This study developed a three-dimensional numerical model of an actual subway station using PyroSim and evaluated smoke movement and life safety during fire scenarios through Fire Dynamics Simulator (FDS) simulations. A mesh sensitivity analysis was conducted to determine the appropriate mesh resolution, and the effects of smoke and ventilation system operation on smoke spread and life safety criteria were examined. The results showed that activating the system increased the available safe egress time (ASET) based on visibility from 208.5 s to 330.1 s, indicating improved evacuation feasibility. Temperature and toxic gas concentrations remained within acceptable limits during system operation. These findings demonstrate that smoke and ventilation systems play a critical role in enhancing the fire-safety performance of underground subway stations and provide foundational data for performance-based design and fire-safety strategies in underground structures.

Fires in postpartum care centers pose significant risks to the safety of mothers and newborns, highlighting the need for effective egress safety evaluation. This study proposes a systematic method for assessing egress safety based on the Egress Safety Ratio in postpartum care center buildings. Fire simulations were conducted to analyze the correlation between fire environment factors (e.g., temperature, toxic gases) and available safe egress time, which served as the foundation for constructing a comprehensive database. Using this database, an artificial neural network-based real-time prediction model was developed, enabling the identification of safe egress routes under various fire scenarios. Additionally, an integrated system for quantitatively evaluating Egress Safety Ratio was established. The reliability of the proposed model was validated by comparing fire simulation results with artificial neural network-based predictions using different postpartum care center floor plans, demonstrating good agreement and confirming its accuracy and effectiveness in evaluating and improving egress safety. The proposed model is expected to serve as a valuable tool for enhancing fire safety in postpartum care centers.

This work presents an evaluation of the effectiveness of active ventilation methods compared to passive ventilation methods in a typical B + GF + 9 building, focusing on the impact of burner height location on smoke control performance. The numerical model was validated using a full-scale room fire experiment involving a 4350 kJ/s wood crib load, where the HRR was calibrated via the mass loss method, achieving an RMSE of 210 kW and MRE of 5.04%. FDS simulations were conducted across six scenarios involving burners on the ground, fifth, and ninth floors. The findings demonstrate that, while natural ventilation allows the stairwell to reach lethal conditions with temperatures exceeding 180 °C and CO concentrations above 0.24%, the implementation of top-level mechanical pressurization maintains temperatures below the 60 °C tenability threshold. The mechanical ventilation system extended the Available Safe Egress Time (ASET) by 75% to 110%, with effectiveness increasing as the burner elevation approached the fan location. Overall, the study provides a validated approach for transforming stairwells into protected refuge zones in existing mid-rise buildings. Overall, merging empirical with computational methods is a proven basis for simulating scaled-up, complicated layouts. This guarantees accurate initial conditions when analyzing urban fire emergencies.

Smoke movement and accumulation during building fires remain a dominant life-safety threat, as tragically demonstrated by recent large-scale incidents such as the 2025 Kartalkaya hotel fire. Beyond obstructing visibility, smoke rapidly degrades breathable air quality, directly constraining evacuation and firefighting effectiveness. To mitigate these risks, smoke management and smoke control systems implemented through natural, mechanical and hybrid ventilation configurations are widely employed to regulate smoke stratification and preserve tenable conditions. This review provides a comprehensive and critical synthesis of smoke ventilation systems, examining their classification, design principles and operational performance across diverse building typologies. International regulatory frameworks, including EN 12101, NFPA 92 and ISO 21927, are analysed alongside performance-based design methodologies, advanced modelling tools and emerging control strategies such as artificial intelligence, sensor-driven automation and digital twins. Particular attention is given to the interaction between ventilation performance, evacuation dynamics and system resilience under variable environmental and operational conditions. Unlike conventional reviews that primarily catalogue technologies or standards, this study reframes smoke ventilation as a governing life-safety system that directly defines Available Safe Egress Time through its coupling with pressure zoning, smoke stratification stability and adaptive control logic. By positioning smoke ventilation at the core of performance-based fire safety design, the review clarifies application boundaries, identifies scenario-dependent optimisation challenges and highlights pathways for integrating intelligent control within regulatory-compliant frameworks. The findings support a shift from prescriptive system selection towards context-specific performance optimisation, providing actionable insights for researchers, engineers and policymakers engaged in the development of resilient and adaptive smoke ventilation strategies.

Fire safety in high-rise talent apartments, which is vital for safeguarding strategic human resources, was investigated to enhance evacuation resilience. A coupled fire-evacuation model was established using PyroSim and Pathfinder. This study analyzed multi-factor management strategies, including occupant vertical distribution, evacuation speed, evacuation priority settings, panic psychology, and guide intervention. Additionally, an Artificial Neural Network (ANN) model was developed using simulation data obtained under non-panic conditions to predict evacuation time and explore intelligent algorithms. Results show that the evacuation stairwells are the primary bottlenecks. Panic psychology significantly reduces evacuation efficiency, with severe panic increasing total evacuation time by up to 71.1%. The combined strategy CS4, integrating Pyramidal Vertical Distribution (VD7) and Organized Segmented Speed Control (ES6), reduced evacuation time by 17.42%. Guide intervention effectively mitigates the negative impact of panic. The ANN model achieved a coefficient of determination (R2) of 0.8695, confirming its predictive capability. Visibility was identified as the key parameter determining the Available Safe Egress Time (ASET). This study demonstrates that an integrated “hard–soft combination” strategy, complemented by intelligent modeling, offers an effective approach to building a resilient evacuation system for high-rise talent apartments.

This study analyzes the flow and dispersion characteristics of fire smoke within the complex spatial structure of a T-type subway interchange station to clarify the impact of geometric parameter variations on the smoke spread timeline and evacuation environment. A three-dimensional numerical model of a typical T-type interchange station was constructed based on field survey data, with key variables defined as the height difference (H) between the platform and concourse layers and the horizontal distance (L) from the fire source to the track intersection. Through the simulation of multiple fire scenarios, the relationship between the smoke front arrival time (T) and the critical danger time (Ts) at key evacuation nodes was quantified in relation to the structural parameters. The results demonstrated significant linear correlations between vertical smoke spread and horizontal diffusion to adjacent tracks with H and L, respectively. Conversely, smoke intrusion at the transfer stairway exhibited nonlinear behavior driven by geometric constraints. The study notably highlights the dual effect of the height difference (H) on smoke spread. Significantly, the study highlights the dual effect of the height difference (H) on evacuation safety. While an increased height difference delays the initial vertical ascent and enlarges the smoke reservoir capacity, thereby extending the available safe egress time, it simultaneously elongates the physical evacuation path. Consequently, a trade-off emerges between the dispersion delay benefit and the increased evacuation distance. Strategies proposed based on the model analysis include the control of the vertical height difference to H≤ 11 m, the installation of smoke barriers, and the optimization of the smoke control system in the transfer corridors. These findings provide a theoretical basis and quantitative evidence for the optimization of smoke control systems and emergency evacuation design in T-type subway interchange stations.

Purpose This study examines fire safety design in hospitals, aiming to identify and understand the factors that influence its effectiveness through control and evacuation while addressing challenges related to patient mobility. Design/methodology/approach The study employs a qualitative narrative approach, systematically reviewing 130 relevant articles and research papers. Conducting a systematic literature review identified 10 key factors of safe egress in hospitals that affect patient evacuation. Then, through semi-structured interviews, 25 field experts confirmed those findings and added two more key factors. Findings This study found patient mobility rate and conditions as the most crucial key factor influencing safe egress apart from the other 12 factors which are occupant types, occupant behaviour, exit characteristics, interior layout, fire spread and fire cells, building fire-rated materials, required safe egress time/available safe egress time, fire detection and suppression systems, signs and evacuation elevators, building model simulation and staff training. Research limitations/implications This study’s limitations include the non-inclusion of the most recent fire incident reports due to their unavailability to the public. Additionally, reliance on secondary data sources in some areas introduces the potential for inaccuracies. The scope of the literature review was also limited by language (English only). The robustness of the methodology followed mitigates the limitations of the study. Practical implications This study assists field professionals – including architects, fire engineers, consultants, medical staff and firefighters – as well as the general public, by providing critical design information to ensure the safe evacuation of all hospital occupants, particularly patients, thus participating in achieving the United Nation’s goals of creating safe environments and fostering sustainable, resilient infrastructure while ensuring the safety of people of all ages. Moreover, the new factor of patient mobility conditions is an addition to the body of knowledge that would interest academics. Originality/value The novelty of the study identified patient mobility conditions as the key influencer for safe fire egress at hospitals while discussing the interrelations between the 12 critical factors.

Study on personnel movement and evacuation time in large shopping mall fires

This paper presents an integrated simulation methodology that combines fire hazard modeling with pedestrian evacuation analysis to evaluate how tenability conditions affect occupant egress. In the proposed approach, fire scenarios representative of leisure and spa resorts are modeled using the Fire Dynamics Simulator (FDS). The most critical hazards—visibility reduction, oxygen depletion, and toxic gas concentrations—were integrated as dynamic 3D, time‐dependent data into evacuation simulations performed with Pathfinder. The stochastic nature of the simulations arises from variability in occupant premovement times, demographic characteristics, and walking speeds, which reflect realistic heterogeneity in evacuation behavior. The results show that poor visibility conditions reduce the available safe egress time (ASET), the time before conditions become untenable, by 55%, increase required safe egress time (RSET) by up to 26.2%, and consequently decrease the safe egress margin (the difference between ASET and RSET) by 702%. Conversely, safety systems such as sprinklers and fire doors significantly enhance egress performance, increasing ASET by 133%, reducing RSET by 3.5%, and improving the safe egress margin by 90.1% compared with scenarios without these systems. These findings demonstrate that the integrated framework not only improves the accuracy of evacuation performance assessment but also provides practical insights for real‐world performance‐based design. In particular, the methodology supports safer exit allocation, enhanced emergency planning, and the identification of architectural modifications that reduce evacuation risks.

Smouldering fires produce significant quantities of toxic smoke and gases that are responsible for severe casualties while rarely considered in building fire safety design. This work simulates smouldering smoke transport using a surrogate model with prescribed mass-loss rate, surface temperature, and CO/CO2 yields. It quantifies the hazards of low-buoyancy, CO-rich smoke from indoor smouldering fires by tracking the carbon monoxide concentration and smoke flow patterns. As the smouldering burning temperature increases, the smoke pattern changes from (1) the stagnation flow on the ground to (2) the boundary wall flow and finally to (3) two-zone structure, because a low temperature smouldering fuel induces a much weaker smoke buoyancy than a flame. Smoke stratification under a hot ceiling becomes easy to occur for a smouldering fire, preventing smoke flowing towards ceiling fire sensors and delaying the fire detection. The available safe egress time (ASET) of smouldering fire can be shorter than flaming fire under the same fuel-burning rate, showing a greater fire hazard. Building design features like roof shape, slab extension, and smoke extraction affect the smouldering smoke flow, where a sawtooth roof reduces ASET by 18% compared to a flat roof atrium. When a smouldering fire source is located under the slab extension, ASET may be reduced to less than a minute due to rapid smoke spread at floor level, while a mechanical extraction system can effectively remove low buoyancy smouldering fire smoke. This work improves our understanding of smouldering fire hazards in complex buildings and provides scientific guidelines for a more comprehensive design evaluation of building fire safety.

Abstract In this study, an artificial neural network (ANN) model was proposed to evaluate the egress safety of underground tunnels during fire. Fire simulations were carried out using the Fire Dynamics Simulator (FDS) for underground tunnels with a general cross-section, considering fire size as a key variable. In addition, egress simulations were performed using the Pathfinder program, with the spacing of cross-passage and the width of fire doors set as variables. Through this process, the available safe egress time (ASET), required safe egress time (RSET) and the number of casualties were derived for each variable, and the egress safety characteristics of underground tunnels under various parameter combinations were analysed in detail. Based on the derived data, an ANN model was developed to derive the ASET, RSET and survival rate in underground tunnels during fire incidents. The proposed ANN model is expected to efficiently evaluate the egress safety of underground tunnels with general dimensions without the need to perform additional fire and egress simulations. The ANN-based prediction model achieved coefficients of determination (R²) of 0.99 for ASET, 0.99 for RSET and 0.98 for survival rate, with average error rates of 1.72%, 1.36% and 2.31%, respectively, demonstrating very high accuracy.

The high passenger capacity and multi-compartment structure of Blended-Wing-Body (BWB) aircraft introduce new challenges for emergency evacuation. However, existing airworthiness standards, which are established based on conventional tube-and-wing aircraft, primarily assess safety through overall evacuation time, overlooking the dynamic propagation of risks in fire scenarios. To address this limitation, this study develops a fire-coupled occupant evacuation model and proposes a dynamic risk assessment framework that integrates cabin layout, evacuation pathways, and fire dynamics. By comparing the evacuation performance of a 380-seat BWB aircraft and an A350-900 under identical fire intensity conditions, the study suggests a potential for enhanced evacuation safety performance of the BWB configuration, attributed to its ability to effectively mitigate heat radiation and toxic gas dispersion. Furthermore, the conventional assessment model is refined by introducing a coupled criterion between the dynamic risk index R h and the Required Safe Egress Time (RSET), improving the robustness of localized risk evaluations. This method provides theoretical support for optimizing BWB cabin layouts and designing effective emergency response strategies.

Urban large-scale complexes, such as shopping malls, pose significant challenges for fire safety management due to their intricate spatial layouts, high population density, and diverse occupancy characteristics. Efficient fire evacuation strategies are critical for minimizing casualties and economic losses; however, existing approaches often overlook the dynamic interplay between fire propagation and human behavior, resulting in suboptimal safety assessments. This study proposes an integrated simulation framework to optimize evacuation strategies by coupling fire dynamics with pedestrian flow modeling, aiming to enhance both evacuation efficiency and personnel safety. The methodology comprises three key steps: (1) Fire scenario simulation: A Building Information Modeling (BIM)-based digital platform is constructed to simulate fire propagation. Critical fire parameters (e.g., heat release rate, combustion model) are calibrated to quantify temporal variations in smoke temperature, CO concentration, and visibility across different zones. (2) Evacuation dynamics modeling: A pedestrian evacuation model is developed by integrating demographic factors (age structure, movement speed, population density) and fire-induced regional risks, enabling realistic simulation of crowd movement under fire conditions. (3) Safety performance evaluation and strategy optimization: Safety margins at staircases are assessed by comparing Required Safe Egress Time (RSET) and Available Safe Egress Time (ASET), followed by a safety grading system to identify high-risk bottlenecks. Evacuation strategies are then optimized to mitigate these risks. A case study was conducted on a shopping mall in Chengdu to validate the framework. Simulation results indicate an initial evacuation time of 260.4 seconds. Safety performance analysis revealed critical risks at staircases A and C (1st floor) and D (2nd floor) due to insufficient safety margins. After strategy optimization, the total evacuation time was reduced to 245.5 seconds, with safety margins at the three high-risk staircases increased by 130.8 s, 115.2 s, and 72 s, respectively, fully meeting safety requirements. The overall evacuation efficiency was significantly improved. This study demonstrates the effectiveness of the proposed framework in quantifying fire risks and optimizing evacuation strategies for large-scale complexes. The integrated simulation approach provides a scientific basis for evidence-based safety management and evacuation planning, offering valuable insights for urban fire safety engineering and emergency response optimization.

Urban large-scale complexes, such as shopping malls, pose significant challenges for fire safety management due to their intricate spatial layouts, high population density, and diverse occupancy characteristics. Efficient fire evacuation strategies are critical for minimizing casualties and economic losses; however, existing approaches often overlook the dynamic interplay between fire propagation and human behavior, resulting in suboptimal safety assessments. This study proposes an integrated simulation framework to optimize evacuation strategies by coupling fire dynamics with pedestrian flow modeling, aiming to enhance both evacuation efficiency and personnel safety. The methodology comprises three key steps: (1) Fire scenario simulation: A Building Information Modeling (BIM)-based digital platform is constructed to simulate fire propagation. Critical fire parameters (e.g., heat release rate, combustion model) are calibrated to quantify temporal variations in smoke temperature, CO concentration, and visibility across different zones. (2) Evacuation dynamics modeling: A pedestrian evacuation model is developed by integrating demographic factors (age structure, movement speed, population density) and fire-induced regional risks, enabling realistic simulation of crowd movement under fire conditions. (3) Safety performance evaluation and strategy optimization: Safety margins at staircases are assessed by comparing Required Safe Egress Time (RSET) and Available Safe Egress Time (ASET), followed by a safety grading system to identify high-risk bottlenecks. Evacuation strategies are then optimized to mitigate these risks. A case study was conducted on a shopping mall in Chengdu to validate the framework. Simulation results indicate an initial evacuation time of 260.4 seconds. Safety performance analysis revealed critical risks at staircases A and C (1st floor) and D (2nd floor) due to insufficient safety margins. After strategy optimization, the total evacuation time was reduced to 245.5 seconds, with safety margins at the three high-risk staircases increased by 130.8 s, 115.2 s, and 72 s, respectively, fully meeting safety requirements. The overall evacuation efficiency was significantly improved. This study demonstrates the effectiveness of the proposed framework in quantifying fire risks and optimizing evacuation strategies for large-scale complexes. The integrated simulation approach provides a scientific basis for evidence-based safety management and evacuation planning, offering valuable insights for urban fire safety engineering and emergency response optimization.

This study investigated a high school dormitory fire scenario using an integrated approach that combined PyroSim-based fire dynamics simulation with an agent-based evacuation model. The objective was to quantitatively examine temporal variations in fire development and evacuation safety. The results showed that after 280 seconds, corridor visibility deteriorated and temperature rose rapidly, hindering evacuation. At 300-360 seconds, escape routes became effectively blocked, and after 500 seconds, evacuation was no longer feasible. The available safe egress time (ASET) was estimated to be approximately 300 seconds, whereas the required safe egress time (RSET) was 280 seconds, leaving only a narrow 20 seconds margin. This indicates a high risk of casualties owing to realistic delays or congestion. These findings underscore the critical importance of early evacuation and active fire protection systems, such as sprinklers and smoke control, to ensure dormitory fire safety. Policy implications include reinforcement of fire protection facilities, installation of smoke barriers, and regular evacuation drills in educational facilities.

This study examines the effect of fire gases on passengers’ flow during emergency evacuation from a long operational railway tunnel (8 km in length), given the tunnel’s current facilities and infrastructure, and compares it with an ideal scenario. One of the most important challenges in spaces with high populations occurs during emergency evacuation time in fire events since most injuries stem from inhaling toxic gases produced by the fire. Real conditions of the tunnel, such as emergency exit doors and ventilation, and assumptions, such as the train stop location and changes in the tunnel facilities, were considered. The effect of toxic gas inhalation evaluated on the passengers’ movement in 12 different scenarios and provided some suggestions for a safe evacuation in the shortest time. The Available Safe Egress Time was extracted from previous studies, and the base time of emergency evacuation simulation was inserted in the Pathfinder software. The results showed that the tunnel’s current status in the study area (1000-m section of the tunnel) was the worst possible outcome with over 55% of nonevacuated people. However, the construction of a separation wall with doors at distance of 100 or 200 meters (converting into a double tunnel) will result in the evacuation of 100% of passengers even without ventilation.

With the advancement of smart construction technologies, numerous high-altitude long road tunnels have been constructed in various countries in recent years. This has brought tunnel fire safety in special environments into focus as an important challenge. This study, using Pyrosim and Pathfinder software, focuses on the design parameters of personnel egress and smoke extraction systems in high-altitude tunnel fires. Through orthogonal experiments and numerical simulations, the key factors influencing available safe egress time (ASET) and required safe egress time (RSET) are systematically analyzed. In accordance with the fire safety egress principles for road tunnels, where ASET must be greater than RSET, the study proposes a set of optimal smoke extraction design parameter combinations for different altitudes. The results indicate that in natural smoke extraction mode, the influencing factors are ranked as follows: longitudinal ventilation velocity > smoke vent spacing > altitude > smoke vent area. In mechanical smoke extraction mode, the order of influence is as follows: smoke vent wind speed > smoke vent spacing > altitude > smoke vent area > longitudinal ventilation velocity. The study also finds that as altitude increases, the egress speed of personnel decreases, leading to longer egress times to safe areas for trapped individuals. Different types of evacuees also significantly affect egress speed. These findings provide valuable insights for the design and operational management of smoke extraction facilities in road tunnels.

AI-powered safe egress time assessment for complex building fire evacuation

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 (TRSET) was determined according to the critical threshold. Then, the critical evacuation phase time (tmove’) at each key evacuation node was calculated by working backward from TRSET. 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.

Given the continuous increase in occupancy in critical urban infrastructures, the adoption of evacuation strategies has become a widely recognized solution to tackle the challenges posed by natural or manmade disasters. Unfortunately, even in this modern day and age, Bangladesh has witnessed many disastrous accidents resulting in thousands of casualties due to the absence of effective emergency evacuation plans in high-occupancy infrastructures. Effective development of evacuation plans necessitates the collection of diverse data, encompassing details concerning evacuation duration along with several other factors. In light of this, the primary objective of this study is to establish a methodology to determine the total evacuation time of a 5-storeyed readymade garments factory (RMG), representing a densely populated critical infrastructure. A PTV VISWALK microsimulation model of the study infrastructure was developed to simulate evacuation scenarios to reflect the real-life occupancy data. The Social Force Model (SFM) of pedestrian dynamics has been used to represent the panic amidst people during disaster situations by tuning the walking behavior parameters. Integration of VISWALK and SFM parameters ensures the understanding of pedestrian characteristics and movement, which helps to emulate different types of evacuation scenarios. Machine learning techniques have been incorporated with the Latin Hypercube Sampling (LHS) method in our study to calibrate the parameters for creating emergency conditions to obtain the total evacuation time. Results of the microsimulations show that the minimum total evacuation time (TET) or required safe egress time (RSET) is 8 minutes 7 seconds, exceeding the available safe egress time (ASET) 5 minutes, as found in several fire drill surveys of structure with similar geometries. The findings of this study will enhance the understanding of evacuation dynamics and provide insights into the social force model parameters which can be further utilized in the optimization of emergency response strategies within similar infrastructure. The results showcased in this research will inform stakeholders regarding occupants’ safety and provide insights into the potential risks associated with the layout of analogous structures, thereby ensuring more resilient urban environments. Journal of Engineering Science 15(2), 2024, 1-12