sovereignty, which are principles developed by Indigenous researchers for the protection, dissemination, and stewardship of data collected from Tribal/Nation/Aboriginal/First Nations Indigenous communities. The proposed IFDS framework also identifies potential challenges to Indigenous fire data sovereignty. By doing so, the framework serves as an apparatus to deploy fire research and data harvesting practices that are culturally informed, responsible, and ethically demonstrated. The article concludes with specific calls to action for academics and researchers, allies, fire managers, policymakers, and Indigenous Peoples to consider in exercising Indigenous fire data sovereignty and applying Indigenous data sovereignty principles to fire research.
Full article
(This article belongs to the Special Issue Reimagining the Future of Living and Working with Fire)
Open AccessArticle
Simulation Modeling of the Process of Danger Zone Formation in Case of Fire at an Industrial Facility
by
Yuri Matveev, Fares Abu-Abed, Olga Zhironkina and Sergey Zhironkin
Fire 2024, 7(7), 221; https://doi.org/10.3390/fire7070221 - 28 Jun 2024
Abstract
Proactive prevention and fighting fire at industrial facilities, often located in urbanized clusters, should include the use of modern methods for modeling danger zones that appear during the spread of the harmful combustion products of various chemicals. Simulation modeling is a method that
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Proactive prevention and fighting fire at industrial facilities, often located in urbanized clusters, should include the use of modern methods for modeling danger zones that appear during the spread of the harmful combustion products of various chemicals. Simulation modeling is a method that allows predicting the parameters of a danger zone, taking into account a number of technological, landscape, and natural-climatic factors that have a certain variability. The purpose of this research is to develop a mathematical simulation model of the formation process of a danger zone during an emergency at an industrial facility, including an explosion of a container with chemicals and fire, with the spread of an aerosol and smoke cloud near residential areas. The subject of this study was the development of a simulation model of a danger zone of combustion gases and its graphical interpretation as a starting point for timely decision making on evacuation by an official. The mathematical model of the process of danger zone formation during an explosion and fire at an industrial facility presented in this article is based on the creation of a GSL library from data on the mass of explosion and combustion products, verification using the Wald test, and the use of algorithms for calculating the starting and ending points of the danger zone for various factor values’ variables, constructing ellipses of the boundaries of the distribution of pollution spots. The developed model makes it possible to calculate the linear dimensions and area of the danger zone under optimistic and pessimistic scenarios, constructing a graphical diagram of the zones of toxic doses from the source of explosion and combustion. The results obtained from the modeling can serve as the basis for making quick decisions about evacuating residents from nearby areas.
Full article
(This article belongs to the Special Issue Fire and Explosions Risk in Industrial Processes)
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Open AccessArticle
State-to-State Rate Constants for the O(3P)H2(v) System: Quasiclassical Trajectory Calculations
by
Alexey V. Pelevkin, Ilya V. Arsentiev, Ilya N. Kadochnikov, Ivan A. Zubrilin, Evgeny P. Filinov and Denis V. Yakushkin
Fire 2024, 7(7), 220; https://doi.org/10.3390/fire7070220 - 28 Jun 2024
Abstract
The rate constants of elementary processes in the atom–diatom system , including the processes of vibrational relaxation and dissociation, were studied using the quasiclassical trajectory method. All calculations were carried out along
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The rate constants of elementary processes in the atom–diatom system , including the processes of vibrational relaxation and dissociation, were studied using the quasiclassical trajectory method. All calculations were carried out along the ground potential energy surface (PES) 3 that was approximated by a neural network. Approximation data were obtained using ab initio quantum chemistry methods at the extended multi-configuration quasi-degenerate second-order perturbation theory XMCQDPT2 in a basis set limit. The calculated cross-sections of the reaction channels are in good agreement with the literature data. A complete set of state-to-state rate constants was obtained for the metathesis reaction, the dissociation and relaxation of the H2 molecule upon collision with an O atom. According to these data, Arrhenius approximations over a wide temperature range were obtained for the thermal rate constants of considered processes. Data obtained on the dissociation constants and VT relaxation of vibrationally excited H2 molecules can be used in constructing kinetic models describing the oxidation of hydrogen at high temperatures or highly nonequilibrium conditions.
Full article
(This article belongs to the Special Issue State-of-the-Art on Hydrogen Combustion)
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Open AccessArticle
Exploring the Cross-Sectoral Joint Fire Management Mode Driven by Fire Information in China: From the Perspective of Organizational Interaction
by
Yuwei Song and Jida Liu
Fire 2024, 7(7), 219; https://doi.org/10.3390/fire7070219 - 27 Jun 2024
Abstract
With the increase in types of fire risk and the expansion of fire management coverage, it is urgent to involve multiple subjects in fire management. Cross-sectoral joint fire management is a new fire management mode based on collaboration between the fire management sector
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With the increase in types of fire risk and the expansion of fire management coverage, it is urgent to involve multiple subjects in fire management. Cross-sectoral joint fire management is a new fire management mode based on collaboration between the fire management sector and the industry management sector in China. Additionally, fire information from multiple sources plays a significant role in the formation of the cross-sectoral joint fire management mode. To explore the operating characteristics and influencing factors of the cross-sectoral joint fire management mode, this paper constructed a cross-sectoral joint fire management game model by focusing on the interactions and game relationships between multiple organizations. Through numerical simulation analysis, the mechanisms by which the sharing level, coverage range, and disclosure degree of fire information influence the evolution of the game system are investigated. The results show that with the improvement in the sharing level, the coverage range, and the disclosure degree of fire information, although the evolutionary paths of the game system and game subjects’ strategies are different, the cross-sectoral joint fire management game system can form a stable strategy combination of (1,1,1). This indicates that the sharing level, coverage range, and disclosure degree of fire information play positive driving roles in the formation of the cross-sectoral joint fire management mode. Furthermore, it is found that the fire management sector has a greater influence on the cross-sectoral joint fire management mode. Finally, the implications of improving the effectiveness of cross-sectoral joint fire management are proposed: enhancing institutional support, promoting information sharing, and expanding channels for information disclosure.
Full article
(This article belongs to the Special Issue Advances in Industrial Fire and Urban Fire Research)
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Open AccessArticle
Evaluating the Combustion Performance of the Usual Timbers in Furniture Using a Grey Correlation Method Based on Thermolysis, Ignition, and Flame Spread
by
Zhijin Yu, Jiani Song, Lan Xu and Hao Zhang
Fire 2024, 7(7), 218; https://doi.org/10.3390/fire7070218 - 26 Jun 2024
Abstract
Timber is the most widely used material for furniture in view of its characteristics of light mass, high strength, easy processing, coloring, and decorative appearance. However, the flammability of wood has been frequently associated with increased fire intensity and the rapid spread of
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Timber is the most widely used material for furniture in view of its characteristics of light mass, high strength, easy processing, coloring, and decorative appearance. However, the flammability of wood has been frequently associated with increased fire intensity and the rapid spread of fire in buildings. In this paper, the combustion performance of six kinds of common furniture timber was investigated based on thermogravimetric analysis at 25–500 °C, cone calorimetry with 50 kW/m2 thermal radiation intensity, and flame spread experiments with 3 kW/m2 thermal radiation intensity. The ignition, weight loss, thermogenesis, smoke, and flame spread characteristics of these timbers were obtained. Subsequently, a comprehensive index system including thermal stability, heat release ability, smoke production capacity, and flame spreading speed was constructed to evaluate the combustion performance of the selected timbers. In addition, a grey correlation method relying on the game theory to assign weight was proposed for the quantitative analysis of the relevant evaluation indexes. As a result, the combustion performance of the six kinds of timber, which was defined as a specific value from poor to good, was as follows: pine (0.8696) > Chinese fir (0.8568) > Oriented Strandboard (OSB) (0.8425) > density board (0.8122) > plywood (0.8087) > elm (0.7909). Timber with poor combustion performance contributes to the reduction in fire risk in buildings. Our suggestions are of great significance for selecting furniture timber from the perspective of the prevention and control of building fires.
Full article
(This article belongs to the Special Issue Fire Prevention and Control in Urban Infrastructure and Underground Space: 2nd Edition)
Open AccessArticle
Study on Liquid Hydrogen Leakage and Diffusion Behavior in a Hydrogen Production Station
by
Xiang Fu, Guodong Li, Shiyu Chen, Chunyan Song, Zhili Xiao, Hao Luo, Jiaqi Wan, Tianqi Yang, Nianfeng Xu and Jinsheng Xiao
Fire 2024, 7(7), 217; https://doi.org/10.3390/fire7070217 - 26 Jun 2024
Abstract
Liquid hydrogen storage is an important way of hydrogen storage and transportation, which greatly improves the storage and transportation efficiency due to the high energy density but at the same time brings new safety hazards. In this study, the liquid hydrogen leakage in
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Liquid hydrogen storage is an important way of hydrogen storage and transportation, which greatly improves the storage and transportation efficiency due to the high energy density but at the same time brings new safety hazards. In this study, the liquid hydrogen leakage in the storage area of a hydrogen production station is numerically simulated. The effects of ambient wind direction, wind speed, leakage mass flow rate, and the mass fraction of gas phase at the leakage port on the diffusion behavior of the liquid hydrogen leakage were investigated. The results show that the ambient wind direction directly determines the direction of liquid hydrogen leakage diffusion. The wind speed significantly affects the diffusion distance. When the wind speed is 6 m/s, the diffusion distance of the flammable hydrogen cloud reaches 40.08 m, which is 2.63 times that under windless conditions. The liquid hydrogen leakage mass flow rate and the mass fraction of the gas phase have a greater effect on the volume of the flammable hydrogen cloud. As the leakage mass flow rate increased from 5.15 kg/s to 10 kg/s, the flammable hydrogen cloud volume increased from 5734.31 m3 to 10,305.5 m3. The installation of a barrier wall in front of the leakage port can limit the horizontal diffusion of the flammable hydrogen cloud, elevate the diffusion height, and effectively reduce the volume of the flammable hydrogen cloud. This study can provide theoretical support for the construction and operation of hydrogen production stations.
Full article
(This article belongs to the Special Issue Hydrogen Safety: Challenges and Opportunities)
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Open AccessArticle
Experimental Investigation into Shockwave and Flame Characteristics of Hydrogen Released through Various Pressure Relief Devices
by
Chen Kuang, Shishuai Nie, Yujie Lin, Di Liu, Xiaodong Ling, Guoxin Chen, Yi Liu and Anfeng Yu
Fire 2024, 7(7), 216; https://doi.org/10.3390/fire7070216 - 26 Jun 2024
Abstract
This paper presents an experimental investigation into shockwave and flame characteristics of compressed hydrogen released through various types of pressure relief devices (PRDs) for which data have not been previously reported. Burst disks and safety valves with different set pressure (P0
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This paper presents an experimental investigation into shockwave and flame characteristics of compressed hydrogen released through various types of pressure relief devices (PRDs) for which data have not been previously reported. Burst disks and safety valves with different set pressure (P0) of 22–140 MPa were tested. Shockwave intensity/velocity spontaneous ignition/flame behavior was monitored by in-situ pressure/light sensors, respectively. Previous works have mostly focused on burst disks with low P0 (under 10 MPa), leaving safety valves and high-pressure burst disks uninvestigated. It was found that shockwave/spontaneous ignition behavior differs with PRD types. Spontaneous ignition occurs in all burst disk cases, along with an ignition/self-extinguishment/reignition process with relatively low P0, which has not been revealed previously. In contrast, none of the safety valves cause spontaneous ignition, resulting from the absence of shockwave due to lower overpressure values/rise rate during release. This suggests that shockwave formed by sudden release is the most dominant factor in spontaneous ignition. Also, the occurrence of self-extinguishment does not guarantee the absence of jet flame. This work provides a comprehensive database revealing shockwave and flame characteristics of hydrogen released through different PRDs, which offers basic data and theoretical support for the safety and risk assessment of high-pressure hydrogen facilities.
Full article
(This article belongs to the Special Issue Fire Safety Management and Risk Assessment)
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Open AccessArticle
Research on an Edge Detection Method Applied to Fire Localization on Storage Racks in a Warehouse
by
Liang Zhang, Changsong Liu, Mingyang Li, Wei Zhang, Desheng Zhang and Zhibao Lu
Fire 2024, 7(7), 215; https://doi.org/10.3390/fire7070215 - 26 Jun 2024
Abstract
When a fire occurs on storage racks in a warehouse, it is not advisable to find the location of the fire point accurately, because there are a large number of goods on the storage rack, and many interference factors such as light will
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When a fire occurs on storage racks in a warehouse, it is not advisable to find the location of the fire point accurately, because there are a large number of goods on the storage rack, and many interference factors such as light will disturb the precise location of the fire. In response to the above problems, and thanks to the high-speed growth of deep learning technology, we propose an edge detection method and apply it in fire locations successfully. We adopt VGG-16 as our backbone and introduce an attention module to suppress background information and eliminate interference. We test the proposed method on our collected dataset, and the results show that our proposed model can extract the shelf edges more completely and locate the fire point accurately. In terms of detection speed, our method can achieve 0.188 s per image, which meets the requirements of real-time detection. Our approach lays a good foundation for the precise extinguishing of fire that occurs on storage racks.
Full article
(This article belongs to the Special Issue Advances in Building Fire Safety Engineering)
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Open AccessArticle
Fire-RPG: An Urban Fire Detection Network Providing Warnings in Advance
by
Xiangsheng Li and Yongquan Liang
Fire 2024, 7(7), 214; https://doi.org/10.3390/fire7070214 - 26 Jun 2024
Abstract
Urban fires are characterized by concealed ignition points and rapid escalation, making the traditional methods of detecting early stage fire accidents inefficient. Thus, we focused on the features of early stage fire accidents, such as faint flames and thin smoke, and established a
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Urban fires are characterized by concealed ignition points and rapid escalation, making the traditional methods of detecting early stage fire accidents inefficient. Thus, we focused on the features of early stage fire accidents, such as faint flames and thin smoke, and established a dataset. We found that these features are mostly medium-sized and small-sized objects. We proposed a model based on YOLOv8s, Fire-RPG. Firstly, we introduced an extra very small object detection layer to enhance the detection performance for early fire features. Next, we optimized the model structure with the bottleneck in GhostV2Net, which reduced the computational time and the parameters. The Wise-IoUv3 loss function was utilized to decrease the harmful effects of low-quality data in the dataset. Finally, we integrated the low-cost yet high-performance RepVGG block and the CBAM attention mechanism to enhance learning capabilities. The RepVGG block enhances the extraction ability of the backbone and neck structures, while CBAM focuses the attention of the model on specific size objects. Our experiments showed that Fire-RPG achieved an mAP of 81.3%, an improvement of 2.2%. In addition, Fire-RPG maintained high detection performance across various fire scenarios. Therefore, our model can provide timely warnings and accurate detection services.
Full article
(This article belongs to the Topic AI for Natural Disasters Detection, Prediction and Modeling)
Open AccessArticle
Wildfire Effects on the Soil Respiration and Bacterial Microbiota Composition in Mediterranean-Type Ecosystems
by
Panagiotis Dalias, Eleftherios Hadjisterkotis, Michalis Omirou, Ourania Michaelidou, Ioannis M. Ioannides, Damianos Neocleous and Anastasis Christou
Fire 2024, 7(7), 213; https://doi.org/10.3390/fire7070213 - 26 Jun 2024
Abstract
This work provides insights into the effect of fire on soil processes in Mediterranean-type ecosystems in Cyprus. Soil samples from mountainous sites that were subjected to a summer wildfire and adjacent control samples were collected. Incubations were used to estimate basal respiration and
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This work provides insights into the effect of fire on soil processes in Mediterranean-type ecosystems in Cyprus. Soil samples from mountainous sites that were subjected to a summer wildfire and adjacent control samples were collected. Incubations were used to estimate basal respiration and isolate soil CO2 release of heterotrophic microorganisms from autotrophic root respiration and heterotrophic respiration from litter decomposition. Physicochemical property changes, bacteria community changes using DNA extraction and 16S rRNA gene analysis, and the effects of ash and fresh litter addition were studied to reveal the microbial composition and the post-fire soil function. Laboratory incubation showed that burned soils constantly showed higher microbial respiration rates compared with control unburned areas, even six months after a fire. Adding ash to unburned samples increased microbial respiration, suggesting that increased nutrient availability positively corelates with the increased release of CO2 from fire-affected soil. Elevated temperatures due to the wildfire exerted significant effects on the composition of soil bacterial microbiota. Nevertheless, the wildfire did not affect the alpha-diversity of soil bacteria. New communities of microorganisms are still able to decompose fresh plant material after a fire, but at a slower rate than natural pre-fire populations.
Full article
(This article belongs to the Special Issue Effects of Fires on Forest Ecosystems)
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Open AccessArticle
Satellite Image Cloud Automatic Annotator with Uncertainty Estimation
by
Yijiang Gao, Yang Shao, Rui Jiang, Xubing Yang and Li Zhang
Fire 2024, 7(7), 212; https://doi.org/10.3390/fire7070212 - 25 Jun 2024
Abstract
In satellite imagery, clouds obstruct the ground information, directly impacting various downstream applications. Thus, cloud annotation/cloud detection serves as the initial preprocessing step in remote sensing image analysis. Recently, deep learning methods have significantly improved in the field of cloud detection, but training
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In satellite imagery, clouds obstruct the ground information, directly impacting various downstream applications. Thus, cloud annotation/cloud detection serves as the initial preprocessing step in remote sensing image analysis. Recently, deep learning methods have significantly improved in the field of cloud detection, but training these methods necessitates abundant annotated data, which requires experts with professional domain knowledge. Moreover, the influx of remote sensing data from new satellites has further led to an increase in the cost of cloud annotation. To address the dependence on labeled datasets and professional domain knowledge, this paper proposes an automatic cloud annotation method for satellite remote sensing images, CloudAUE. Unlike traditional approaches, CloudAUE does not rely on labeled training datasets and can be operated by users without domain expertise. To handle the irregular shapes of clouds, CloudAUE firstly employs a convex hull algorithm for selecting cloud and non-cloud regions by polygons. When selecting convex hulls, the cloud region is first selected, and points at the edges of the cloud region are sequentially selected as polygon vertices to form a polygon that includes the cloud region. Then, the same selection is performed on non-cloud regions. Subsequently, the fast KD-Tree algorithm is used for pixel classification. Finally, an uncertainty method is proposed to evaluate the quality of annotation. When the confidence value of the image exceeds a preset threshold, the annotation process terminates and achieves satisfactory results. When the value falls below the threshold, the image needs to undergo a subsequent round of annotation. Through experiments on two labeled datasets, HRC and Landsat 8, CloudAUE demonstrates comparable or superior accuracy to deep learning algorithms, and requires only one to two annotations to obtain ideal results. An unlabeled self-built Google Earth dataset is utilized to validate the effectiveness and generalizability of CloudAUE. To show the extension capabilities in various fields, CloudAUE also achieves desirable results on a forest fire dataset. Finally, some suggestions are provided to improve annotation performance and reduce the number of annotations.
Full article
(This article belongs to the Special Issue Intelligent Forest Fire Prediction and Detection)
Open AccessEssay
After the Greenfire Revolution: Reimagining Collective Identities of the Future Wildland Fire Workforce in a Paradigm Shift for Ecological Fire Management
by
Timothy Ingalsbee
Fire 2024, 7(7), 211; https://doi.org/10.3390/fire7070211 - 25 Jun 2024
Abstract
This concept paper explores possible collective identities for a future wildland fire workforce. Taking inspiration from the work of futurists who foresee an end to the dominant fire exclusion/suppression paradigm, and assuming that an emerging fire restoration/resilience paradigm shift replaces it, this paper
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This concept paper explores possible collective identities for a future wildland fire workforce. Taking inspiration from the work of futurists who foresee an end to the dominant fire exclusion/suppression paradigm, and assuming that an emerging fire restoration/resilience paradigm shift replaces it, this paper engages in speculative explorations of the process and product of this paradigm shift with respect to the future collective identities of a workforce conducting ecological fire management. Social constructionist assumptions from symbolic interactionist sociological theory, Gramscian political theory’s concept of hegemony, and new social movement theory’s concept of collective identity all provide the intellectual foundations for the discussion. This concept paper argues that in order to actualize a paradigm shift, more than advances in scientific research or reforms of government policies will be required—the wildland fire community will need to become (or join) a social movement engaged in collective actions. An imaginary social movement, the “Greenfire revolution,” is invented to help illustrate how the selected theories and concepts might apply in the social construction of ecological fire management and the collective identities of its future workforce.
Full article
(This article belongs to the Special Issue Reimagining the Future of Living and Working with Fire)
Open AccessArticle
Hydrogen Jet Flame Simulation and Thermal Radiation Damage Estimation for Leakage Accidents in a Hydrogen Refueling Station
by
Xiang Fu, Xianglin Yan, Shiyu Chen, Chunyan Song, Zhili Xiao, Hao Luo, Jiaqi Wan, Tianqi Yang, Nianfeng Xu and Jinsheng Xiao
Fire 2024, 7(7), 210; https://doi.org/10.3390/fire7070210 - 22 Jun 2024
Abstract
With the rapid development of hydrogen energy worldwide, the number of hydrogen energy facilities, such as hydrogen refueling stations, has grown rapidly in recent years. However, hydrogen is prone to leakage accidents during use, which could lead to hazards such as fires and
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With the rapid development of hydrogen energy worldwide, the number of hydrogen energy facilities, such as hydrogen refueling stations, has grown rapidly in recent years. However, hydrogen is prone to leakage accidents during use, which could lead to hazards such as fires and explosions. Therefore, research on the safety of hydrogen energy facilities is crucial. In this paper, a study of high-pressure hydrogen jet flame accidents is conducted for a proposed integrated hydrogen production and refueling station in China. The effects of leakage direction and leakage port diameter on the jet flame characteristics are analyzed, and a risk assessment of the flame accident is conducted. The results showed that the death range perpendicular to the flame direction increased from 2.23 m to 5.5 m when the diameter of the leakage port increased from 4 mm to 10 mm. When the diameter of the leakage port is larger than 8 mm, the equipment on the scene will be within the boundaries of the damage. The consequences of fire can be effectively mitigated by a reasonable firewall setup to ensure the overall safety of the integrated station.
Full article
(This article belongs to the Special Issue Fire Numerical Simulation)
Open AccessArticle
Optimization Study of Fire Prevention Structure of Electric Vehicle Based on Bottom Crash Protection
by
Jianhong Chen, Peng Xiong, Kai Li and Shan Yang
Fire 2024, 7(7), 209; https://doi.org/10.3390/fire7070209 - 22 Jun 2024
Abstract
As the market share of electric vehicles continues to expand, fire accidents due to impacts from the power battery located at the bottom of the electric vehicles are receiving increasing attention. Lithium-ion batteries, as the mainstream choice of power battery for electric vehicles
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As the market share of electric vehicles continues to expand, fire accidents due to impacts from the power battery located at the bottom of the electric vehicles are receiving increasing attention. Lithium-ion batteries, as the mainstream choice of power battery for electric vehicles solving the problem that they are prone to thermal runaway due to damage when impacted, are the key to preventing and controlling fire accidents in electric vehicles. To address the protective problem of the bottom power battery of electric vehicles when it is impacted by road debris, two new types of sandwich structures with an enhanced regular hexagonal structure and semicircular arch structure as the core layer, respectively, are innovatively proposed in this article. They are used to protect the bottom power battery of electric vehicles and are compared with the traditional homogeneous protective structure in terms of protective performance. A local finite element simulation (FEM) of an electric vehicle containing the necessary components was established for simulation. Stress distribution, deformation, and energy absorption data for each component of an electric vehicle assembled with a protective structure when subjected to a bottom impact were obtained safely and cost-effectively. Three evaluation coefficients, namely, the cell shape variable (Bcmax), the protective effect parameter (ƒPE), and the total energy absorption of the structure (Ea), are proposed to compare and analyze the simulation results of different protective structures under equal mass conditions. The maximum values of the battery deformation of arched sandwich construction and reinforced honeycomb sandwich construction were 0.35 mm and 0.40 mm, respectively, which are much smaller than that of the maximum deformation of the battery under the protection of a homogeneous protective structure, which is 0.62 mm. Their protective effect parameters are 43.55 and 35.48, respectively, which proves that the optimization degree of the protective structure of the bottom of the electric vehicle after the application of the new structure is 35% or more. The total energy absorptions of the two structures are 91.77 J and 87.19 J, respectively, accounting for more than 70% of the kinetic energy in the system, which proves that the deformation of the sandwich structure can effectively absorb the kinetic energy of the collision between the road obstacle and the bottom of the car. The final results show that the arched sandwich structure showed the best impact resistance in the simulation, which can be used for the power battery’s protective structure on the electric vehicle’s bottom. This study fills a gap in local finite element modeling in electric vehicle crash simulations and provides ideas for fire prevention designs of electric vehicle structures.
Full article
(This article belongs to the Special Issue Computational Insights into Fire Safety: Modelling, Simulation, and Innovative Solutions)
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Open AccessArticle
Fire Endurance of Spherical Concrete Domes Exposed to Standard Fire
by
Abdelraouf T. Kassem, Ayman M. El Ansary and Maged A. Youssef
Fire 2024, 7(6), 208; https://doi.org/10.3390/fire7060208 - 19 Jun 2024
Abstract
Fire is considered a common hazard for civil structures. Public and administrative buildings are commonly designed by considering the standard fire rating and, in many cases, contain large compartments with central domes, in which fire growth can be significant. Moreover, tanks and underground
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Fire is considered a common hazard for civil structures. Public and administrative buildings are commonly designed by considering the standard fire rating and, in many cases, contain large compartments with central domes, in which fire growth can be significant. Moreover, tanks and underground fortified structures may be constructed as domes to support the heavy soil above. This paper numerically addressed such a case. First, an axisymmetric finite element model was developed and validated to predict the dome’s transient, thermal, structural, and thermal-structural behavior. Next, the model was used to conduct a parametric study to investigate the effects of the dome ring reinforcement, thickness, stiffness, central angle, base restraints, load type (external pressure or gravitational), and load ratio on the fire endurance of the dome. Design recommendations to increase the fire endurance of concrete domes were formulated based on the parametric study.
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(This article belongs to the Special Issue Fire Prevention and Flame Retardant Materials)
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Open AccessArticle
Data-Driven Wildfire Spread Modeling of European Wildfires Using a Spatiotemporal Graph Neural Network
by
Moritz Rösch, Michael Nolde, Tobias Ullmann and Torsten Riedlinger
Fire 2024, 7(6), 207; https://doi.org/10.3390/fire7060207 - 19 Jun 2024
Abstract
Wildfire spread models are an essential tool for mitigating catastrophic effects associated with wildfires. However, current operational models suffer from significant limitations regarding accuracy and transferability. Recent advances in the availability and capability of Earth observation data and artificial intelligence offer new perspectives
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Wildfire spread models are an essential tool for mitigating catastrophic effects associated with wildfires. However, current operational models suffer from significant limitations regarding accuracy and transferability. Recent advances in the availability and capability of Earth observation data and artificial intelligence offer new perspectives for data-driven modeling approaches with the potential to overcome the existing limitations. Therefore, this study developed a data-driven Deep Learning wildfire spread modeling approach based on a comprehensive dataset of European wildfires and a Spatiotemporal Graph Neural Network, which was applied to this modeling problem for the first time. A country-scale model was developed on an individual wildfire time series in Portugal while a second continental-scale model was developed with wildfires from the entire Mediterranean region. While neither model was able to predict the daily spread of European wildfires with sufficient accuracy (weighted macro-mean IoU: Portugal model 0.37; Mediterranean model 0.36), the continental model was able to learn the generalized patterns of wildfire spread, achieving similar performances in various fire-prone Mediterranean countries, indicating an increased capacity in terms of transferability. Furthermore, we found that the spatial and temporal dimensions of wildfires significantly influence model performance. Inadequate reference data quality most likely contributed to the low overall performances, highlighting the current limitations of data-driven wildfire spread models.
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(This article belongs to the Special Issue Machine Learning (ML) and Deep Learning (DL) Applications in Wildfire Science: Principles, Progress and Prospects)
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Open AccessArticle
All Lives Matter: A Model for Resource Allocation to Fire Departments in Portugal
by
Milad K. Eslamzadeh, António Grilo and Pedro Espadinha-Cruz
Fire 2024, 7(6), 206; https://doi.org/10.3390/fire7060206 - 18 Jun 2024
Abstract
Optimizing Resource Allocation in Fire Departments (RAFD) is crucial for enhancing Fire Protection Services (FPS) and ultimately saving lives. Efficient RAFD ensures that fire departments have the necessary resources to respond effectively to emergencies. This paper presents a method for optimizing RAFD based
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Optimizing Resource Allocation in Fire Departments (RAFD) is crucial for enhancing Fire Protection Services (FPS) and ultimately saving lives. Efficient RAFD ensures that fire departments have the necessary resources to respond effectively to emergencies. This paper presents a method for optimizing RAFD based on performance assessment results, examining its impact on Fire Department (FD) efficiency in Portugal. Evaluating data from 353 FDs, two RAFD optimization methods were assessed: one adhering to Portuguese regulations and constraints, such as budget allocation limitations, and another without such constraints. Integrating a slack-based data envelopment analysis model and mixed-integer linear programming, the study found that incorporating FD efficiency scores in RAFD improved overall efficiency at national, district, and FD levels. While adherence to Portuguese regulations led to balanced resource allocation and a 4% performance improvement at the national level, relaxing constraints yielded an 8% improvement, albeit with potential performance deterioration in some FDs. The detailed budget and efficiency metric analysis provided in this paper offers actionable insights for fire protection services enhancement. This underscores the importance of diverse optimization strategies to enhance FD efficiency, with implications for decision-makers at the Portuguese National Authority for Emergency and Civil Protection and similar organizations globally.
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(This article belongs to the Special Issue Combustion and Fire I)
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Open AccessArticle
Forest Fire Prediction: A Spatial Machine Learning and Neural Network Approach
by
Sanjeev Sharma and Puskar Khanal
Fire 2024, 7(6), 205; https://doi.org/10.3390/fire7060205 - 18 Jun 2024
Abstract
The study of forest fire prediction holds significant environmental and scientific importance, particularly in regions like South Carolina (SC) with a high incidence rate of forest fires. Despite the limited existing research on forest fires in this area, the application of machine learning
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The study of forest fire prediction holds significant environmental and scientific importance, particularly in regions like South Carolina (SC) with a high incidence rate of forest fires. Despite the limited existing research on forest fires in this area, the application of machine learning and neural network techniques presents an opportunity to enhance forest fire prevention and control efforts. Utilizing data of forest fire from the SC Forestry Commission for the year 2023, prediction models were developed incorporating various factors such as meteorology, terrain, vegetation, and infrastructure—key drivers of forest fires in SC. Feature importance analysis was employed to construct the final fire prediction model using different machine learning and neural network approaches including Decision Tree (DT), Random Forest (RF), Logistic Regression (LR), Artificial Neural Network (ANN), Support Vector Machine (SVM), and Convolutional Neural Network (CNN). Correlation coefficients analysis was employed to construct the final fire hazard map using a correlation test. The evaluation of predictive performance based on accuracy scores revealed that the DT model achieved the highest accuracy of 90.58%, surpassing other models. However, based on the kernel density map of the fire data from 2000 to 2023, the correlation test gave the better fire hazard map compared to any other machine learning or neural network approach that utilized feature importance. Nonetheless, all models achieved prediction accuracies exceeding 80%. This finding directed us to the approach based on the correlation coefficients rather than to those just based on feature importance. The overlap between fire locations and carbon hotspots provided the immediate need to mitigate the carbon loss due to fire in those locations. These results serve as a valuable resource for forest fire prediction in SC, demonstrating the efficacy of the correlation test, providing a theoretical foundation and data support for future forestry applications in the region, and showing the outperforming capability of this method compared to other approaches based on feature importance and the importance to prioritize areas to mitigate the climate change impact based upon fire prediction.
Full article
(This article belongs to the Special Issue Machine Learning (ML) and Deep Learning (DL) Applications in Wildfire Science: Principles, Progress and Prospects)
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Open AccessArticle
Assessment of Pinus halepensis Forests’ Vulnerability Using the Temporal Dynamics of Carbon Stocks and Fire Traits in Tunisia
by
Fatma Rezgui, Florent Mouillot, Nabil Semmar, Lobna Zribi, Abdelhamid Khaldi, Zouheir Nasr and Fatma Gharbi
Fire 2024, 7(6), 204; https://doi.org/10.3390/fire7060204 - 17 Jun 2024
Abstract
Carbon stocks provide information that is essential for analyzing the role of forests in global climate mitigation, yet they are highly vulnerable to wildfires in Mediterranean ecosystems. These carbon stocks’ exposure to fire is usually estimated from specific allometric equations relating tree height
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Carbon stocks provide information that is essential for analyzing the role of forests in global climate mitigation, yet they are highly vulnerable to wildfires in Mediterranean ecosystems. These carbon stocks’ exposure to fire is usually estimated from specific allometric equations relating tree height and diameter to the overall amount of aboveground carbon storage. Assessments of vulnerability to fire additionally allow for specific fire resistance (bark thickness, crown basal height) and post-fire recovery traits (cone mass for regeneration, and fine branches or leaves mass for flammability) to be accounted for. These traits are usually considered as static, and their temporal dynamic is rarely assessed, thus preventing a full assessment of carbon stocks’ vulnerability and subsequent cascading effects. This study aimed to measure the pools of carbon stocks of individual trees varying between 30 and 96 years old in the Djbel Mansour Aleppo pine (Pinus halepensis) forest in semi-arid central Tunisia in the southern range of its distribution to fit a sigmoid equation of the carbon pools and traits recovery according to age as a vulnerability framework. Allometric equations were then developed to establish the relationships between fire vulnerability traits and dendrometric independent variables (diameter at breast height, height, and live crown length) for further use in regional vulnerability assessments. The total carbon stocks in trees varied from 29.05 Mg C ha−1 to 92.47 Mg C ha−1. The soil organic carbon stock (SOC) at a maximum soil depth of 0–40 cm varied from 31.67 Mg C ha−1 to 115.67 Mg C ha−1 at a soil depth of 0–70 cm. We could identify an increasing resistance related to increasing bark thickness and basal crown height with age, and enhanced regeneration capacity after 25 years of age with increasing cone biomass, converging toward increasing vulnerability and potential cascading effects under shorter interval fires. These results should be considered for rigorous forest carbon sequestration assessment under increasing fire hazards due to climate and social changes in the region.
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(This article belongs to the Special Issue Integrated Vulnerability of Forest Systems to Wildfire: Implications on Forest Management Tools. VIS4FIRE Project)
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