Search Results (337)

To conduct an in-depth analysis of safety risks in small-scale business premises, this study employed field research to examine small restaurants, small supermarkets, convenience stores, and small hotels within a certain urban area. The investigation identified several critical safety issues across different types of establishments. In small restaurants, major concerns included inadequate emergency response capabilities among responsible personnel, insufficient fire separation between kitchen areas with open flames and public dining zones, as well as missing or malfunctioning emergency lighting and evacuation signage. Small supermarkets and convenience stores exhibited non-compliant electrical wiring installations and absent or defective fire extinguishing equipment. In small hotels, prevalent risks involved the lack of emergency escape respirators in guest rooms, the failure to install fire-rated doors in linen storage areas, and obstructed evacuation pathways due to clutter. Based on these findings, the study proposes practical countermeasures and recommendations aimed at enhancing safety standards in such premises. Full article

With the increasing frequency of global forest fires, research on the spread of forest fires has become one of the important directions in fire research. In order to improve the accuracy of surface fire spread simulation, based on relevant forest resources map preprocessing technologies, this paper takes the triangle mesh division idea of Tri-14 CA model for crowd evacuation and the Wang Zhengfei’s improved forest surface fire spread speed model as the basis, obtains the basic equation set of forest fire spread speed in 14 directions, and establishes the spatio-temporal spread mathematical model of forest surface fire. Based on the above, a software platform is established by applying computer technology to realize the calculation and visualization simulation of forest fire spread. Combined with examples, the correctness and practicability of the model software are illustrated, aiming to provide information support for forest disaster emergency departments. Full article

Designing fire evacuation strategies for hospitals involves navigating complex infrastructure and accommodating the unique needs of patients, many of whom may have limited mobility or require specialized support during emergencies. This study examines critical egress parameters and their impact on evacuation efficiency in hospital environments, emphasizing configurations that can improve safety and reduce evacuation time. Although the inclusion of smoke effects in recent evacuation models is gaining traction, their combined impact with assisted evacuation scenarios in hospital settings remains underexplored. By integrating smoke propagation data into evacuation modelling, we analyze the effects of reduced visibility and smoke spread on egress routes and occupant behavior. Findings show that smoke effects significantly increase evacuation time estimates (around 50%) compared to traditional models (without accounting for smoke effects), highlighting the risk of underestimation in practical applications, particularly in regions where strict codal compliance is lacking. The study also reveals that stairway width, number, and location substantially affect evacuation times, with about 40% reduction achieved by increasing stairway width from 44 to 66 inches. Additionally, situational awareness enhancements, such as real-time information on fire location and safe exits, can improve evacuation efficiency by about 35%. For taller hospital buildings, the findings highlight the need for implementation of situational awareness in addition to optimized egress planning to achieve safe and efficient evacuation strategies. Full article

Underground rail transit transfer stations are large-scale, complex structures with high-passenger flows, making them more vulnerable to fires and rescue challenges than other stations. Taking Zhongnan Road Metro Transfer Station in Wuhan as a project example, this study simulates two typical fire scenarios—flammable package ignition and equipment short circuits—using PyroSim to analyze changes in smoke movement, temperature, visibility, and CO concentration within the station. The required safety egress time (T_RSET) was determined according to the critical threshold. Then, the critical evacuation phase time (t_move’) at each key evacuation node was calculated by working backward from T_RSET. The threshold control of the open/close time nodes of the evacuation passages in the Pathfinder calculation was realized based on this time parameter. Based on the improved optimization algorithm method, personnel evacuation simulations are conducted to analyze evacuation characteristics, efficiency, and safety levels. Results show that the combustion characteristics of the fire source significantly affect the efficiency of passenger evacuation. The evacuation fails in Scenario 1 (flammable package) but succeeds in Scenario 2 (short circuit of an elevator circuit). Safety ratings for exits A–F are Level 1 (Good), Staircase 1 is Level 2 (Qualified), Staircases 2 and 3 are Level 3 (At Risk), and Staircase 4 is Level 4 (Poor). Finally, suggestions for improvement were proposed regarding size, quantity, and layout optimization of egress staircases. Full article

Fire is a disaster that seriously threatens people’s lives. Because fires occur suddenly and spread quickly, especially in densely populated places or areas where it is difficult to evacuate quickly, it often causes major property damage and seriously endangers personal safety. Therefore, it is necessary to detect the occurrence of fires accurately and promptly and issue early warnings. This study introduces YOLOv11-CHBG, a novel detection model designed to identify flames and smoke. On the basis of YOLOv11, the C3K2-HFERB module is used in the backbone part, the BiAdaGLSA module is proposed in the neck, the SEAM attention mechanism is added to the model detection head, and the proposed model is more lightweight, offering potential support for fire rescue efforts. The model developed in this study is shown by the experimental results to achieve an average precision (mAP@0.5) of 78.4% on the Dfire datasets, with a 30.8% reduction in parameters compared to YOLOv11. The model achieves a lightweight design, enhancing its significance for real-time fire and smoke detection, and it provides a research basis for detecting fires earlier, preventing the spread of fires and reducing the harm caused by fires. Full article

To study the impact of the psychological and behavioral characteristics of people, fire environment, and evacuation routes on fire evacuation efficiency, this study focuses on a university library as the research subject. A fuzzy logic algorithm is employed to analyze how psychological and behavioral traits influence initial evacuation speed during a fire. Also, fire data simulated using PyroSim software is integrated, with gas temperature, CO concentration, and visibility quantified through empirical formulas to adjust the reduction factor of evacuation speed, examining the effects of fire-generated products on evacuation performance. By incorporating fire environment factors into the heuristic function and refining pheromone update rules through iterative strategies, the ant colony algorithm is enhanced to achieve path planning. Results show that the psychological–environmental-route correction method improves evacuation efficiency by 16.2% compared to traditional methods without correction. This demonstrates that the proposed correction method can improve the efficiency of building fire evacuation and provides theoretical support and technical solutions for future library fire safety management. Full article

When a building normally used for exhibitions is converted into a Fangcang shelter hospital in emergency situations, its original space combination, functional flow line, and safety exits are significantly changed. When the building becomes densely populated, if an accident such as a fire, explosion, or earthquake occurs, then safe evacuation will be a serious challenge. This study systematically considers the characteristics of the building space and functional flow line after the conversion of an exhibition building to a Fangcang shelter hospital. Pathfinder software was used to simulate representative scenarios of a Fangcang shelter hospital and to analyze the main spatial factors affecting evacuation efficiency in terms of evacuation time, spatial congestion characteristics, and the exits used by personnel. Then, a targeted design optimization strategy was proposed based on the accessibility of safety exits and the internal space layout of the building. Finally, a simulation was used to verify the effectiveness of the design strategy. The results of this study provide solid theoretical support and methodological guidance for the spatial arrangement of exhibition buildings converted into Fangcang shelter hospitals so as to effectively improve the efficiency of safe evacuation and promote the resilience and safety of exhibition buildings. Full article

Ventilation in subway and railway tunnels is a critical safety component, especially during fire emergencies, where effective smoke and heat management is essential for successful evacuation and firefighting efforts. The Subway Environmental Simulation (SES, Version 4.1) model is widely used for predicting airflow and thermal conditions during fire events, but its accuracy in real-world applications requires validation. This study compares SES predictions with experimental data from the Memorial Tunnel fire ventilation tests to evaluate its performance in simulating the effects of jet fans on longitudinal ventilation. The analysis focuses on SES’s ability to predict flow rate and temperature distributions. Results showed reasonable agreement between SES-predicted airflows and temperatures. However, SES tended to underpredict temperatures upstream and near the fire source, indicating a limitation in simulating thermal behavior close to the fire. These findings suggest that SES can be a reliable tool for tunnel ventilation design if certain safety margins, based on the error values identified in this study, are considered. Nonetheless, further improvements are necessary to enhance its accuracy, particularly in modeling heat transfer dynamics and the impact of fire-induced temperature changes. Future work should focus on conducting additional full-scale test validations and model refinements to improve SES’s predictive capabilities for fire safety planning. Full article

Early evacuation during bushfires remains the safest strategy; however, in many realistic scenarios, timely evacuation is challenging, making safe sheltering a last-resort option to reduce risk compared to late evacuation attempts. However, most Australian homes in bushfire-prone areas are neither designed nor retrofitted to provide adequate protection against extreme bushfires, raising safety concerns. This study addresses this gap by investigating the concept of retrofitting a part of the residential buildings as attached safe rooms for sheltering and protection of valuables, providing a potential last-resort solution for bushfire-prone communities. Numerical simulations were conducted using the Fire Dynamics Simulator to assess heat transfer and internal temperature conditions in a representative residential building under bushfire exposure conditions. The study investigated the impact of the placement of the safe room relative to the fire front direction, failure of vulnerable building components, and the effectiveness of steel shutters in response to internal temperatures. The results showed that the strategic placement of safe rooms inside the building, along with adequate protective measures for windows, can substantially reduce internal temperatures. The findings emphasised the importance of maintaining the integrity of openings and the external building envelope, demonstrating the potential of retrofitted attached safe rooms as a last-resort solution for existing residential buildings in bushfire-prone areas where the entire building was not constructed to withstand bushfire conditions. Full article

Historical buildings are exposed to an increased risk of fire. The direct influence comes from the buildings’ structural design and the fire protection level. The fundamental principle for reducing the loss of heritage value in historical buildings due to fire is fire protection, as part of crisis management. This article focuses on selected castle buildings from Slovakia. Three castle buildings were selected based on their location in the country. All of them are currently used for museum purposes. Using an analytical form, we assessed fire hazards and fire safety measures in two parts, calculated the fire risk index, and proposed solutions. Qualitative research, which is more suitable for the issue at hand, was used to evaluate the selected objects. The main methods used in the research focused on visual assessment of the current condition of the objects and analysis of fire documentation and its comparison with currently valid legal regulations. Based on the results, we can conclude that Kežmarok Castle (part of the historical city center) has a small fire risk (fire risk index = 13 points). Trenčín Castle (situated on a rock above the city) and Stará Ľubovňa Castle (situated on a limestone hill outside the city, surrounded by forest) have an increased risk of fire (fire risk index = 50–63). Significant risk sources identified included surrounding forest areas, technical failures related to outdated electrical installations, open flames during cultural events, the concentration of highly flammable materials, and complex evacuation routes for both people and museum collections. Full article

Emergency preparedness training in organizations frequently involves simple evacuation drills triggered by fire alarms, limiting the opportunities for broader skill development. Digital technologies, particularly virtual reality (VR), offer promising methods to enhance learning for handling incidents and evacuations. However, implementing VR-based training remains challenging due to unclear integration strategies within organizational practices and a lack of empirical evidence of VR’s effectiveness. This paper explores how VR-based training tools can be implemented in schools to enhance emergency preparedness among students, teachers, and staff. Following a design science research process, data were collected from a questionnaire-based study involving 12 participants and an exploratory study with 13 participants. The questionnaire-based study investigates initial attitudes and willingness to adopt VR training, while the exploratory study assesses the VR prototype’s usability, realism, and perceived effectiveness for emergency preparedness training. Despite a limited sample size and technical constraints of the early prototype, findings indicate strong student enthusiasm for gamified and immersive learning experiences. Teachers emphasized the need for technical and instructional support to regularly utilize VR training modules, while firefighters acknowledged the potential of VR tools, but also highlighted the critical importance of regular drills and professional validation. The relevance of the results of utilizing VR in this context is further discussed in terms of how it can be integrated into university curricula and aligned with other accessible digital preparedness tools. Full article

In this article, two generalized net models (GNMs) are proposed to study the behavior and effectiveness of intelligent virtual agents (IVA) working in a risky environment under different scenarios and training algorithms. The proposed GNMs allow for the selection of machine learning algorithms such as intensity of characteristics Q-learning (InCh-Q), as well as the modification of multi-plan reinforcement learning (RL), proximal policy optimization (PPO), soft actor–critic (SAC), the generative adversarial imitation learning (GAIL) algorithm, and behavioral cloning (CB). The choice of action, the change in priorities, and the achievement of goals by the IVA are studied under different scenarios, such as fire extinguishing, rescue operations, evacuation, patrolling, and training. Transitions in the GNMs represent the scenarios and learning algorithms. The tokens that pass through the GNMs can be the GNMs of the IVA architecture or the IVA memory model, which are enriched with knowledge and experience during the experiments, as the scenarios develop. The proposed GNMs are formally correct and, at the same time, understandable, practically applicable, and convenient for interpretation. Achieving GNMs that meet these requirements is a complex problem. Therefore, issues related to the design and use of GNMs for the reliable modeling and analysis of the behavior and effectiveness of IVAs operating in a dynamic and risky environment are discussed. Some advantages and challenges in using GNMs compared to other classical models used to study IVA behavior are considered. Full article

Assessing building fire safety risks during the early design phase is vital for developing practical solutions to minimize loss of life and property. This study aims to identify research trends and provide a guiding framework for researchers by systematically reviewing the literature on integrating machine learning-based predictive methods into building fire safety design using bibliometric methods. This study evaluates machine learning applications in fire safety using a comprehensive approach that combines bibliometric and content analysis methods. For this purpose, as a result of the scan without any year limitation from the Web of Science Core Collection-Citation database, 250 publications, the first of which was published in 2001, and the number has increased since 2019, were reached, and sample analysis was performed. In order to evaluate the contribution of qualified publications to science more accurately, citation counts were analyzed using normalized citation counts that balanced differences in publication fields and publication years. Multiple regression analysis was applied to support this metric’s theoretical basis and determine the impact levels of variables affecting the metric’s value (such as total citation count, publication year, and number of articles). Thus, the statistical impact of factors influencing the formation of the normalized citation count was measured, and the validity of the approach used was tested. The research categories included evacuation and emergency management, fire detection, and early warning systems, fire dynamics and spread prediction, fire load, and material risk analysis, intelligent systems and cyber security, fire prediction, and risk assessment. Convolutional neural networks, artificial neural networks, support vector machines, deep neural networks, you only look once, deep learning, and decision trees were prominent as machine learning categories. As a result, detailed literature was presented to define the academic publication profile of the research area, determine research fronts, detect emerging trends, and reveal sub-themes. Full article

Mathematical modeling and computer visualization of hazardous zones of toxic substance cloud spread that occur during different accidents at industrial enterprises located near residential areas are in high demand to support the operational planning of evacuation measures and accident response. The possible chain-like nature of fires and explosions of containers with toxic substances inside increases the importance of predicting changes in hazardous zone parameters in real time. The objective of this study is to develop algorithms for the development of a mathematical model of a hazardous zone during an explosion and fire at an enterprise. The subject of this study is a software tool created for the visualization of hazardous substance emission zones in real time, superimposed onto a development map to determine potential damage to human health and for the operational planning of evacuation measures. The proposed model takes into account variables such as the air temperature, wind speed and direction, the mass of the substance at each explosion and fire site, etc. C# and Visual Studio 2022 languages and an SQL database were used to create a software tool for visualizing the hazardous area. The testing of the calculation model and software used for the visualization of the hazardous zones of toxic substance cloud spread are presented on the basis of explosion cases involving a railway tank containing ammonia and the combustion of polyvinyl chloride at a chemical industry enterprise. The results confirmed the operability of the software and the prospects of its use in regard to the mitigation of the consequences of human-made accidents. Full article

In this article, the application of virtual reality technology for the realistic and immersive visualization of various tasks and scenarios in fields such as power engineering and fire safety has been examined in order to help prepare students and professional electrical engineers with electrical safety, the operation of electrical substations, potential emergencies, injury prevention, fire safety, and others. Additionally, the use of machine learning algorithms to guide evacuations from hazardous environments, fault prevention, fire prediction, and discovery of conductive materials has been examined. The most frequently used algorithms in these areas have also been described and summarized, and conclusions have been made about the combined advantages of using VR and ML algorithms. Finally, the needs, contributions, and challenges of using machine learning in virtual reality projects have been examined. Full article