The performance of fire hose directly affects the fire extinguishing efficiency and rescue safety in fire and rescue. Proper drying can prolong the service life, improve operational reliability and reduce costs. To address the problems of high energy consumption and long processing cycles of conventional drying methods, this study proposes a collaborative drying technology that integrates infrared radiation with air source heat pump. Four comparative experimental protocols were designed (infrared drying, heat pump-infrared segmented drying, infrared-heat pump segmented drying, infrared-heat pump combined drying). A quantitative evaluation system including power consumption, SMER and MER was established to investigate the influence mechanism of different operating parameters on drying efficiency. Experimental results show that when the heat pump-infrared segmented drying mode (infrared temperature 35 ℃, mode conversion time 1.5 h) is adopted, the comprehensive performance of the system is the best. Total energy consumption is reduced to 4.74 kWh, SMER increases to 1.35 kg/kWh, and MER reaches 2.56 kg/h, representing a 27.3% reduction in energy consumption compared to traditional heat pump drying. The parameter optimization scheme proposed in this study can reduce the operating costs of the fire hose drying system and promote the sustainable use of fire hose, offering significant environmental value.

In order to improve the judgment accuracy of fire detection, this study proposed an intelligent fire judgment model based on multivariate data fusion for the first time, integrating wind speed, temperature and fire scale, breaking through the traditional single parameter limitation. Firstly, the determination principle and response threshold of smoke sensing and temperature sensing flame detector are analyzed, and the application characteristics and limitations of various detectors are clarified. Subsequently, fire entity tests of wood stacks with various ignition methods and different ignition positions were carried out in a space with a net height of 3 m. The results show that the response time of the detector is positively correlated with the distance of the fire source, that is, the farther the distance, the longer the response time, and the ignition mode has little influence on the response time. The smoke detector can accurately determine the fire when the critical wind speed is 0.15 m/s, and the temperature detector can trigger the alarm when the ambient temperature reaches 67 ℃. Finally, a mathematical model of fire judgment is constructed based on AHP, and the test results are brought into the formula to obtain the comprehensive fire judgment threshold of the test scene， which is Y=0.781. When the actual value exceeds this threshold, it is judged as a fire. The formula combines the parameters of wind speed, temperature and fire size, and verifies that the error range is less than 15%. This study provides the test basis for the accuracy evaluation of the fire detector and has important significance for the comprehensive evaluation of the detector performance.

The propagation of forest fires is primarily characterized by surface fires. A substantial body of research has been devoted to investigating surface fires, with particular attention paid to the interactive effects of low slope angles and wind on their propagation characteristics. In contrast, studies on the coupled effects of fuel load and slope on surface fire spread characteristics remain relatively limited. In this study, a slope‑adjustable experimental setup was used to conduct comparative experiments on surface fire spread under varying slope angles (0°, 20°, 30°, 40°), fuel loads (0.8, 1.0, 1.2 kg/m²), and fuel types (Pinus koraiensis and Quercus mongolica). Quantitative analyses were performed on the evolution of fire front shape, flame geometry parameters, rate of fire spread, and flame plume temperature. The results revealed that the time required for the fireline pinch‑shaped front to transition from its initial state to a steady state during surface fire spread on a variable slope exhibited a negative correlation with slope angle. When the slope angle was below 30°, its influence on the flame inclination angle was relatively weak; however, when the slope angle exceeded 30°, this influence became even less pronounced. Additionally, fuel type notably affected both the spread rate and flame length. Under identical operating conditions, the flame length and spread rate of Pinus koraiensis were greater than those of Quercus mongolica. The spread rate increased significantly when the slope angle exceeded 30°. Furthermore, correlation analysis was used to evaluate the effects of slope angle and fuel load on the characteristic parameters of fire spread. The results showed that slope angle significantly influenced flame angle, flame length, spread rate, and combustion temperature, whereas fuel load mainly determined flame length, spread rate, and combustion temperature.

Against the global backdrop of frequent forest-grassland fires, the pneumatic fire extinguishers have emerged as essential equipment for grassroots firefighting in China due to their superior portability and terrain adaptability, although persistent bottlenecks such as the difficulty in controlling reignition, excessive vibration and noise, and limited endurance remain. In this paper, the pneumatic fire extinguishing mechanism, equipment evolution, and future development directions are systematically reviewed. It is demonstrated that the extinguishing process is achieved through three stages comprising the removal of combustible volatiles, heat supply interruption, and combustion reaction termination via high-speed airflow. Nevertheless, quantitative research is currently constrained by inconsistent parameter standards and the absence of universal models for complex scenarios, making it difficult to provide accurate support for equipment optimization. In China, pneumatic fire extinguishers have progressed through phases of functional realization, integrated expansion, and performance optimization, achieving significant advancements in structural design, the synergistic application of fire extinguishing agents, and noise reduction, though system integration and technology development remain insufficient. It is proposed that future technological breakthroughs should prioritize battery power upgrades and synergistic innovation with aerogel fire extinguishing agents, while simultaneously bridging the gaps between quantitative theory and engineering application. This study is intended to provide a theoretical and practical reference for technological innovation and engineering application of pneumatic fire extinguishers, ultimately enhancing the efficiency of forest and grassland fire suppression.

Forest fires are major natural disasters worldwide, posing severe threats to the ecological environments, human lives and property. To address forest fires more effectively, this study introduces the concept of digital twins and employs the fire dynamic simulation software PyroSim, coupling five factors: ignition points, slope, wind speed, relative humidity and ambient temperature. A microscopic forest fire scenario in Pinus yunnanensis forests is constructed for refined simulations, aiming to investigate the influence of these factors on forest fire spread and to analyze the dynamics fire development process. A sliced dynamic simulation method is proposed to mitigate the lag issues in simulations under fixed environmental parameters and initial fire source conditions. The research results indicate that the digital twin-driven sliced dynamic simulation can reflect the actual behavioral characteristics of forest fires in a more realistic and efficient manner, thereby providing an important references for the study of forest fire suppression strategies.

With the increasing complexity of building structures, firefighters face greater wayfinding challenges during internal rescue missions. This study aimed to explore the effects of psychological factors, including sense of direction, spatial anxiety, spatial navigation strategies, and mental rotation ability, on firefighters’ wayfinding performance, providing a theoretical basis for optimizing firefighter selection and training. Fifty-eight male frontline firefighters from Shanghai and Jiangsu were selected as participants. Psychological characteristics were measured using Santa Barbara Sense of Direction Scale (SBSOD), Spatial Anxiety Scale (SAS), Wayfinding Strategy Scale (WSS), and Mental Rotation Test (MRT). Wayfinding performance was assessed through a self-developed virtual maze task. Data were analyzed using independent t-tests, ANOVA, and linear regression models. Results show that, sense of direction significantly influenced wayfinding performance, with the high-directional group completing tasks faster; Among spatial navigation strategies, the survey-strategy group performed best, while the route-strategy group performed worst; Spatial anxiety had no significant effect on performance; Mental rotation ability showed a significant positive impact. Sense of direction, survey strategy, and mental rotation ability are critical psychological factors for enhancing firefighters' wayfinding efficiency in complex environments, while the impact of spatial anxiety is context-dependent. It is recommended to incorporate spatial cognition assessments in firefighter selection and strengthen survey-strategy training through targeted programs.

To analyze the potential factors influencing the psychological and physiological states of firefighters during smoke and heat training, this study employed an intelligent smoke and heat training device for firefighters and utilized a feature data correlation analysis model. By collecting 16 indicators (including heart rate, electroencephalogram, and heart rate variability) from 100 firefighters during smoke and heat training, the research explored the factors affecting their psychological and physiological states in such training. The results showed that both age and firefighters' daily psychological states had a p-value less than 0.01 with their psychological states during smoke and heat training, indicating that younger firefighters were more prone to psychological problems during training, and regulating their daily psychological states could alleviate psychological pressure during smoke and heat training. The p-value for years of service versus training duration was 0.054, with a regression coefficient of -19.494, indicating that firefighters with longer service experience exhibited shorter training durations. The p-value for resting heart rate and training oxygen consumption was merely 0.016, with a regression coefficient of -0.128, indicating that firefighters with lower resting heart rates exhibited reduced oxygen consumption. The p-value for body weight and training duration exceeded 0.5, suggesting a relatively insignificant correlation between the two variables.

To address the challenge of emergency supplies demand forecasting in the early stages of typhoon disasters, where data are often incomplete and traditional methods are highly dependent on prior assumptions, this paper innovatively optimizes a case-based reasoning forecasting model. First, the entropy weight method and principal component analysis are integrated to determine the weights of disaster characteristic attributes, and case similarity is calculated through weighted distance metrics. Second, a random forest regression model is introduced, which incorporates demographic and socioeconomic indicators, to construct an event-outcome-based case revision mechanism. Furthermore, a multi-case weighted comprehensive reasoning approach is adopted to predict disaster consequences, and the total demand is estimated by integrating established material supply standards. The results demonstrate that the proposed method can effectively forecast emergency material needs under data-scarce conditions. It is operationally straightforward and highly adaptable, providing reliable support for emergency decision-making and material allocation during the initial disaster response phase.

Based on the functional positioning of fire rescue agencies, this paper focuses on the dimension of administrative law enforcement in response to the requirement of "deepening fire control law enforcement reform". Using relevant data from the fire control law enforcement business environment assessment index system established in the 2020 Fire control law enforcement business environment assessment report as the analytical source, combined with information collected from regional research interviews, this paper identifies existing issues that hinder the optimization of the business environment, such as weak intelligence in fire control approvals, weak standardization in case handling, weak scientificity in fire investigations, and weak standardization in supervision and inspection. Through an analysis of the characteristics of various fire control operations and in conjunction with the practical aspects of fire control law enforcement, the paper proposes measures to promote the digital transformation of administrative licensing, establish standardized procedures for case handling, strengthen the full-process standardization of fire investigations, innovate technological empowerment for supervision and inspection, and align the innovation of legal concepts with the transformation of the digital and intelligent era, thereby contributing fire control efforts to optimizing the business environment.

To explore the intrinsic relationships among the contributing factors of gas leakage accidents and identify the key and root causes, this study collected 148 gas leakage accident investigation reports as textual data. The Latent Dirichlet Allocation (LDA) model was applied for topic mining, and 18 accident causative factors were identified and summarized through literature analysis. An integrated approach combining the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) was adopted to plot cause-and-result diagrams of the factors and construct a multi-level hierarchical structure model. This allowed for determining the causal attributes of each factor and their roles within the system, as well as clarifying the hierarchical relationships and transmission paths among the factors. The results show that the causal factors of gas leakage accidents exhibit a five-level hierarchical structure. Among them, inadequate safety supervision and insufficient implementation of safety education and training are identified as root causes, while violations of operating procedures and failures of auxiliary equipment and facilities are the most direct surface-level causes. A total of 11 key causal chains from root causes to surface-level factors were identified, revealing the multi-level transmission paths among the causes of gas leakage accidents and providing clear directions for accident prevention and control.