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Mass shooting cases have caused large casualties worldwide. The counterforce, such as the policemen, is of great significance to reducing casualties, which is the core issue of social safety governance. Therefore, we model both the killing force and counterforce, to explore the crowd dynamics under the shooting. Taking the "Borderline" shooting in 2018 as the target case, the agent-based modeling is applied to back-calculate this dynamic process and explore key behavior rules of individuals. The real death tolls of three classes of agents (civilians, policemen, & killers) are as the real function, based on which we calculate the gaps between real target case and simulations. Eventually, we obtain three optimal solutions, which achieve the least gap or highest matching degree. Besides, we make counterfactual inferences under the optimal solutions, to explore the strategic interactions between policemen and killers. For strategies of killers, we explore different sizes, positions, and moving patterns of the killers. The optimal size of policemen is four to five, for each one killer. For strategies of policemen, we explore the size, locations, and the response time. It indicates that optimal response time of policemen is thirty to forty shots of the killer, and the death of civilians and policemen can be minimized, and the death probability of the killer can be maximized. These findings help to improve public safety governance for our cities. To effectively deal with sudden shooting terrorist cases, patrol routes, reasonable settings, and swift dispatches of the police (stations) should be considered. [ABSTRACT FROM AUTHOR]

Rapid perception of the location of the fire point is crucial to building fire emergency response in the process of building fire emergency response, which can help firefighters direct fire-fighting operations, effectively control fire sources, and provide strong evidence for the analysis and investigation of fire causes. This paper uses acoustic CT temperature measurement technology to determine the fire source location of a building fire and verifies its validity and applicability as follows: we construct various fire point numerical models based on the fire dynamics simulator (FDS) and obtain temperature data at different times; neural network means were used to obtain the time-of-flight (TOF) of an acoustic wave traveling; the large ill-conditioned matrix equation of acoustic flight under different meshing schemes was constructed and solved based on the simultaneous algebraic reconstruction technique (SART) and least squares QR-decomposition (LSQR), and then reconstruction temperature data under each scheme were obtained. Through the error analysis, the reconstruction effect of each reconstruction scheme is evaluated, and then the applicability of the location coordinate determination of the fire point is analyzed. The results show that the determination of the fire location under the conditions of various fire points in the building space can be realized by acoustic CT temperature measurement technology. [ABSTRACT FROM AUTHOR]

During an evacuation from a building, the use of particular exits may vary significantly resulting in some becoming crowded while others are rarely used, which may cause inefficient egress. In this study, a new method of quantifying this varying exit usage and subsequently categorizing them into five different performance groups is proposed. This method is expected to allow us to compare the performance of exits in the same building as well as exits between separate buildings. To quantify the exit usage, the actual numbers of occupants using specific exits for a certain period are needed as well as the design occupant load and design number of occupants using the specific exits. The former values are obtained by actually counting occupants and the latter values are determined by exit design criteria, i.e., calculations found in building and life safety codes. Seven exits are selected from two buildings and their performance is compared quantitatively as a proof of concept. We hope these equations can be used in future research for the quantitative and qualitative study of exit usage. [ABSTRACT FROM AUTHOR]

Building fires are one of the most common fire types and tend to cause heavy casualties. During the evacuation, the shortest path makes the escapees leave the accident scene faster. Meanwhile, the safety of escapees in the evacuation process cannot be ignored. Optimal path should both ensure evacuation efficiency and maximize the safety of escapees. A bi-objective path planning model, which considers both path risk and path length, is presented. Path risk is based on five risk factors that are likely to cause casualties in a fire: carbon monoxide (CO), hydrogen cyanide (HCN), temperature, visibility, and crowding. The linear weighted sum method is used to convert the risk-objective model and the length-objective model into a dynamic bi-objective path planning model. The Dijkstra algorithm is modified to solve the model. The modified algorithm outperforms the traditional Dijkstra algorithm in terms of both efficiency and adjustment ability. The simulation analysis of a building fire shows that the bi-objective model and algorithm can plan a combined optimal evacuation path for escapees considering risk and path length, which avoids the area with high risk level and optimizes the evacuation path length. [ABSTRACT FROM AUTHOR]

In modern buildings, false ceilings are widely used for building services systems and aesthetic purposes, but they also pose challenges in terms of fire safety. A fire accident typically results from the failure of multiple safety measures or components. In many fire accidents, fire and smoke reached the false ceiling and kept spreading in the interstitial space without any detection. This study first generates a numerical database of false ceiling fire scenarios by varying the room dimensions, false-ceiling leakage area, fire size and locations. Then, a smart model based on machine learning to predict the fire smoke motion below and above the false ceiling is developed. The trained model is capable to predict the activation time of fire detectors and sprinklers for any given false ceiling design and fire scenario. This methodology enables a designer to generate multiple fire scenarios and determine the available safe egress time (ASET) for performance-based fire engineering designs especially in terms of fire detection time. In case of a real fire, with the data feed from the fire sensor network, the trained machine learning model can further predict the critical building fire events with the false ceiling, such as multi-compartment fires, smoke in the evacuation path, and structural failures. This work proposes a smart framework for improving the building fire safety design of false ceilings and the sensor-driven fire forecast to support firefighting.It enhances the emergency response processes by enabling dynamic risk assessment through prediction of critical events. [ABSTRACT FROM AUTHOR]

This paper introduces an emotion-based BDI (Belief, desire, intention) methodology to model decision-making during fire evacuation simulations while considering human emotions. The methodology is designed to represent human decision-making processes in graphical representations, which can be simply translated for the implementation phase to simulate various case studies. The methodology utilizes the Belief, Desire, and Intention architecture and the OCEAN Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism) personality behavior to represent decision-making processes graphically, making it easy to translate into a simulation. The methodology aims to create a more realistic simulation closer to real human behavior by incorporating emotions that affect decision-making. In this paper, we validate the emotion-based BDI methodology by replicating the bushfire Australia case study and benchmarking with the previous work on BDI fire evacuation. From the comparison, we found that both results share almost similar patterns. The results show "dead while still unaware" (0% vs. 0%), "dead while deciding what to do" (69% vs. 48%), "dead while defending" (6% vs. 8%), and "dead while preparing to defend" (6% vs 28%), "dead while preparing to escape" (4% vs 0%) and "dead while escaping" (15% vs 20%). The results show that in our Simulation, there is a death related to preparing to escape (4% vs 0%). However, the other causes of death have an almost similar percentage of death causes. Hence, based on the comparison, supporting and validating our emotion-oriented simulation model is considered adequate. Therefore, this emotion-based BDI methodology can systematically reproduce human cognition and emotion. [ABSTRACT FROM AUTHOR]

Mission Critical Buildings (MCB) are buildings that must remain operational in the event of a crisis to minimize risks due to asset damage, business interruption, and personnel impact. MCBs in processing facilities face operational hazards including explosions, fragments, fires, and toxic events. In the CSB's investigation report of the Philadelphia Energy Solutions Refinery incident, a recommendation was included for the API to update its standard to "require protection of critical safeguards and associated control system components from fire and explosion hazards, including radiant heat and flying projectiles." This recommendation, if implemented, would require facilities to ensure MCBs are Multi‐hazard Resistant Buildings (MRBs) able to withstand a range of potential impacts. This paper details the key design characteristics of MRBs to protect critical assets in industrial processing facilities such as critical safeguards and control systems; emergency response equipment; people critical to operations and emergency response; or people located in buildings near processing units. Key concepts of protective building design are introduced, including the response of different building materials to hazards common in processing facilities. These concepts are then examined to illustrate how building response translates to human and equipment vulnerability. [ABSTRACT FROM AUTHOR]

Large‐scale pool fires on offshore platforms can have disastrous consequences. Wind load is an essential component of the marine environment; hence, wind‐shielding facilities are installed on the platforms as needed. A computational fluid dynamics technique is used in this study to model large‐scale pool fires. The effects of wind load and windshields on large‐scale pool fires are investigated. Furthermore, the impact of the large‐scale pool fire on personnel is evaluated based on thermal radiation dose. It has been discovered that the growing horizontal momentum of the wind load might result in a significant distance of fatal injury. The windshields have double‐edged effects, including that: (1) they can reduce the injury distance by preventing the spread of fire products; and (2) they could block the release of heat and smoke. It is advised that while installing windshields on offshore platforms, different fire scenarios need to be considered. This research can be used to provide technical support for the development of the emergency evacuation strategy and layout design of offshore platforms. [ABSTRACT FROM AUTHOR]

After a strong earthquake, criteria are needed to determine whether buildings are safe to reoccupy based on observable damage. This paper presents a simulation‐based methodology to identify relevant damage indicators and safety thresholds for building structures. Prior knowledge of the most relevant damage indicators and their thresholds can increase the accuracy and confidence of post‐earthquake evaluations. Current practice to translate observable damage into a tagging decision relies on qualitative guidelines based on past earthquake experience and judgment, which may be susceptible to speculation and interpretation. In addition, past experience may not be relevant to newer structural systems and to large or complex (e.g., high‐rise) buildings. To augment past observations and data from structural component tests, nonlinear dynamic analyses can be used to estimate the collapse safety of structures with simulated damage. Technologies to execute these simulations have matured over the years, although to date they have not been systematically applied to evaluate the destabilizing effects of simulated damage on collapse safety. In this paper, a methodology is presented to use numerical simulations of damage to identify and evaluate relevant damage indicators that can be quantitatively related to safety thresholds. Damage indicators are selected based on their reliability in estimating the structural safety and their sensitivity to modeling uncertainty, that is, where the preferred indicators are insensitive to variability in the structural materials and model parameters. The safety threshold for each damage indicator is selected to maximize accuracy in post‐earthquake building assessments. The methodology is demonstrated through an application study of ductile reinforced concrete frame buildings. Results show that aggregated indices of structural component damage (e.g., aggregated over the floor of a building) outperform other damage indicators based on peak or residual drifts or simpler percentages of damaged components. Subject to agreement of a number underlying assumptions, this methodology can be applied to a wider variety of structures to improve post‐earthquake evaluation guidelines. [ABSTRACT FROM AUTHOR]

To accurately simulate realistic pedestrian evacuation from a fire, a cellular automaton model of the dynamic changes in pedestrian movement parameters is developed in conjunction with fire dynamics software. The fire dynamics software is used to simulate the spread of smoke within the scene to obtain visibility and CO concentration data within the scene. We imported the smoke data into the cellular automata and adjusted the pedestrian movement speed over time, resulting in simulation data that closely align with reality. The results show that for the single-room scenario, as pedestrian density increased from 0.1 to 0.5 persons per square meter ( p / m 2 ), the influence of the percentage of pedestrians familiar with their location on evacuation efficiency decreased from 44.93% to 24.52%. Conversely, in the multi-room scenario, it increased from 23.68% to 38.79%. The proportion of pedestrians less affected by smoke decreases and stabilizes as the CO yield increases. In the single-room scenario, when the CO yield is below 10%, the crowd with a low percentage of pedestrians familiar with the site is more affected by smoke than those with a high percentage. In the multi-room scenario, the victimization rate of the crowd follows an increasing-then-decreasing curve, ultimately stabilizing with changes in CO yield. [ABSTRACT FROM AUTHOR]

The article discusses the importance of personnel safety during evacuations in industrial process plants and how wireless personnel location technology can improve evacuation processes. It mentions the issues with traditional mustering procedures, presents the medical case for faster response times, and showcases the implementation of industrial wireless technology for real-time evacuation mapping.

Evacuation models represent one of the main tools used to assess building fire safety. Existing evacuation models are based on data from evacuation drills in western and developed countries, while there is a need for data from South Asian and developing countries (in general). This paper presents the results of an evacuation drill carried out in a library of a developing country in South Asia (Pakistan). The data of 85 student evacuees were recorded and analysed. Pre‐evacuation and walking speed data have been reported in this paper which are compared with the available data for library evacuations in other countries. The average pre‐evacuation time of 24.3 s (± standard deviation [SD] = 19.83 s) obtained in this study was shorter than previously published data for similar building types in other parts of the world. Furthermore, unimpeded horizontal speeds (mean = 0.74 m/s, SD = 0.28 m/s) were also smaller than the values reported in the available literature. Stair descending speeds (mean = 0.97 m/s, SD = 0.36 m/s) were within the ranges of stair movement data listed in previous studies. These findings represent a pioneering dataset for future building designs and evacuation simulations in developing countries. [ABSTRACT FROM AUTHOR]

To ensure the safety of construction site personnel and to improve the efficiency of emergency safety evacuation of site personnel, this study analyzes the risk reasons for fire accidents and the characteristics of combustion fires on construction sites. Based on a refined BIM model, a numerical simulation of the fire situation is performed using PyroSim (2019 version) software on a construction site. In the Pyrosim fire simulation model, fire scenarios with distinct construction stages and fire source locations are set up to simulate, compare, and analyze the varying pattern of each fire product in various fire scenarios. Using this information with the Pathfinder (2019 version) simulation model, a coupled simulation test of fire evacuation is conducted to assess the safety of evacuating individuals in each fire scenario. The results show that flammable materials in open spaces are more risky to burn than in confined spaces. After optimizing the utilization of safety exits and the density of people in the second simulation, it was found that the required safety evacuation time was reduced to 267 s, which is lower than the available safety evacuation time of 318.5 s for each scenario. All fire scenarios meet the safe evacuation criteria. The study results can provide a theoretical basis for developing fire response strategies for construction units and contribute to site safety management. [ABSTRACT FROM AUTHOR]

Copyright of Fly Ash Comprehensive Utilization is the property of Hebei Fly Ash Comprehensive Utilization Magazine Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The underground space in the Starting Area in the Guangzhou International Financial City is being developed to save resources and improve land benefits. However, high-density development has increased the likelihood of fires. Therefore, PyroSim and Pathfinder were used in this study to investigate the fire smoke flow and personnel evacuation in the underground space in the Starting Area. Firstly, the 2D temperature cloud map and the temperature and visibility recorded by sensor A over time of Zone I in the Starting Area were analyzed. Then, the 3D smoke diffusion, the 3D temperature diffusion map, and the value of thermocouple and smoke obscuration recorded by sensors of Zone II were analyzed. Next, smoke flow of Zones III to V in the Starting Area under different fire source positions was simulated. Finally, the personnel evacuation model was established to simulate the personnel flow rate and density. The simulation results show that the available safe evacuation time for people is 530 s when all the firefighting facilities fail and fire breaks out in Zone I. For large public spaces, the overall spread speed of fire is fast, which requires the use of the fire control system in time to control the spread of fire. Fortunately, the space of evacuation time is relatively sufficient; it only takes 143 s to evacuate personnel safely in Zone II, which is sufficient compared to the time for the fire to completely spread. Suggestions were made for fire safety management, such as evacuating personnel to the safety exits of other adjacent areas during a fire and installing linkage fire alarm systems in large public space s. [ABSTRACT FROM AUTHOR]

Building evacuation safety has been one of the focal points of researchers, and there is a wealth of research findings for certain places (e.g., buildings with a high population density) or for particular research subjects (e.g., the physically challenged ethnic group). However, current publications are relatively rare in analyzing the features of physically impaired individuals in crowded places and their impact on the effectiveness of the whole evacuation process, including non-disabled people. Additionally, only such studies tend to concentrate on the behavioral characteristics of disabled people, which lack exploring and comparing evacuation optimization strategies and evaluation of comprehensive evacuation performance. This paper proposed a computer simulation-based method that combined horizontally phased evacuation and vertically phased evacuation, supplemented with the use of handicapped ramps and a reasonable arrangement of class locations, to achieve the optimal evacuation performance of a teaching building with special consideration of the heterogeneous population. And then, a simulated building model was constructed to test and compare the effectiveness and applicability of these approaches through 33 evacuation scenario studies. The results found that (1) component design can improve evacuation effectiveness, with the arrangement of ramps and the location of stair doors successfully reducing evacuation time by 12% and 6.6%, respectively; (2) a combination of two ramps and separate handicap access can decrease evacuation time by 18%; (3) the horizontal-phased evacuation approach drops evacuation time by 7.1%, but the vertical-phased evacuation strategy is not very efficient. When the two are successfully combined, evacuation time is further reduced to 9.2%; and (4) based on the above measures, the evacuation time can be finally shortened by 19% if the veteran teachers are concentrated in the classrooms on the lower floors. These obtained conclusions will provide significant reference and methodological support for the safe evacuation of other similar buildings with heterogeneous populations. [ABSTRACT FROM AUTHOR]

In this paper, performance-based fire-protection design is used for the fire-safety design of public amenities with restrained personnel activities. In these places, tourists' activities are constrained in a limited space such as cockpit moving along the track. Since it is another typical scenario of fire-protection problem that cannot fully comply with the current mandatory codes and regulations, simulation analysis is used in order to ensure that such fire scenario could achieve performance objectives as expected. Firstly, corresponding fire-protection performance objectives, strategies and simplified evaluation criteria are brought forward in this paper. Then, through simulating the smoke flow in the fire using the computational fluid dynamics software FDS, the effectiveness of the smoke control strategy is verified. Meanwhile, the escaping environments of these fire scenes are analyzed. Further, the personnel evacuation simulation software (Pathfinder) is resorted to simulate the personnel emergency evacuation. The efficiency and the total time that consumed are obtained. Finally, by analyzing the similarities and differences of evacuation under different fire scenes, the fire and smoke spread in the riding area can be effectively controlled, and a safe evacuation environment can be provided for the evacuation of tourists. [ABSTRACT FROM AUTHOR]

This study focuses on vehicle and pedestrian traffic management in freeway tunnels during emergencies such as fire propagation caused by traffic accidents. Such accidents can result in traffic breakdowns in a short time and a limited space, leading to severe health and safety issues. This study establishes a parsimonious bimodal tunnel evacuation management strategy that can provide real-time evacuation instructions by combining real-world historical traffic data and a cell transmission model (CTM). To exploit the evacuation capability of road tunnels with both vehicle cross and passenger passages, an equivalent cellular traffic network of a road tunnel and its escape facilities is first developed for bimodal evacuation. Simultaneously considering efficiency and social fairness in an emergency evacuation, a risk evaluation function is initially established and embedded in a system optimal objective function. The rationale of the proposed compact system models and the mechanism of effective traffic management measure generation is validated based on a real freeway tunnel emergency happened in Melba and Mullum-Mullum tunnels in Melbourne, Australia. The results suggest that the proposed CTM-based model has twinned the bimodal traffic characteristics and the flexibility to balance the evacuation efficiency and social fairness consideration in road tunnels under emergency conditions. [ABSTRACT FROM AUTHOR]

Cryogenic liquid nitrogen (LN 2) is proposed as an effective fire suppressant/extinguisher for challenging fires. Upon reaching a fire source, this inert cryogen vaporizes expediently and separates the fuel from the air. Additionally, it cools the burning fuel and slows down its pyrolysis/gasification reactions. A prior investigation concentrated on the survivability of single LN 2 droplets, following breakup of the jet exiting the nozzle, and the predicted the droplet size that reaches a target. This investigation addresses the application of a liquid nitrogen jet for the extinction of fires with a combination of experiments and theoretical analysis. Small scale laboratory experiments were conducted with a sprayer and larger scale experiments were conducted with a cryogenic hose and nozzle. In these experiments the reach of the liquid nitrogen jets was measured, and their fire extinction capabilities were assessed. Numerical simulations were performed with the ADREA-HF CFD code using the mixture approach and explicit modelling of LN 2 evaporation using the Lee model. Numerical results on the reach of a liquid nitrogen jet qualitatively matched the experimental observations for release of a liquid nitrogen jet in open atmosphere. The Lee model coefficient was found to depend strongly on the nozzle diameter. An integral model was also constructed to explore the effects of relevant parameters, such as the LN 2 storage tank pressure, the initial jet vapor quality, the jet velocity at the nozzle exit and the effects of the ambient air entrainment. Based on experiments and theoretical analysis, it became evident that for effective extinction of a fire with liquid nitrogen a commercial nozzle should have a large diameter and should be brought close to the burning target, i.e., within a few meters. As this action can pose potential safety risks to firefighters, the advancement of the nozzle towards the fire should be operated remotely. [ABSTRACT FROM AUTHOR]

This study proposes a modified cellular automaton to simulate passenger ship fire evacuation. A fire dynamics simulator (FDS) is used to simulate the firing process for the passenger ship. The generated carbon monoxide (CO) concentration, temperature, and visibility are converted into equivalent lengths and input to the equivalent field of the modified cellular automaton. The fire field is applied to keep the evacuees away from the fire. And game theory is adopted to solve the conflict in the choice of route for evacuees. With or without fire on the passenger ship, three different evacuees' densities are used to study the influence of different proportions of evacuees who are familiar with exits during the evacuation time. The positions of exits are also studied. The results show that when the fire release rate increases from 3000 to 8000 kW s−2 for the same evacuation scenario, the earliest time that evacuees are in danger is 50% earlier. The impact of fire on evacuees is greater than that of evacuees' density. In the case of two close exits or exits close to the bulkheads, the congestion near exits is obvious and has the greatest effect on the evacuation time of the high evacuees' density. [ABSTRACT FROM AUTHOR]

Copyright of Guangdong Architecture Civil Engineering is the property of Guangdong Architecture Civil Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Fire incidents in residential and industrial areas are often the cause of human casualties and property damage. Although there are existing systems that detect fire and monitor the presence of people in indoor areas, research on their implementation in embedded platforms is limited. This article introduces an ultra-lowpower embedded system for fire detection and crowd counting using efficient deep learning methods. For the prediction of fire occurrences, environmental and gas sensor along with multilayer perceptron nodes are used. For crowd counting, a custom lightweight version of YOLOv5 is introduced, using an architecture based on ShuffleNetV2, resulting in a model with low memory requirements, high accuracy predictions, and fast inference on an embedded platform. The accuracy, power consumption, and memory requirements of the proposed system are evaluated using public datasets and datasets acquired by the environmental and image sensors, and its performance is compared to that of existing approaches. [ABSTRACT FROM AUTHOR]

The spatial layout and arrangement of obstacles in the built environment significantly affect its evacuation performance. However, few researchers focus on pedestrian simulation-based design optimization of built environment under emergency evacuation conditions. In this paper, we aim to evaluate the evacuation performance of optimized design solutions for traffic space in the teaching building of a primary school based on a pedestrian simulation approach and to quantify the effect of design parameters on evacuation time. Firstly, the level of traffic space design parameters was determined and optimized design solutions for the traffic space of the school building were generated. Secondly, based on the Anylogic simulation platform, the environment module and pedestrian evacuation behaviour rules of the teaching building were built to realize the evacuation behaviour simulation. Thirdly, the effect of the traffic space design parameters on the evacuation time of the teaching building was evaluated and the most significant design parameters were identified. Finally, the optimal combination of traffic space design parameters was proposed under evacuation performance orientation. The results show that the sensitivity of the traffic space design parameters to evacuation time is 31.85%. The effect of corridor width on evacuation time is 49.06 times greater than the staircase width. The optimal design combination for the traffic space in the teaching building of the primary school is a 3.0 m wide trapezoidal corridor combined with a 3.6 m wide staircase, and a 3.0 m wide fish maw corridor combined with 3.6 m wide staircase, guided by evacuation performance. The framework developed in this paper provides technical support for the development of evacuation performance-oriented design optimization of the built environment, and the results are intended to supplement the building design specifications. [ABSTRACT FROM AUTHOR]

Counting the number of people in a specific area is crucial in maintaining proper crowd safety and management especially in highly-congested indoor scenarios. Recent convolutional neural network (CNN) approaches integrate auxiliary sub-networks to increase the accuracy of the model in estimating crowd size. However, these models require large computational costs due to additional calculations, resulting in an impractically slow inference speed for real-world applications. In this paper, we propose a fast, efficient, and robust crowd counting model called Condensed Network or ConNet. We utilize a composite technique composed of multiple compression methods to reduce the number of parameters of our proposed model. ConNet attains counting accuracy on par with state-of-the-art crowd counting methods on benchmark datasets featuring indoor scenes, while significantly reducing parameter count and increasing inference speed. Moreover, ConNet still performs accurately even with extreme changes in lighting conditions, image resolutions, and camera orientations. Our smallest model ConNet-04 has 61.0× less parameters and is at most 9.0× faster than the baseline approach. Our code and trained models are publicly available at https://github.com/mikatej/ConNet. [ABSTRACT FROM AUTHOR]

Pedestrian evacuation is an important measure to ensure disaster safety in central retail districts, the efficiency of which is affected by the synergy of road network planning indices. This paper established the typical forms of central retail district (CRD) road networks in terms of block form, network structure and road grade, taking China as an example. The experiment was designed using the orthogonal design of experiment (ODOE) method and quantified the evacuation time under different road network planning indices levels through the Anylogic simulation platform. Using range and variance analysis methods, the synergy of network density, network connectivity, road type and road width on pedestrian evacuation efficiency were studied from the perspectives of significance, importance and optimal level. The results showed that the type of CRD will affect the importance of network planning indices, and that the network connectivity is insignificant (P 0.477/0.581) in synergy; networks with wide pedestrian primary roads (30.1~40.0 m), medium secondary roads (3.1~5.0 m/side) and high density (11.0~13.0 km/km2) have the highest evacuation efficiency. From the perspective of evacuees, this paper put forward urban design implications on CRD road networks to improve their capacity for disaster prevention and reduction. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of chair burning on the concentration of toxic gases and heat exhaust in a cinema hall. Different ventilation systems, including displacement ventilation (DV), impingement jets ventilation (IJV), stratum ventilation (SV), and hybrid ventilation (combination of displacement and stratum ventilation) were considered in this study. Large Eddy Simulation (LES) of the turbulent flows was performed using Pyrosim software. Concentrations of the toxic gases (CO and CO2) and the heat generated by the fire in the exit doors have been discussed in detail. Concentrations of the generated toxic gases from the fire in all three systems were within the permissible safe ranges. However, among the tested systems, displacement ventilation and impingement jet had better results. Displacement ventilation could decrease the concentrations of soot by 31%, CO by 16%, and CO2 by 11% rather than stratum ventilation. The maximum concentrations of CO and CO2 were 6.35 ppm and 335 ppm, respectively, in the displacement ventilation system. For the stratum ventilation, the concentrations of CO and CO2 were reported 7.5 ppm and 370 ppm, respectively. Using the displacement and the impingement jet ventilation systems, the heat exhaust from door #1 and door #2 are, respectively, 66.6%, and 96% lower than those obtained by the stratum ventilation system. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to present a systematic review of the published literature on building information model (BIM)-based simulation tools used for occupant evacuation over the past 23 years. Design/methodology/approach: A literature review was conducted on BIM-based simulation tools used for occupant evacuation over the past 23 years. The search identified a total of 37 relevant papers, which were reviewed. The paper describes the use of BIM-based simulation tools over the years and identifies the research gaps. Findings: BIM-based simulation tools have undergone progressive development, with constant improvements through the integration of advanced tools and collection of more data. These tools can assist in identifying faults in the building design. The outcomes of the simulation were not entirely accurate, as real-life scenarios vary depending on the various building types and the behavior of their occupants. Research limitations/implications: This study contributes to the literature through reviewing the capabilities of BIM-based simulation tools and the different simulation methods along with their limitations. Practical implications: Fire safety engineers and architects can comprehend the utilization of BIM-based simulation tools to enhance the fire evacuation in light of their shortcomings and flaws. Originality/value: BIM-based simulation tools are becoming more advanced and widely used. There has not been a comprehensive evaluation of the capabilities of the integration of BIM tools and simulation modeling for occupant evacuation. This study guides researchers on the capabilities and efficiencies of integrated solutions for occupant evacuations and their inherent shortcomings. The study identifies future research areas in BIM-based tools for occupant evacuation. [ABSTRACT FROM AUTHOR]

Daylight improves indoor environmental quality, the physical and mental health of occupants, and their efficiency. Research in the area of human-centric lighting that considers the visual and non-visual effects of light on human vision, have focused on examining human visual perception in response to a wide variety of lighting aspects. To investigate the effect of surface materials, window size, and shading patterns on participants’ evaluation of brightness, daylight distribution, contrast, and satisfaction with view, a virtual reality experiment is implemented in a university classroom. Moreover, responses are compared with metrics (i.e., RAMMG and illumines level) to evaluate their performance and robustness. Thirty-three subjects evaluated thirteen immersive virtual environments (IVEs) with different glazing visible light transmittance, reflectance coefficient of surfaces, window to wall ratio, number of windows, and shading geometry using a Likert-type scale survey. The results indicated that participants’ evaluation of brightness is influenced by reflection coefficient of the surfaces and WWR. While daylight distribution is affected by number of windows and shading geometry in addition to other studied parameters. Based on the subjects’ responses the contrast is only affected by reflection coefficient of the surfaces. Their satisfaction with amount of outside view is also influenced by WWR and number of windows. Moreover, based on statistical results defining a specific range of acceptable contrast based on the RAMMG metric is not suggested, and users' evaluation depends on the surface material in addition to the reflection coefficient of them. Furthermore, the level of lighting perceived by people is affected by materials and their color (beside the reflection coefficient of the surfaces), number of windows (even with similar WWR), and shading pattern (even with the same aperture ratio) as well as the glazing visible light transmittance. [ABSTRACT FROM AUTHOR]

Scholars have long sought to identify key city locations that have a pronounced effect on the flow of people under various conditions. Identifying key locations makes it possible for government and/or enterprises to obtain accurate estimates as to the flow of people and thereby formulate reasonable management strategies. Note however that much of the previous research based on professional knowledge or machine learning fails to provide accurate results. Some researchers have employed CNN-based models to predict the flow of people, claiming that those models can extract freatures from multiple locations to improve prediction accuracy. Theoretically, the features extracted using CNN-based models could be used themselves as key locations for specific problems; however, the fact that the features are consolidated via multiple operations often renders interpretation difficult when applied to a real-world setting. In the current study, we developed a novel approach to the identification of key locations based on the results of a CNN-based model and the Grad-Cam kit. The structure of a CNN-based models can have a profound effect on the results of the Grad-Cam kit; therefore, we compared the results obtained using three state-of-art models as well as our CNN-LSTM. Actual flow patterns based on telecommunication data in Taipei were used to verify the efficacy of the proposed method. [ABSTRACT FROM AUTHOR]

With the characteristics of high-speed transportation, the elevator has an overwhelmingly crucial meaning footnote in an auxiliary evacuation high-rise building with more than 30 floors causing the time to be the deciding factor under the emergency condition. The study shows that using the stairway or elevator separately cannot achieve the best effect. The elevator's evacuation time depends on the number of occupants on each floor and the elevator's carrying capacity. This paper discusses how to use the stair and elevator to optimize the hybrid evacuation in high-rise buildings and proposes two goals for the evacuation model of high-rise buildings under emergency conditions. One is that both the last occupant to use the stairway and the last occupant to use the elevator reach the safe place simultaneously. The other is that we fine-tune the evacuation destinations of the occupants to balance the utilization of each evacuation path as much as possible. We present the optimization method with three steps, and the evacuation time shrunk by up to 57% according to the baseline. Finally, we compare the optimized hybrid evacuation and the single evacuation method to the previous work and give the results of the experiments. [ABSTRACT FROM AUTHOR]

As a critical factor in architectural design, emergency evacuation is influenced by numerous parameters. Designers utilize modelling software to evaluate their sketches after completion ofbasic design. However, no various alternatives of early design stages could be assessed via simulations, since it is a time-consuming procedure. In this study, deep-learning algorithms have been adapted for the assessment of the evacuation process at early design stages. The main methods applied include an image-to-image translation with a conditional GAN (Pix2Pix) and Extreme Gradient Boosting (XGBoost). The developed Pix2Pix model generates the heat maps of possible route congestions with a Structural Similarity Index (SSIM) of 0.89. Besides, the XGBoost model predicts the evacuation time with the mean absolute error (MAE) and R2 values of 36 s and 0.94, respectively. This method generates the results of intended analyses at high speed and is a reliable alternative for time-consuming evacuation simulations in early design stages. [ABSTRACT FROM AUTHOR]

Illegal construction poses a safety hazard to both cities and people and affects the social stability and long-term stability of the country. Therefore, it is important to detect illegal buildings as early as possible. However, current illegal building detection methods generally suffer from either detection cycles or low detection accuracies. To solve these challenges, this study adopts an unusual method that detects illegal building objects to prevent illegal building behavior. A detection model, CRMNet, which is based on the anchor-free detection model CenterNet, and dataset for illegal building objects are proposed. ResNet50 is selected as the backbone for extracting futures after weighing the computational cost and detection accuracy. Furthermore, Mish, a new activation function, is used to improve the identification accuracy of illegal building objects. Experimental results show that the mean average precision (mAP) of the proposed detector on the illegal building object dataset reached 88.16%, which is higher than that of other popular object detection methods. Additionally, in contrast to mainstream target detection methods, the proposed detection method has fewer parameters and a higher detection accuracy, which can be better applied to mobile devices and smart devices. [ABSTRACT FROM AUTHOR]

The number of high-rise buildings is increasing day by day in order to use the limited space more effectively in cities that are concentrated with increasing urbanization. The fact that Istanbul is the 7th city with the highest number of high-rise buildings in the world shows the place of our country in the field and the importance that should be given to the subject. One of the biggest problems encountered in high-rise buildings is long evacuation times. The extended evacuation route with the increasing number of floors makes evacuation difficult. In this study, the issue of evacuation of high-rise buildings by elevator which has been discussed and researched for many years is examined. Standards and regulations that allow evacuation by elevator in the world have been provided. The building model created on the İş Tower building in Istanbul, which has recently been the tallest building in Turkey, has been analyzed with simulations. In the study, the effect of the use of elevators on the evacuation time of the building was examined. In 5 different scenarios modeled, it was examined that what fraction of the occupants of each floor should use the elevators and stairs to reach the shortest evacuation time. As a result, it was seen that the shortest evacuation time was reached when 25% of the occupants on each floor were evacuated by elevator and the remaining 75% by stairs. In this scenario, an approximate 18% reduction in evacuation time was observed compared to the use of stairs alone. In addition, architectural factors that prevent the most effective use of the building's evacuation components are mentioned. [ABSTRACT FROM AUTHOR]

Real-time acquisition and visualization of temperature anomalies in building spaces and 3D temperature field data during fires are of vital importance for fire danger warnings, early rescue operations, evacuation commands, and subsequent fire accident investigations. Taking into account the non-contact, global (planar and spatial), and high efficiency advantages of acoustic CT temperature measurement technology, this study involved the conducting of exploratory preliminary research in order to provide new ideas for the real-time global perception of information on building fires. The detailed research objective was as follows: obtain the temperature data at any time of a fire based on Fire Dynamics Simulator (FDS) and fit them to form the base temperature distribution diagram at that time. The large ill-conditioned matrix equation of acoustic flight under the scheme of multi-grid division was then constructed. The discrete temperature data of each grid in the building space was obtained by solving the matrix equation based on algebraic reconstruction algorithm (ART) and joint algebraic reconstruction algorithm (SART). The three-dimensional temperature field reconstruction of building space was realized by the interpolation of discrete temperature data. The reconstruction effect of each scheme was evaluated through the error analysis between the reconstruction data and the basic data. The results show that the real-time reconstruction of a 3D temperature field of a building thermal field can be realized based on acoustic CT temperature measurement technology, and the reconstruction algorithm and grid division scheme have a significant control effect on the reconstruction effect. [ABSTRACT FROM AUTHOR]

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Risk-based catastrophe bonds require the estimation of losses from the convolution of hazard, exposure and vulnerability models. These models are affected by different uncertainties that arise from the definition of their input parameters. In this paper, we propose a stochastic approach to treat the uncertainty in the asset location and attributes of the exposure model. The proposed method uses the Monte Carlo sampling approach to generate a stochastic exposure database, where each asset location is generated randomly within the geometric bound of the administration, while the asset attributes (i.e. construction type and material, number of storey, building activity type and number of dwelling) are sampled from distributions built from census data. Finally, a sensitivity analysis is performed to investigate the influence of the spatial resolution of the exposure model on the average annual losses (AAL) and catastrophe bond prices. To this end, we implement four exposure models, with spatial resolution at the asset, municipality and province levels, on a study region comprising ten provinces in southern Italy. Compared to the proposed model, the exposure model where assets are relocated and aggregated at the geometric centroid of the municipality underestimates AAL by 8 % , while a higher difference (up to 20 % ) is observed for the exposure model where assets are relocated and aggregated at the geometric centroid of the province. We also consider an exposure model whose asset locations are extracted from publicly available building footprints. Yet, this latter model was incomplete for some provinces resulting in underestimation of AAL up to 90 % . Differences in catastrophe bond prices obtained from the four exposure models are less evident, with the exposure model built based on the building footprints showing a difference up to 9.5 % . [ABSTRACT FROM AUTHOR]

Concerns about fire risk reduction and rescue tactics have been raised in light of recent incidents involving flammable cladding systems and fast fire spread in high-rise buildings worldwide. Thus, governments, engineers, and building designers should prioritize fire safety. During a fire event, an emergency evacuation system is indispensable in large buildings, which guides evacuees to exit gates as fast as possible by dynamic and safe routes. Evacuation plans should evaluate whether paths inside the structures are appropriate for evacuations, considering the building's electric power, electric controls, energy usage, and fire/smoke protection. On the other hand, the Internet of Things (IoT) is emerging as a catalyst for creating and optimizing the supply and consumption of intelligent services to achieve an efficient system. Smart buildings use IoT sensors for monitoring indoor environmental parameters, such as temperature, humidity, luminosity, and air quality. This research proposes a new way for a smart building fire evacuation and control system based on the IoT to direct individuals along an evacuation route during fire incidents efficiently. This research utilizes a hybrid nature-inspired optimization approach, Emperor Penguin Colony, and Particle Swarm Optimization (EPC-PSO). The EPC algorithm is regulated by the penguins' body heat radiation and spiral-like movement inside their colony. The behavior of emperor penguins improves the PSO algorithm for sooner convergences. The method also uses a particle idea of PSO to update the penguins' positions. Experimental results showed that the proposed method was executed accurately and effectively by cost, energy consumption, and execution time-related challenges to ensure minimum life and resource causalities. The method has decreased the execution time and cost by 10.41% and 25% compared to other algorithms. Moreover, to achieve a sustainable system, the proposed method has decreased energy consumption by 11.90% compared to other algorithms. [ABSTRACT FROM AUTHOR]

Rescue and evacuation of underground interchange tunnels after a fire are challenging. Therefore, a method of integrating building information modeling (BIM) and a fire dynamic simulator (FDS) was proposed to analyze fire characteristics and personnel escapes in underground interchange tunnels. A BIM model of underground interchange tunnels was built, and then different formats (DXF and CAD) were generated and imported into Pyrosim software and Pathfinder software. With an increase in ventilation velocity, the CO concentration and temperature downstream of the fire source increased, and visibility decreased, according to simulation results. The critical ventilation velocity was 3.6 m/s at 30 MW. Evacuation simulation results suggested that the congestion of the transverse passage was very unfavorable for personnel escape: the escape time increased by 14.9% and 20% when the interior and entrance of the transverse passage were severely congested, while a 2.5 m wide transverse passage effectively reduced the escape time. Visibility was the first indicator that it did not meet the safety of the escape. After the tunnel's personnel have been evacuated, the air supply or exhaust system should be started, and smoke should be expelled at a higher velocity. It is necessary to clear the passageway quickly or increase the automatic firefighting facilities when congestion is severe. [ABSTRACT FROM AUTHOR]

The increased use of advanced technologies by consumers and hospitals is moving care closer to patients, and the challenge is one of how patient data can be shared with external care providers and patients. To support care continuity, patient data include both clinical data used by external care providers and non-clinical data used by social care providers. Care coordination of a patient outside a hospital requires peer-to-peer connectivity among a number of these clinical and social care providers, using a digital platform that aligns their goals and assigns their resource sharing responsibilities. With no single entity supporting such care coordination, most hospitals currently distribute this responsibility to several of its provider partners and patients. Such a division of responsibility with no real time feedback leads to discontinuous resource sharing, localized data analysis, and challenges in tailoring care to improve health outcomes. The goal of this paper is to propose a blockchain architecture model that uses a number of constructs for creating and assigning ownership to patient data so it can support peer-to-peer resource sharing and uses smart contracts to support goal alignment. Using two blockchain applications implemented in Hyperledger and illustrating their potential representation using the constructs in multi-chain, we develop a conceptual model for developing blockchain applications in general to support continuity of care. The generalizability of this model is illustrated by applying these constructs to four additional healthcare applications. Finally, we conclude the paper with a discussion of the limitations and directions for future research. [ABSTRACT FROM AUTHOR]

Queuing is a frequent daily activity. However, long waiting lines equate to frustration and potential safety hazards. We present a novel, personality-based model of emotional contagion and control for simulating crowd queuing. Our model integrates the influence of individual personalities and interpersonal relationships. Through the interaction between the agents and the external environment parameters, the emotional contagion model based on well-known theories in psychology is used to complete the agents' behavior planning and path planning function. We combine the epidemiological SIR model with the cellular automaton model to capture various emotional modelling for multi-agent simulations. The overall formulation involves different emotional parameters, such as patience, urgency, and friendliness, closely related to crowd queuing. In addition, to manage the order of the queue, governing agents are added to prevent the emotional outbreak. We perform qualitative and quantitative comparisons between our simulation results and real-world observations on various scenarios. Numerous experiments show that reasonably increasing the queue channel and adding governing agents can effectively improve the quality of queues. [ABSTRACT FROM AUTHOR]

Classroom thermal comfort has a direct effect on student health and educational outcomes. However, measuring thermal comfort (TC) is a non-trivial task. It is represented by several subjective metrics e.g., Thermal Sensation Vote, Thermal Comfort Vote, Thermal Preference Vote, etc. Since machine learning (ML) is being increasingly used to predict occupant comfort, multiple TC metrics for the same indoor space may yield contradictory results. This poses the challenge of selecting the most suitable single TC metric or the minimal TC metric combination for a given indoor space. Ideally, it will be a metric that can be used to predict all other TC metrics and occupant behavior with high accuracy. This work addresses this problem by using a primary student thermal comfort dataset gathered from 11 schools and over 500 unique students. A comprehensive evaluation is carried out through hundreds of TC prediction models using several ML algorithms. It evaluates the ability of TC metrics to predict (a) other TC metrics, and (b) the adaptive behavior of primary students. An algorithm is proposed to select the most suitable single TC metric or the minimal TC metric input combination. Results show that ML models can accurately predict all TC metrics and occupant-adaptive behavior using a small subset of TC metrics with an average accuracy as high as 79%. This work also found Thermal Sensation Vote to be the most significant single TC predictor, followed by Thermal Satisfaction Level. Interestingly, satisfaction with clothing was found to be as equally relevant as thermal preference. Furthermore, the impact of seasons and choice of ML algorithms on TC metric and occupant behavior prediction is shown. [ABSTRACT FROM AUTHOR]

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