Search Results (385)

The emergency evacuation sign system is crucial for the safety and sustainable development of urban rail transit. Dynamic emergency evacuation signs, which offer real-time guidance during emergencies, are gaining prominence. There is an urgent need to develop a dynamic system that balances perceptual and cognitive visibility. Against this backdrop, this study built a simulation experiment platform based on BIM, Unity, and VR. Eight experimental scenarios were created using the platform: two emergency events (fire/fire accompanied by power outage) × four emergency evacuation signage systems (static emergency signage system/dynamic dissuasion emergency signage system/dynamic dissuasion emergency signage system with flashing/dynamic dissuasion emergency signage system with flashing and auxiliary information), and experimental testing was completed. The evacuation behavior parameters of 39 passengers were extracted and used to construct a multidimensional indicator system. Subsequently, generalized estimation equations were applied to investigate the impact mechanism of signage systems on passengers’ evacuation behavior. Finally, the coupling coordination degree model was used to quantitatively evaluate the coupling coordination level of four emergency evacuation signage systems under different emergencies. Results indicate that compared to static signage system, the three sets of dynamic identification system schemes have a positive impact on passenger evacuation behavior and significantly reduce the number of decision-making errors. Particularly in high-risk scenarios involving fire accompanied by power outages, the dynamic dissuasion emergency signage system with flashing and auxiliary information outperforms others by achieving a better balance of reliability, efficiency, and safety. This study investigates the efficacy of various emergency evacuation signage systems across diverse emergency scenarios, offering insights for the enhanced design of such systems and thereby fostering the sustainable development of urban rail transit infrastructure. Full article

The surge in lithium-ion battery (LIB) use, essential for mass-scale renewable energy storage, raises concerns about fire hazards. However, to date, there is a lack of industry-wide understanding of large-scale LIB fire propagation. This paper suggests a translational forensic approach to promote fire safety awareness and introduces the cellular automata (CA) model coupled with the Monte Carlo (MC) approach to address the complex fire propagation simulation within an energy storage system (ESS). The objective is to demonstrate that the CA-MC model can provide a flexible and scalable connection for all levels of battery fire studies. The numerical model is coupled with experimental tests which have been performed to establish the actual timing of fire propagation from a single source. Cellular automata simulation, conducted through hybrid modeling and an applied risk analysis approach to evaluate fire hazards associated with LIBs, offers crucial insights into potential risks. The results demonstrate that, with fire incident initiation at a probability of 0.1 (10%), 33% of batteries will burn, and at a probability of 0.6 (60%) and beyond, the entire battery module will face complete burndown. Achieving full combustion of the entire module will take only approximately 42 timesteps on average, indicating rapid fire propagation. The actual time for a complete fire to occur in the battery module has been estimated to be 304 s per timestep, or 3.5 h total. Using this example, it is shown that the CA-MC approach can be extended to many other aspects of battery fire studies and is ideal as a translational tool, spanning all domains of the LIB industry. Full article

Forest fires represent a paramount natural disaster of global concern. Zhejiang Province has the highest forest coverage rate in China, and forest fires are one of the main natural disasters impacting forest management in the region. In this study, we comprehensively analyzed the spatiotemporal distribution of forest fires based on the MODIS data from 2013 to 2023. The results showed that the annual incidence of forest fires in Zhejiang Province has shown an overall downward trend from 2013 to 2023, with forest fires occurring more frequently in winter and spring. By utilizing eight contributing factors of forest fire occurrence as variables, three models were constructed: Logistic Regression (LR), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost). The RF and XGBoost models demonstrated high predictive ability, achieving accuracy rates of 0.85 and 0.92, f1-score of 0.84 and 0.92, and AUC values of 0.892 and 0.919, respectively. Further analysis using the RF and XGBoost models revealed that elevation and precipitation had the most significant effects on the occurrence of forest fires. Additionally, the predictions of forest fire risk generated by the RF and XGBoost models indicated that the incidence rate is high in the southern part of Zhejiang Province, particularly in the Wenzhou and Lishui areas, as well as in the southwest of the Hangzhou area and the north of the Quzhou area. In the future, the forest fire risk in this area can be predicted using site factors with the RF and XGBoost models, providing a scientific reference for forest management in Zhejiang Province and aiding in the prevention and mitigation of the impacts of forest fires. Full article

The safety of 18650 lithium-ion batteries is critical for the reliability and durability of electric vehicles, especially as interest in sustainable transportation grows. Battery failures, such as fires or explosions, pose significant risks to both users and manufacturers, highlighting the need for advanced power systems. This study used finite element method (FEM) simulations and crash tests to evaluate battery safety in accident scenarios. The results showed that mechanical damage, especially from collisions, can cause internal short circuits, increasing the risk of thermal runaway, especially when combined with high temperatures during normal operation or charging. This can be caused by mechanical damage to the battery causing a change in the distance inside the battery, causing it to short circuit. The results highlight the importance of designing battery systems that prevent internal short circuits, especially under extreme conditions, and the need for continuous monitoring of battery parameters to detect early signs of failure. In the context of improving battery safety, the battery not only saves lives, but also extends vehicle life, reduces electronic waste, and increases energy efficiency, which is consistent with global efforts to minimize the environmental impact of technology and promote safer transportation. Full article

Wildland firefighting is physically and mentally demanding. The aerobic capacity of firefighters is important due to the demands of the activity and the associated occupational risks. The main objectives of this study were to identify and characterise the physically demanding tasks undertaken by volunteer firefighters during wildland fires (real work conditions). A total of 125 firefighters replied to a survey about sociodemographic, biometric data, and work fitness assessment. A group of 23 was evaluated in a physical stress test using a VO_2peak protocol to determine maximum oxygen consumption and ventilatory thresholds. The physical demands and physiological responses were collected during the operations at the firefront (n = 21). The results revealed that wildland firefighting entails physical demands that exceed established reference values, with maximum oxygen uptake exceeding 40%. The cardiovascular strain is particularly notable in tasks performed near the firefront, reflecting fatigue. The physical and cardiac demands associated with forest fire fighting have been demonstrated to contribute to occupational illnesses with prolonged exposure. This study underscores the imperative for interventions to enhance the identification and real-time monitoring of physiological parameters to enhance firefighters’ overall health and well-being. Full article

Lithium titanate oxide cells are gaining attention in electric vehicle applications due to their ability to support high-current charging and their enhanced thermal stability. However, despite these advantages, safety concerns, particularly thermal runaway, pose significant challenges during abuse conditions such as overcharging. In this study, we investigated the effectiveness of various dielectric fluids in mitigating thermal runaway during overcharge abuse tests of cylindrical LTO cells with a capacity of 10 Ah. The experimental campaign focused on overcharging fully charged cells (starting at 100% State of Charge) at a current of 40A (4C). The tests were conducted under two conditions: the first benchmark test involved a cell exposed to air, while the subsequent tests involved cells submerged in different dielectric fluids. These fluids included two perfluoropolyether fluorinated fluids (PFPEs) with boiling points of 170 °C and 270 °C, respectively, a synthetic ester, and a silicone oil. The results were analyzed to determine the fluids’ ability to delay possible thermal runaway and prevent catastrophic failures. The findings demonstrate that some dielectric fluids can delay thermal runaway, with one fluid showing superior performance with respect to the others in preventing fire during thermal runaway. The top-performing fluid was further evaluated in a simulated battery pack environment, confirming its ability to mitigate thermal runaway risks. These results provide important insights for improving the safety of battery systems in electric vehicles. Full article

Previous evaluation models for cultural relic buildings in relation to fire risk fail to consider the necessity for effective firefighting and rescue capabilities in complex forest environments. This paper incorporates variables, including those pertaining to forest fires and climatic conditions, into the assessment index system. The hierarchical analysis method and the local punishment-incentive variable weighting method are employed to introduce a compensation coefficient score. A model for the evaluation of firefighting and rescue capability in a continuous area of cultural relic buildings in conjunction with the surrounding forest environment has been developed. The firefighting and rescue capability of the Yuelu Mountain scenic spot was evaluated at 73.91 (level III) using the fixed weight method and 69.52 (level IV) using the variable weight method. The variable weight method proved to be a more accurate approach for evaluating the status and importance of dynamic targets, thus enabling a more precise evaluation of the comprehensive evaluation area. The evaluation results inform the formulation of targeted improvement measures for enhancing the firefighting and rescue capabilities of cultural relic buildings. Full article

The semi-arid Caatinga biome is particularly susceptible to fire dynamics. Periodic droughts amplify fire risks, while anthropogenic activities such as agriculture, pasture expansion, and land-clearing significantly contribute to the prevalence of fires. This research aims to evaluate the effectiveness of a fire detection model and analyze the spatial and temporal patterns of burned areas, providing essential insights for fire management and prevention strategies. Utilizing deep neural network (DNN) models, we mapped burned areas across the Caatinga biome from 1985 to 2023, based on Landsat-derived annual quality mosaics and minimum NBR values. Over the 38-year period, the model classified 10.9 Mha (12.7% of the Caatinga) as burned, with an average annual burned area of approximately 0.5 Mha (0.56%). The peak burned area reached 0.89 Mha in 2021. Fire scars varied significantly, ranging from 0.18 Mha in 1985 to substantial fluctuations in subsequent years. The most affected vegetation type was savanna, with 9.8 Mha burned, while forests experienced only 0.28 Mha of burning. October emerged as the month with the highest fire activity, accounting for 7266 hectares. These findings underscore the complex interplay of climatic and anthropogenic factors, highlighting the urgent need for effective fire management strategies. Full article

Forest fires not only cause severe damage to ecosystems and biodiversity but also directly threaten the safety of human societies. Given the significant increase in both the frequency and intensity of forest fires worldwide, especially under extreme climate conditions, efficient fire detection and initial attack (IA) are particularly critical. The initial attack is a key stage in forest fire control, and the time taken for fire detection is a crucial factor influencing the success of the initial attack. In response to the challenges of forest fire prevention and control, this study explores Unmanned Aerial Vehicle (UAV) cruising strategies, aiming to develop appropriate approaches based on regional characteristics and provide efficient periodic monitoring solutions for areas with high ecological value and challenging accessibility. By optimizing UAV patrol routes, this research seeks to maximize coverage in areas with lower initial attack success rates and significantly reduce fire detection time, thereby improving detection efficiency. We developed and applied four optimization strategies, random search, high-risk first (HRF), nearest high-risk first (NHRF), and a genetic algorithm-based (GA-based) strategy, to compare different UAV flight routes. To evaluate the deployment effectiveness of the four UAV cruise strategies, we introduced two evaluation metrics: Average Grid Risk (AGR) and Average Distance Risk (ADR). Experimental results showed that the NHRF and GA-based strategies performed better. Specifically, NHRF achieved the highest high-risk coverage, ranging from 51.5% to 71.3%, significantly outperforming the random search strategy (4–7%) and the HRF strategy (23.1–37.5%). The GA-based algorithm achieved the highest grid coverage, ranging from 30% to 59.8%, far surpassing the random search strategy (4–6.6%) and the HRF strategy (10.2–19.1%). Additionally, the NHRF and GA-based strategies delivered the best AGR and ADR performance, respectively. The application of these innovative strategies and evaluation metrics enhances forest fire prevention through periodic monitoring and supports more efficient firefighting efforts. Full article

Recent research has focused on vanadium redox flow batteries (VRFBs) to address the short lifetimes and fire risks associated with lithium battery systems. While VRFBs offer advantages in safety, they suffer from low energy density and efficiency compared with lithium batteries. To improve VRFB performance, studies are exploring improvements in materials such as anodes, cathodes, and separators and optimizing operations by controlling electrolyte flow rates. However, the impact of current magnitude on VRFB efficiency has been less studied, with few analyses addressing both current and flow rate effects. This research proposes an experimental procedure to evaluate charge/discharge efficiency, energy efficiency, and system efficiency across varying current magnitudes and electrolyte flow rates, using a 40 W VRFB stack composed of four 10 W cells in series. In addition, we introduce a design method for an electrical equivalent circuit model that simulates the VRFB stack, reflecting experimental findings. The model’s accuracy was validated by comparing it with data from 11 full charge/full discharge cycle tests, which varied current and electrolyte amounts. Full article

Ensuring the safety of oil tank farms is essential to maintaining energy security and minimizing the impact of potential accidents. This paper develops a quantitative regional risk model designed to assess both individual and societal risks in oil tank farms, with particular attention to energy-related risks such as leaks, fires, and explosions. The model integrates factors like day–night operational variations, weather conditions, and risk superposition to provide a comprehensive and accurate evaluation of regional risks. By considering the cumulative effects of multiple hazards, including those tied to energy dynamics, and the stability and validity of the model are researched through Monte Carlo simulations and case application. The results show that the model enhances the reliability of traditional risk assessment methods, making it more applicable to oil tank farm safety concerns. Furthermore, this study introduces a practical tool that simplifies the risk assessment process, allowing operators and decision-makers to evaluate risks without requiring in-depth technical expertise. The methodology improves the ability to safeguard oil tank farms, ensuring the stability of energy supply chains and contributing to broader energy security efforts. This study provides a valuable method for researchers and engineers seeking to enhance regional risk calculation efficiency, with a specific focus on energy risks. Full article

Forest fires are a frequent and destructive phenomenon in Southwestern China, posing significant threats to ecological systems and human lives and property. In response to the growing need for effective forest fire prevention, this study introduces an innovative method for predicting and assessing forest fire risk. By integrating multi-source data, including optical and microwave remote sensing, meteorological, topographic, and human activity data, the approach enhances the sensitivity of risk models to vegetation water content and other critical factors. The vegetation water content is derived from both Vegetation Optical Depth and optical remote sensing data, allowing for a more accurate assessment of changes in vegetation moisture that influence fire risk. A time series prediction model, incorporating attention mechanisms, is used to assess the probability of fire occurrence. Additionally, the method includes fire spread simulations based on Cellular Automaton and Monte Carlo approaches to evaluate potential burn areas. This combined approach can provide a comprehensive fire risk assessment using the probability of both fire occurrence and potential fire spread. Experimental results show that the integration of microwave data and attention mechanisms improves prediction accuracy by 2.8%. This method offers valuable insights for forest fire management, aiding in targeted prevention strategies and resource allocation. Full article

Recently, battery electric vehicles (BEVs) have faced various technical challenges, such as reduced driving range due to ambient temperature, slow charging speeds, fire risks, and environmental regulations. This numerical study proposes an integrated thermal management system (ITMS) utilizing R290 refrigerant and a 14-way valve to address these issues, proactively meeting future environmental regulations, simplifying the system, and improving efficiency. The performance evaluation was conducted under high-load operating conditions, including driving and fast charging in various environmental conditions of 35 °C and −10 °C. As a result, the driving efficiency was 4.82 km/kWh in high-temperature conditions (35 °C) and 4.69 km/kWh in low-temperature conditions (−10 °C), which demonstrated higher efficiency than the Octovalve-ITMS applied to the Tesla Model Y. Furthermore, in fast charging tests, the high voltage battery was charged from a 10% to a 90% state of charge in 26 min at 35 °C and in 31 min at −10 °C, outperforming the Octovalve-ITMS-equipped Tesla Model Y’s fast charging time of 27 min under moderate ambient conditions. This result highlights the superior fast-charging performance of the 14-way valve-based ITMS, even under high cooling load conditions. Full article

This article presents a comprehensive statistical evaluation of defect frequency in fire alarm systems under real operating conditions, focusing on risk-based factors. The aim is not to introduce a complete RBI approach but rather to assess defect trends that can inform future RBI-based inspection strategies. The study categorizes and evaluates defects by frequency, particularly examining components such as cable and wire systems, acoustic signal devices, and the impact of detector contamination. These findings establish a foundation for developing tailored risk-based inspection and predictive maintenance strategies. A three-stage explanatory research design was employed, analyzing 4629 inspection reports with findings verified through expert surveys and cross-sample analysis. Results indicate that certain components, including acoustic devices and detectors, exhibit a significant increase in defects after 10 years, especially under challenging environmental conditions. Additionally, while ring bus technology supports less frequent functional testing, cable and wire systems require heightened attention in the early operational years. The study also identifies statistically significant trends and their potential for application to a broader system population, supporting enhanced RBI-based maintenance practices. These insights contribute to refining current maintenance approaches and offer practical recommendations for optimizing inspection routines based on risk factors. The article does not propose a system overhaul but lays essential groundwork for further research and improvement in fire alarm system reliability through targeted, risk-informed practices. Full article

With the development of modernization, traditional fossil energy reserves are decreasing, and the power industry, as one of the main energy consumption forces, has begun to pay attention to increasing the proportion of clean energy generation. With the deepening of electrification, the peak-valley difference of residential electricity consumption increases, but photovoltaic and wind power generation have fluctuations and are manifested as reverse peak regulation. Thermal power plants as the main force of peak regulation gradually reduce the market share, making nuclear power plants bear the heavy responsibility of participating in peak regulation. The traditional method of adjusting operating power by inserting and removing control rods has great safety risks and wastes resources. Therefore, this paper proposes a new energy storage system that can keep the nuclear power plant running at full power and produce hydrogen to synthesize ammonia from excess power. A comprehensive evaluation model of energy storage based on z-score data standardization and objective parameter assignment AHP (analytic hierarchy process) analysis method was established to evaluate energy storage systems according to a multi-index system. With an AP1000 daily load tracking curve as the input model, the simulation model built by Aspen Plus V14 was used to calculate the operating conditions of the system. In order to provide a construction basis for practical engineering use, Haiyang Nuclear Power Plant in Shandong Province is taken as an example. The system layout scheme is proposed according to the local environmental conditions. The accident tree analysis method is combined with ALOHA 5.4.1.2 (Areal Locations of Hazardous Atmospheres) hazardous chemical analysis software and MARPLOT 5.1.1 geographic information technology. A qualitative and quantitative assessment of risk factors and the consequences of leakage, fire, and explosion accidents caused by hydrogen and ammonia storage processes is carried out to provide guidance for accident prevention and emergency rescue. The design of an “Electric-Hydrogen-Ammonia” energy storage system proposed in this paper provides a new idea for zero-carbon energy storage for the peak shaving of nuclear power plants and has a certain role in promoting the development of clean energy. Full article