Search Results (99)

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

This work—mixing an original experimental approach, as well as numerical simulations—proposes to study film boiling modes around a small nickel sphere. While dealing with a simple looking phenomenon that is found in many industrial processes and has been solved for basic quenching regimes, we focus on describing precisely how vapor formation and film thicknesses, as well as vapor bubble evacuation, affect cooling kinetics. As instrumenting small spheres may lead to experimental inaccuracies, we optically captured, using a high-speed camera, the vapor film thickness at mid height, the vapor bubble volume, and the bubble detachment frequency, along with the heat flux. More precisely, an estimation of the instant sphere temperature, in different conditions, was obtained through cooling time measurement before the end of the film boiling mode, subsequently facilitating heat flux evaluation. We encountered a nearly linear decrease in both the vapor film thickness and vapor bubble volume as the sphere temperature decreased. Notably, the detachment frequency remained constant across the whole temperature range. The estimation of the heat fluxes confirmed the prevalence of conduction as the primary heat transfer mode; a major portion of the energy was spent increasing the liquid temperature. The results were then compared to finite element simulations using an in-house multiphysics solver, including thermic phase changes (liquid to vapor) and their hydrodynamics, and we also captured the interfaces. While presenting a challenge due to the contrast in densities and viscosities between phases, the importance of the small circulations along them, which improve the heat removal in the liquid phase, was highlighted; we also assessed the suitability of the model and the numerical code for the simulation of such quenching cases when subcooling in the vicinity of a saturation temperature. Full article

The safety of pipeline transportation technology is the key to guaranteeing the development and application of CCUS. In the process of CO₂ pipeline transportation, manual pressure relief may be required due to equipment failure, overpressure, or other reasons. However, the sharp temperature drop in the evacuation process may lead to the formation of dry ice, which may cause a pipeline blockage and equipment damage. Although the multi-stage throttling method of pressure relief can effectively control the stability of the equipment, the effect on the low temperature of the pipeline needs to be further investigated. Therefore, in order to evaluate the safety of multi-stage throttling pressure relief, a comparative experiment of dense-phase venting with double-stage throttling was carried out based on an industrial-scale pipeline experimental device. The results show that the double-stage throttling pressure relief scheme can significantly reduce the pressure drop rate and improve the stability of the pressure relief structure. Moreover, the temperature drop limit upstream of the main pipeline is controlled under the double-stage throttling scheme, but it exacerbates the low temperature level downstream, which is not conducive to mitigating the risk of freeze-plugging of the pressure relief valve. Therefore, it is recommended that the double-stage throttling relief scheme be used to close the valve in time to return to the temperature and to adopt an intermittent means of pressure relief. Full article

Powders with phase composition including quasi-amorphous phases and calcium carbonate CaCO₃ in the form of calcite or aragonite and sodium halite NaCl as a reaction by-product were synthesized from 0.5M aqua solutions of sodium silicate and 0.5M aqua solutions of calcium and/or magnesium chlorides. Starting solutions were taken in quantities which could provide precipitation of hydrated calcium and/or magnesium silicates with molar ratios Ca/Si = 1 (CaSi), Mg/Si = 1 (MgSi) or (Ca+Mg)/Si = 1 (CaMgSi). Hydrated calcium and/or magnesium silicates, hydrated silica, magnesium carbonate, hydrated magnesium carbonate or hydrated magnesium silicate containing carbonate ions are suspected as components of quasi-amorphous phases presented in synthesized powders. Heat treatment of synthesized powders at 400, 600, 800 °C and pressed preceramic samples at 900, 1000, 1100 and 1200 °C were used for investigation of thermal evolution of the phase composition and microstructure of powders and ceramic samples. Mass loss of powder samples under investigation during heat treatment was provided due to evacuation of H₂O (m/z = 18), CO₂ (m/z = 44) and NaCl at temperatures above its melting point. After sintering at 1100 °C, the phase composition of ceramic samples included wollastonite CaSiO₃ (CaSi_1100); enstatite MgSiO₃, clinoenstatite MgSiO₃ and forsterite Mg₂SiO₄ (MgSi_1100); and diopside CaMgSi₂O₆ (CaMgSi_1100). After sintering at 1200 °C, the phase composition of ceramics CaSi_1200 included pseudo-wollastonite CaSiO₃. After heat treatment at 1300 °C, the phase composition of MgSi_1300 powder included preferably protoenstatite MgSiO₃. The phase composition of all samples after heat treatment belongs to the oxide system CaO–MgO–SiO₂. Ceramic materials in this system are of interest for use in different areas, including refractories, construction materials and biomaterials. Powders prepared in the present investigation, both via precipitation and via heat treatment, can be used for the creation of materials with specific properties and in model experiments as lunar regolith simulants. Full article

Architectural design seeks to address many challenges, one of which is creating buildings that can quickly and safely evacuate people. Therefore, it is even more important to pay attention to the safety of personnel evacuation. Past disasters have shown that the number of casualties in large sports stadiums can be as severe as those caused by plane crashes. This study uses a case study approach to analyze the evacuation of spectators in a 40,000-seat stadium, comparing the practical application of three performance verification methods. The results indicate that Simulex’s visual dynamic simulation effectively reflects how walking speeds decrease in crowded conditions and how bottlenecks form along evacuation routes. People tend to gather at corners, leading to congestion and uneven distribution of evacuees, with several escape staircases being underutilized. The Guide to Safety at Sports Grounds is suitable for the early planning stages of architectural design, while the “Verification Guideline of Buildings Evacuation Safety Performance-based Design” is better suited for the detailed design phase to ensure compliance with the safety standard of evacuating spectators within 8 min. Compared to planning and designing based solely on regulations or empirical verification formulas, using visualization software allows for effective adjustments to evacuation routes before finalizing the design, balancing crowd flow across all safety exits and improving evacuation efficiency during the operational phase. Full article

Landslide hazard chains pose significant threats in mountainous areas worldwide, yet their cascading effects remain insufficiently studied. This study proposes an integrated framework to systematically assess the landslide-landslide dam-outburst flood hazard chain in mountainous river systems. First, landslide susceptibility is assessed through a random forest model incorporating 11 static environmental and geological factors. The surface deformation rate derived from SABS-InSAR technology is incorporated as a dynamic factor to improve classification accuracy. Second, motion trajectories of rock masses in high-risk zones are identified by Rockfall Analyst model to predict potential river blockages by landslide dams, and key geometric parameters of the landslide dams are predicted using a predictive model. Third, the 2D HEC-RAS model is used to simulate outburst flood evolution. Results reveal that: (1) incorporating surface deformation rate as a dynamic factor significantly improves the predictive accuracy of landslide susceptibility assessment; (2) landslide-induced outburst floods exhibit greater destructive potential and more complex inundation dynamics than conventional mountain flash floods; and (3) the outburst flood propagation process exhibits three sequential phases defined by the Outburst Flood Arrival Time (FAT): initial rapid advancement phase, intermediate lateral diffusion phase, and mature floodplain development phase. These phases represent critical temporal thresholds for initiating timely downstream evacuation. This study contributes to the advancement of early warning systems aimed at protecting downstream communities from outburst floods triggered by landslide hazard chains. It enables researchers to better analyze the complex dynamics of such cascading events and to develop effective risk reduction strategies applicable in vulnerable regions. Full article

Effective evacuation is vital for minimizing casualties during disasters. This study employed the Web of Science (WOS) database to perform a bibliometric analysis of the evacuation literature. VOSViewer (v1.6.20) and CiteSpace (v6.3.R1) software were used to visualize publication trends, international collaboration networks, keyword co-occurrence, clustering, and keyword bursts. The findings indicate that three research focuses are foundational to advancing the field of evacuation research, with shifts in these areas reflecting the dynamic nature of the field’s transition. Four key research themes outline the core content of the field’s investigation. Furthermore, this study identifies three key research phases in evacuation: the theoretical model development and foundational research phase, the behavioral dynamics and advanced simulation phase, and the data-driven intelligence and practical application phase. Future directions of evacuation research are discussed. This study provides a comprehensive analytical framework that deepens the understanding of the evacuation field. Full article

Media platforms provide an effective way to gauge public perceptions, especially during mass disruption events. This research explores public responses to the 2023 Ohio train derailment event through Twitter, currently known as X, and Google Trends. It aims to unveil public sentiments and attitudes by employing sentiment analysis using the Valence Aware Dictionary and Sentiment Reasoner (VADER) and topic modeling using Latent Dirichlet Allocation (LDA) on geotagged tweets across three phases of the event: impact and immediate response, investigation, and recovery. Additionally, the Self-Organizing Map (SOM) model is employed to conduct time-series clustering analysis of Google search patterns, offering a deeper understanding into the event’s spatial and temporal impact on society. The results reveal that public perceptions related to pollution in communities exhibited an inverted U-shaped curve during the initial two phases on both the Twitter and Google Search platforms. However, in the third phase, the trends diverged. While public awareness declined on Google Search, it experienced an uptick on Twitter, a shift that can be attributed to governmental responses. Furthermore, the topics of Twitter discussions underwent a transition across three phases, changing from a focus on the causes of fires and evacuation strategies in Phase 1, to river pollution and trusteeship issues in Phase 2, and finally converging on government actions and community safety in Phase 3. Overall, this study advances a multi-platform and multi-method framework to uncover the spatiotemporal dynamics of public perception during disasters, offering actionable insights for real-time, region-specific crisis management. Full article

Street-type spaces, characterized by their relative closedness and propensity for human congregation, inherently carry potential safety evacuation risks. In order to study the influence of slopes on the evacuation efficiency of pedestrians in street-type public spaces under the state of passenger flow surge during holidays, this study systematically analyzes the changing rules and behavioral characteristics of pedestrian evacuation in downhill movement through a three-phase analysis of the risk of crowd gathering in urban street-type spaces (before, during, and after) and evacuation simulation experiments combining variables such as slope, street width, obstacle layout, disability type, and group movement. The findings indicate that, in the structural design of street-type spaces, slopes of more than 4° should be minimized to maintain the smooth flow of pedestrians. Areas in streets with widths narrower than 2 m are high-risk zones for crowd gathering and should be better supervised. The number and location of obstacles should be reasonably arranged under the condition of satisfying the safety of pedestrians’ passage. The differences in the ability of evacuees should be taken into account to improve evacuation system deficiencies and ensure that everyone can evacuate safely. Ultimately, we propose a preventive mechanism for the safe evacuation of urban street-type public spaces to reduce the risk of crowd gathering and safeguard pedestrians. This study provides a theoretical framework for understanding the dynamics of pedestrian evacuation in inclined street-type spaces, thereby guiding urban planners and public safety managers to enhance the design and management of such spaces. Full article

Against the backdrop of global climate change, extreme weather events, such as heavy rainfall, typhoons, tsunamis, and rising sea levels, have become frequent, posing unprecedented challenges to human society. As an important strategy for coastal cities to respond to climate change, climate-induced evacuation is influenced by complex and diverse factors. This study delves into the driving mechanisms of population migration willingness, revealing the dynamic balance of push, pull, and resistance factors and their interaction with individual value orientations affecting migration decisions. By constructing a Logistic Regression Model, this research quantitatively analyzes the significant impacts of personal circumstances, family characteristics, living conditions, risk perception, compensation relocation, and supportive policies on climate-induced migration willingness, using Shanghai as a case study. The findings indicate that age, education level, household size, housing type, risk perception, and compensation policies are key factors. Building upon the multidimensional capital interaction mechanisms and dynamic threshold response patterns identified in the research, this study proposes a three-phase progressive policy framework: initially, establishing an integrated human–material–social capital framework to implement tiered relocation incentive programs, which address decision window constraints through cognitive empowerment and asset replacement strategies; subsequently, creating a dynamic compensation adjustment mechanism by developing policy toolkits aligned with inverted U-shaped utility curves while enhancing synergistic effects between cultural cognition transformation and vocational training; and ultimately, innovating an institutional–cultural co-governance paradigm that rebalances public service dependency and place attachment through spatial equity redistribution. Specific recommendations encompass designing modular risk education curricula, establishing social network transplantation mechanisms, piloting climate citizenship regimes, and constructing cross-border governance knowledge platforms. These multidimensional interventions encompassing capital restructuring, threshold responsiveness, and cultural adaptation offer valuable policy insights for resolving the “development resilience–migration inertia” paradox in coastal cities. Full article

Previously we suggested a new pharmaceutical derived from coordination complex of Co³⁺ with polyacrylic acid (PAA) exhibiting hemostatic and microbicidal activity, namely Hestatin. Differences in the physiological activity of Hestatin synthesized from PAA 10 kDa (Hestatin 10) and 200 kDa (Hestatin 200) were shown. We tested the acute toxicity of Hestatin and its effect on the healing rate of sterile wounds in rats. Free 10 kDa PAA, emulsion wax, emulsion wax carrying resveratrol, and dexpanthenol were tested for comparison. Hestatin 10 exhibited no acute toxicity when administered intragastrically at dosages of 5 g per kg. Hestatin 10 surpassed all tested drugs in its wound healing ability. Histological analysis of skin sections of rats in the area of healing defects showed an increased rate of synthesis of reticular fibers compared to the placebo. In the early stages of wound healing (inflammatory phase), Hestatin 10 stimulated taxis of mast cells (MCs) to the wound bottom but not to the wound perimeter. At the final stage of wound healing (remodeling phase), Hestatin 10 promoted MC evacuation from the skin defect area. This effect is the opposite of the well-known wound-healing agents (dexpanthenol and resveratrol), which enhance MC infiltration into the defect area in the remodeling phase. Full article

A fresh paradigm for classifying current studies on flood management systems is proposed in this review. The literature has examined methods for managing different flood management activities from a variety of fields, such as machine learning, image processing, data analysis, and remote sensing. Prediction, detection, mapping, evacuation, and relief efforts are all part of flood management. This can be improved by adopting state-of-the-art tools and technology. Preventing floods and ensuring a prompt response after floods is crucial to ensuring the lowest number of fatalities as well as minimizing environmental and financial damages. The following noteworthy research questions are addressed by the framework: (1) What are the main methods used in flood control? (2) Which stages of flood management are the majority of research currently in existence focused on? (3) Which systems are being suggested to address issues with flood control? (4) In the literature, what are the research gaps regarding the use of technology for flood management? To classify the many technologies that have been studied, a framework for classification has been provided for flood management. It was found that there were few hybrid models for flood control that combined machine learning and image processing. Furthermore, it was discovered that there was little use of machine learning-based techniques in the aftermath of a disaster. To provide efficient and comprehensive disaster management, future efforts must concentrate on integrating image processing methods, machine learning technologies, and the understanding of disaster management across all phases. The study has proposed the use of Generative Artificial Intelligence. Full article

With the continued recognition of the devastating effects of natural hazards, the construction of shelters has become essential in urban disaster preparedness planning systems. After analyzing the deficiency of the conventional spatial allocation model of shelters and the hierarchy of evacuation assignments, this study proposes a bi-level and two-phase spatial configuration methodology of shelters. The first hierarchy aims to evacuate refugees from demand blocks to both emergency shelters and resident emergency congregate shelters. The second hierarchy aims to transfer refugees from selected shelters in the first hierarchy to resident emergency congregate shelters. Each hierarchy contains two phases of optimizing calculations. The optimization objects for the first phase and second phase are minimizing the number of new shelters and the evacuation time, respectively. A genetic algorithm and exhaustive approach are programmed to determine the solution of the model in the first and second phases, respectively. The evacuation assignment rule is proposed based on the gravity model, which distributes evacuees proportionally to nearby shelters. This study uses the deterministic user equilibrium problem to present the evacuation traffic flow allocation, which improves the scientificity of the location model of shelters. The refuge demands differentiate the population between daytime and nighttime through mobile signaling data and improve the accuracy from the plot scale to the building scale. Using mobile signaling data to differentiate refuge demands between day and night populations enhances the model’s precision. Finally, to validate the proposed methodology, this study selected the main area of Changshu City, Jiangsu Province, China, which has a population of 1.6 million, as a case study area. Full article

Background: In recent decades, the size and passenger capacity of cruise/passenger ships has been associated with noticeable growth; in turn, this has created significant concerns regarding the adequacy of existing evacuation protocols during an “abandon the ship” situation (life threatening emergency). This study provides a systematic overview of related weaknesses and challenges, identifying critical factors that influence evacuation efficiency, and also proposes innovative/interdisciplinary solutions to address those challenges. It further emphasizes the growing complexity of cruise/passenger ship evacuations due to increased vessel size/heavy density of human population, as well as identifying the necessity of addressing both technical and human-centered elements to enhance safety and efficiency of those specific operations. Methods: Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach, a comprehensive systematic literature search was conducted across academic databases, including Scopus, Science Direct, Google Scholar, and a limited number of academic journals that are heavily maritime-focused in their mission. Emphasis was placed on peer-reviewed articles and certain gray studies exploring the impacts of ship design, human behavior, group dynamics, and environmental conditions on evacuation outcomes. This review prioritized research incorporating advanced simulation models, crowd management solutions (applied in various disciplines, such as stadiums, airports, malls, and ships), real-world case studies, and established practices aligned with contemporary maritime safety standards. Results: The key findings identify several critical factors influencing the overall evacuation efficiency, including ship heeling angles, staircase configurations, and passenger (physical) characteristics (with their mobility capabilities and related demographics clearly standing out, among others). This effort underscores the pivotal role of group dynamics, including the influence of group size, familiarity among the group, and leader-following behaviors, in shaping evacuation outcomes. Advanced technological solutions, such as dynamic wayfinding systems, real-time monitoring, and behavior-based simulation models, emerged as essential tools for optimizing an evacuation process. Innovative strategies to mitigate identified challenges, such as phased evacuations, optimized muster station placements, and tailor made/strategic passenger cabin allocations to reduce congestion during an evacuation and enhance the overall evacuation flow, are also highlighted. Conclusions: Protecting people facing a life-threatening situation requires timely preparations. The need for a holistic evacuation strategy that effectively integrates specific ship design considerations and human factors management, along with inputs related to advanced information technology-related solutions, is the best way forward. At the same time, the importance of real-time adaptive management systems and interdisciplinary approaches to address the challenges of modern cruise/passenger ship evacuations clearly stands out. These findings provide a robust foundation for future research and practical applications, contributing to advancements in maritime safety and the development of efficient evacuation protocols for large-in-size cruise/passenger vessels. Full article

Advancements in 3D modelling technology have facilitated more immersive and efficient solutions in spatial planning and user-centred design. In healthcare systems, 3D modelling is beneficial in various applications, such as emergency evacuation, pathfinding, and localization. These models support the fast and efficient planning of evacuation routes, ensuring the safety of patients, staff, and visitors, and guiding them in cases of emergency. To improve urban modelling and planning, 3D representation and analysis are used. Considering the advantages of 3D modelling, this study proposes a framework for 3D indoor navigation and employs a multiphase methodology to enhance spatial planning and user experience. Our approach combines state-of-the art GIS technology with a 3D hybrid model. The proposed framework incorporates federated learning (FL) along with edge computing and Internet of Things (IoT) devices to achieve accurate floor-level localization and navigation. In the first phase of the methodology, Quantum Geographic Information System (QGIS) software was used to create a 3D model of the building’s architectural details, which are required for efficient indoor navigation during emergency evacuations in healthcare systems. In the second phase, the 3D model and an FL-based recurrent neural network (RNN) technique were utilized to achieve real-time indoor positioning. This method resulted in highly precise outcomes, attaining an accuracy rate over 99% at distances of no less than 10 metres. Continuous monitoring and effective pathfinding ensure that users can navigate safely and effectively during emergencies. IoT devices were connected with the building’s navigation software in Phase 3. As per the performed analysis, it was observed that the proposed framework provided 98.7% routing accuracy between different locations during emergency situations. By improving safety, building accessibility, and energy efficiency, this research addresses the health and environmental impacts of modern technologies. Full article