By sorting out and analyzing the development process of China's fire science and technology, this paper points out the bottlenecks and shortcomings faced by the innovation and development of China's fire protection science and technology. In response to China's fire safety situation and the actual needs of fire rescue, and combined with the innovation and development mode of multidisciplinary integration, it puts forward the paradigm of cross-integration and innovation development of China's fire protection science and technology in the new era, as well as the development path and strategy of digital transformation, so as to point out the development direction and path for the innovation and development of China's fire protection science and technology.

Advanced fire detection and early-warning technologies are critical for source-level risk control and timely intervention. This article systematically reviews the developmental stages and macroscopic characteristics of fires, and identifies three key factors governing the response time of detection systems: the onset time of characteristic hazardous signals, their propagation time to the detector, and the intrinsic response time of the device. The fundamental principles and inherent limitations of conventional detection and alarm technologies are summarized. Building on an in-depth understanding of the combustion mechanism of combustibles, especially the initial pyrolysis and combustion stages, design methodologies for devices and systems capable of detecting latent-stage fires are further introduced. These approaches rely on the precise recognition of trace-level hazardous signals specific to the combustion context, too. Finally, we outline future trends in fire warning technologies, which are expected to evolve towards greater specialization, sensitivity, and accuracy.

With the intensive development of urban construction, the widespread application of new building materials and composites, and the rapid expansion of new energy facilities, modern building fire behavior exhibits high intensity, complex coupling, and nonlinear characteristics. Traditional small- and medium-scale experiments are increasingly insufficient to fully reveal the dynamics and risk features of fires. Full-scale fire experimental facilities have become an essential foundation for fire science research. This paper systematically reviews the current status of full-scale fire research infrastructure worldwide, including large-space fire testing halls, high-rise building fire test facilities, large fire-resistance furnaces, tunnel and transportation vehicle fire testing facilities, as well as energy storage stations and photovoltaic fire testing platforms. By summarizing the scales, functions, and representative experimental capabilities of these facilities, the study highlights the essential role of full-scale experiments in fire dynamics research, smoke movement simulation, occupant evacuation assessment, fire prevention and control technology validation, and major fire investigation. Furthermore, future development directions are discussed, emphasizing intensive construction, shared instrumentation, intelligent technologies, and standardization.

Quantitative research on the combustion and gas generation characteristics of lithium-iron batteries in an open space environment plays a crucial supporting role in fire safety assessment and prevention and control technologies. Based on the experimental platform for new energy fire calorimetry and thermal runaway gas analysis, the paper conducts a study on the combustion, smoke generation, and gas generation characteristics of 280 Ah lithium-iron phosphate batteries. The results indicate that under the condition where a 280 Ah lithium-iron phosphate battery is triggered by heating and then burns, the maximum heat release rate reaches 133.0 kW, the total heat release amounts to 14.26 MJ, the total smoke production is 52.5 m², and the heat-production equivalent is 0.38 kg of n-heptane. When a 280 Ah lithium-iron phosphate battery is triggered by heating and only generates gas without burning, a total of 15 types of gases, including esters, CO₂, and CH₄, are identified using a Fourier transform instrument. The total volume of these gases is 294.17 L, among which the volume of esters is 164.68 L and the total volume of hydrocarbons is 27.73 L.

This research constructed small scaled fire-suppression experimental platforms emulating three archetypal fire scenarios-structural (building) fires, electric bicycle fires, and diesel fuel fires-to comprehensively characterize aqueous-phase properties, acute toxicity, and genotoxic potential of firefighting runoff under divergent extinguishment strategies. The objectives were to provide data support for exploring the disposal methods of firefighting runoff and the formulation/revision of relevant standards. The results revealed that fire-extinguishing runoff universally exhibited weakly acidic to circumneutral (pH value 6.4~7.4), concomitant with elevated organic burdens. Notably, total organic carbon (TOC) concentrations in structural fire runoff peaked at 3 722.5 mg/L. Toxicological quantification demonstrated that 4-nitroquinoline-N-oxide (4-NQO) equivalency concentrations in runoff (12.5~75.7 μg/L) exceeded groundwater and surface water baselines (1~520 ng/L) by orders of magnitude. Runoff derived from Class A foam deployment during structural fire suppression elicited 63.5% luminescent bacteria (Vibrio fischeri) inhibition at merely 0.1% dilution. Moreover, both acute toxicity and genotoxicity of the firefighting runoff increased with extinguishing duration, indicating that continuous scouring of combustibles enhanced the ecological toxicity of the runoff. Class A foam extinguishing agents primarily contributed to acute toxicity, while aqueous film-forming foams (AFFF) predominantly mediated genotoxic effects. These results suggest that during large-scale fires, while ensuring firefighting and rescue effectiveness, efforts should be made to minimize the application time of foam concentrates and enhance the collection and treatment of firefighting wastewater to mitigate the potential ecological toxicity risks posed by firefighting runoff.

The floating roof, as a critical safety component of internal floating-roof storage tanks, is essential for the overall fire safety of the tanks. Its fire resistance serves as a key performance indicator affecting fire safety. However, frequent accidents involving in-service aluminum pontoon-type floating roofs have been reported, while numerous new floating roof designs have emerged. This study employs a full-assembly fire resistance test method to evaluate 21 floating roof products across 8 different types. The influence of material and structural design on fire resistance is analyzed. Results indicate that the fire resistance of aluminum pontoon-type floating roofs fails to meet practical requirements. For the new full-liquid-contact floating roofs, the sealing effectiveness between buoyancy units and between buoyancy units and perimeter vertical plates significantly impacts fire resistance. Finally, recommendations for floating roof selection in engineering applications are provided.

To explore the accident risk of leakage in multiple areas for a comprehensive energy station, an analysis model of multiple leakage scenarios for a comprehensive energy station was constructed using FLACS software. First, the leakage scenarios where leakage might occur in the comprehensive energy station were identified, and the specific condition parameters of the possible leakage scenarios were determined in combination with accident cases and the layout of the comprehensive energy station. Then, the leakage consequence analysis was carried out for different leakage scenarios. The results showed that the volume and diffusion distance of the gas leakage in the hydrogen production area and the hydrogenation area were mainly affected by the leakage pressure. The leaked dangerous gas cloud in the hydrogen production area was prone to spreading to the LNG area. Once an ignition source explodes, it was easy to cause a domino effect, threatening the safety of the LNG area. When the LNG leakage aperture reached 50 mm, the leaked LNG was easy to form a liquid pool on the ground, and the combustible gas cloud would migrate to the hydrogen production area under the influence of the wind field. Once an explosion occurred, it would affect the safety of the equipment operation in the hydrogen production area. Some suggestions were provided to mitigate the consequences of leakage accidents in multiple areas for different leakage scenarios.

Flexible copper indium gallium selenide (CIGS) photovoltaic (PV) cells are gradually expanding their applications due to their advantages of flexibility and easy installation. However, they are encapsulated with thermoplastic materials, which have lower thermal stability, faster fire spreading speed and higher fire risk. In this paper, the combustion spread characteristics of flexible PV cells under different tilt angles (-30°~+30°) and ignition positions (top and bottom) are studied, and the changing rules of combustion parameters such as flame morphology, flame angle, fire spreading speed, cell surface temperature, and radiant heat flux are analysed. It is found that: with the increase of the tilt angle of the panel from -30° to +30°, the flame angle and pyrolysis time show the trend of increasing and then decreasing, while the flame length, heat flux, and fire spreading speed show the opposite trend; when the tilt angle is from +10° to +20°, there is a significant surge in the flame length and spread speed, the pyrolysis time is shortened by 40%, and heat flux is increased by 65%. Based on the differences in flame front morphology under different tilt angles and ignition positions, three different radiative heat transfer models are established, and the theoretical and experimental values of radiative heat flux are within 20% of each other, which has good applicability.

To explore the thermal runaway behavior and combustion characteristics of sodium-ion battery, the thermal runaway characteristics of sodium-ion battery under different trigger conditions were studied based on the heat release rate test system, and the combustion characteristics (heat release rate, total heat release, smoke production rate, total smoke production) were compared with lithium-iron phosphate battery and lithium ternary battery. The results show that under 0.5C overcharge conditions, the surface temperature of sodium-ion battery can reach up to 834.9 °C, with a maximum heat release rate of 156.99 kW and a maximum smoke production rate of 1.65 m2/s. Under the heating condition of 7 ℃/min temperature rise rate, the maximum surface temperature of sodium-ion battery can reach 594.7 ℃, the maximum heat release rate is 227.41 kW, and the maximum smoke production rate is 1.54 m2/s. The combustion performance of sodium-ion battery was compared with that of lithium-ion battery. The results show that the combustion characteristics of sodium-ion battery are between those of ternary lithium battery and lithium-iron phosphate battery. Ternary lithium battery has the highest heat release rate and smoke production rate, while lithium-iron phosphate battery has the highest total heat release.

An experimental platform integrating constant-temperature environment simulation, charge-discharge control, and multi-parameter monitoring (temperature, voltage, gas concentration) was established. Normal charge-discharge and overcharge comparison tests were conducted under three environmental temperatures. The study found that during normal charge-discharge, the temperature change of the battery is dominated by the environmental temperature, with a slow temperature rise at low temperatures, a continuous temperature increase at high temperatures, and a stable temperature at room temperature. Under the overcharge condition, however, significant dangerous characteristics were observed: the battery temperature exceeded 100 °C in all three environmental temperatures, accompanied by the intense release of flammable gases such as hydrogen, VOCs, sulfur dioxide, and hydrogen sulfide, posing an explosion risk in a confined space, with the fastest temperature rise rate at 40 °C. Based on these findings, this paper proposes an intelligent thermal runaway early warning system: relying on the BMS master-slave architecture, it collects battery terminal voltage, multi-point temperatures, and hydrogen/VOCs gas concentrations in real time. The core early warning parameters include temperature thresholds, upper limits of temperature rise rate, and hydrogen concentration thresholds, and it integrates SOC/SOH algorithms to track the battery's health status. This system can respond to abnormal temperature rise and gas leakage within milliseconds, triggering protection mechanisms to prevent thermal runaway accidents.

China's building fire protection code system has undergone over seventy years of development, evolving from initial reference and exploration in the early days of the nation's founding to system refinement during the reform and opening-up period, and further to the establishment of a technical regulation framework in the new era. This has resulted in a new regulatory system that integrates technical regulations with supporting technical standards. Currently, building fire protection regulations face challenges such as digital transformation and the renovation of existing buildings, necessitating continuous innovation to provide fire safety technical support for the people's aspirations toward a better life. At the same time, it is essential to expand international cooperation and offer Chinese fire protection code expertise to ensure construction fire safety for projects under the Belt and Road Initiative.

In view of the problem that mobile fire smoke exhaust fans generally adopt the positive pressure air supply and smoke exhaust mode, and the existing in-duct air volume testing methods cannot objectively reflect their ductless air supply characteristics, this paper focuses on the air supply characteristics and influencing factors of new high-efficiency and large-air-volume mobile fire smoke exhaust fans, and establishes an air volume testing method suitable for ductless conditions. Based on 4 new high-efficiency and large-air-volume mobile fire smoke exhaust fans, the paper designs 5 typical working conditions and completes the actual measurement of wind speed and air volume. The test results show that the wind speed attenuates outward from the axis in a volcano-like distribution, while the air volume reaches the maximum at a specific annular radius, and the distribution laws of the two are inconsistent. In terms of the influencing factors of air supply characteristics, the fan power has the most significant impact on air volume output, followed by the impeller diameter, while the number of blades and test distance have relatively smaller impacts.

To address the aging issues of intumescent fire-resistant coatings, which are the most widely used for steel structure fire protection, a simple natural weathering test site was established. A total of eight coatings，comprising water-based and solvent-based types from two representative domestic and two international brands，underwent a natural aging test lasting up to four years. The aging behavior of the conting was systematically characterized through visual monitoring, fire resistance testing, element analysis infrared spectroscopy, etc. Results demonstrate that outdoor exposure significantly accelerates coating degradation compared to indoor conditions, particularly for water-based systems, while top coating effectively delays defect formation. Coatings like DSP, BRP, CRP, and DRP maintained structural integrity (0% defect rate), with lower fire resistance rating decay rates of 5.08%～28.79% and controlled bond strength decay after aging. In contrast, ASP, BSP, CSP, and ARP exhibited premature failure (cracking/spalling) due to leakage of expandable components through surface defects. Critically, the degradation of appearance, fire resistance, and bond strength displayed high synchronicity, correlating strongly with changes in content of key elemental and component. Overall, solvent-based coatings outperformed water-based alternatives.

As the most widely used fire suppression system among fixed fire protection equipment, automatic sprinkler systems face numerous challenges during long-term service due to factors such as geographical and climatic differences, operation and maintenance management, resulting in diverse and unpredictable failure modes. This paper reviews the current state of research on the reliability of automatic sprinkler systems both domestically and internationally, introduces reliability evaluation methods, accelerated testing techniques, and residual life prediction calculation methods, and outlines the development of reliability standard systems worldwide. It points out that while China's reliability standardization system is rapidly advancing, there are still no relevant reliability standards issued for fire protection facilities and equipment. Therefore, based on existing research, this paper proposes recommendations for establishing a reliability standard system for automatic sprinkler systems.

The concurrent expansion of China's forest coverage and increasing frequency of extreme weather events have substantially elevated forest fire risks, rendering scientifically efficient wildfire suppression a critical challenge. Despite comprehensive technological advancements in forest firefighting-encompassing prediction systems, personal protective equipment, fire suppressants, ground-based apparatus, and aerial capabilities-following China's fire service structural reforms, persistent deficiencies remain in intelligent firefighting technologies for combating major and catastrophic wildfires. Analysis of global forest firefighting technologies and emerging trends indicates that China should prioritize developing: intelligent wildfire behavior prediction, precise identification of extreme fire behavior, lightweight ergonomic firefighter gear, environmentally efficient forest fire suppressants, intelligent and reliable fire engines, unmanned rapid firebreak construction systems, and specialized firefighting aircraft with modular payloads. These initiatives must focus on practical firefighting scenarios and operational requirements to ultimately enhance China's integrated forest fire management capabilities.

Airport terminals, sports stadiums, and other large-span spatial venues pose significant challenges for conventional fire detection technologies in meeting early warning requirements due to their unique architectural structures and internal spatial layouts. Existing image-based fire detectors currently have a maximum detection range of 100 meters, while the horizontal spans of many large-span buildings exceed 200 meters, demanding higher detection distances and sensitivity from such detectors. In the early detection of fires in long-distance and large-scale spaces, it is necessary to improve the ability of detection algorithms to accurately identify small target fires. To address this issue, this study proposes an improved YOLOv8-based algorithm specifically optimized for small-target flame detection. This study proposes an improved YOLOv8-based flame image detection algorithm. For enhancing model accuracy, a CA-Res module integrating coordinate attention and dynamic residual adjustment is incorporated. To control model complexity, the BottleneckCSP module in the original model has been optimized. For improving multi-scale detection capability, an additional small-target fire detection layer is added to the Head section of the model's output terminal. Comparative tests demonstrate that the three-dimensional improvements to YOLOv8 significantly enhance flame detection accuracy while maintaining satisfactory detection precision and real-time performance for small-target flame images. This technical solution effectively addresses the challenges of long-distance and wide-range fire detection in image-based fire monitoring systems, providing a viable approach for early fire warning in large-span spaces such as airport terminals and stadiums.

In order to solve the problem of insufficient sample library of fire images in large-span spatial places, which leads to low accuracy of fire detection, a method of enhancing synthesized samples of large-span spatial fire is proposed. This method is based on an improved CycleGAN network, which constructs a flame block generation network and a fire image generation network. The flame block generation network generates flame block images, and the fire image generation network integrates flame blocks into designated areas of the engineering scene to generate fire samples that can be used for object detection models. The results show that the synthesized samples generated by the model improved the performance of the object detection model significantly, with a increase of 25.11% in mAP@0.5, verifying the effectiveness of the data augmentation method. Therefore, by generating high-quality and diverse large-span fire images, the problem of insufficient fire sample libraries has been effectively alleviated, providing strong support for the development of artificial intelligence based image fire detection algorithms for specific scenarios.

As a category of fire safety products, foam fire extinguishing agent have raised global concern due to the environmental pollution and ecotoxicity effects resulting from their widespread and extensive use. Consequently, substantial researches have been conducted by domestic and international researchers on the environmental properties of these agents. This paper provides a comprehensive review of the evaluation indicators and methodologies for assessing the environmental properties of foam fire extinguishing agents worldwide. It analyzes the environmental performance characteristics of major types of foam fire extinguishing agents used domestically and internationally, and compares the differences in relevant standards and certification systems concerning environmental properties across various regions. Considering the current status of production and application within China, future recommendations are proposed. This review aims to provide references for advancing research on environmental performance evaluation of foam fire extinguishing agents in China, refining relevant standards, and mitigating the environmental risks associated with their use.

Foam rheological properties are important for engineering design and hydraulic calculation of foam fire extinguishing system. The dynamic viscosity and shear stress of compressed air foam under different working conditions were measured by a rotary rheometer, and the rheological properties and rheological model of a new type of high stability compressed air foam are analyzed. The results show that the rheological constitutive equation of the new high stability compressed air foam based on polysaccharide polymer conforms to the Herschel-Bulkley model within 5 minutes and belongs to the yield pseudo-plastic fluid, and the foam dynamic viscosity decreases with the increase of shear rate. The shear stress and dynamic viscosity of the new high stability compressed air foam gradually increase with the increase of polysaccharide polymer premix mixing ratio, gas-liquid ratio and foaming time. The rheological properties of the compressed air foam decreases with the increase of polysaccharide polymer premix mixing ratio. When the mixing ratio of polysaccharide polymer premix is increased from 37.5% to 50.0%, the shear stress is almost unchanged. The rheological properties of the high stability compressed air foam decreases gradually with the increase of gas-liquid ratio and foaming time.

This study addresses the issues of insufficient high-temperature resistance and thermal protection in traditional aramid-based firefighting protective clothing. It investigates the design and preparation process of aramid/polyimide blended fabrics and their application performance in protective clothing for firefighting. Through the design of fabric composition and structure, a series of high-temperature resistant fabrics are prepared. The key protective properties, including mechanical properties, residual tensile strength, fire resistance, flame retardancy, thermal protective performance, are systematically evaluated, and protective clothing for firefighting with high-temperature resistance is also prototyped. The results show that the prepared high-temperature resistant fabrics retain a residual tensile strength of over 650 N after being subjected to heat treatment at 400 °C for 30 min. The time to break under butane flame exposure exceeds 43 s. The high-temperature resistance and fire resistance of the fabrics are significantly superior to those of aramid fabrics and even better than the two tested PBI fabrics. The prototyped high-temperature resistant protective clothing for firefighting combines light weight with high thermal protection, significantly enhancing the safety and comfort of firefighters during firefighting operations and providing technical support for the development of high-performance firefighting protective equipment.

In order to better cope with the impact of large language models on the intelligent and digital transformation of the fire rescue industry, this paper first reviews the development history of large language models, and then analyzes their development logic from general ability construction to industry adaptation. Secondly, focusing on fire rescue scenarios, the system elaborates on the relevant technical implementation and practical application status of large language models in the field of fire rescue. Based on this, it deeply analyzes the core challenges faced by large language models in industry applications, such as data availability and industry adaptability. Finally, the research directions and application prospects of future large language models in the field of fire rescue were discussed.

Faced with challenges such as weak fire supervision forces, outdated traditional supervision models, difficulties in multi-source data fusion, and insufficient regulatory efficiency, the Tianjin Fire and Rescue Brigade actively responded to the requirements of the national development of new quality productivity and big data strategy, with the goal of creating new quality combat effectiveness, and developed a fire risk monitoring and early warning system to lead and guide the comprehensive supervision of fire safety in the city. This article systematically elaborates on the establishment of a fine-grained fire risk warning model, a large model in the field of fire protection, and a fire risk traceability model by the Tianjin Fire and Rescue Brigade, relying on the technical strength of the National Supercomputing Center and other technologies, with big data as the foundation and AI intelligent computing as the support. It also integrates multidimensional real-time monitoring data to achieve precise push and penetration of warning information to local, industry, and professional regulatory entities, significantly improving the accuracy of risk identification, the efficiency of regulatory resource allocation, and the closed-loop rate of fire hazard rectification. This provides strong support for building a scientific and efficient comprehensive fire safety supervision system and promoting the transformation of governance to "pre-vention" mode.

Accurate identification of the ignition cause in electrical fires is crucial for promptly resolving disputes, effectively preventing recurrence, and minimizing losses. Achieving this objective relies on evidence collection and identification techniques. Addressing the practical needs of electrical fire investigation, this paper reviews research advances in electrical fire evidence collection and identification techniques in China, including evidence localization techniques based on BMS, cloud, and smart meter data analysis; key breakthroughs in intelligent molten mark recognition; recrystallization mechanisms of short-circuit molten marks; destructive testing methods for aluminum/brass evidence and Micro-CT/X-ray non-destructive testing technologies. Future developments trends in evidence classification systems, integrated analysis technologies, and ignition propensity characterization are also presented.

This paper proposes a method for forest fire spread direction analysis and ignition point backtracking to address forest fire investigation needs. The approach constructs a fire scene model through UAV mapping, utilizes a ResNet-18 convolutional neural network to identify fire spread directions from trace images, and generates a continuous direction field using inverse distance weighted interpolation. Runge-Kutta method is employed for backward streamline integration, with DBSCAN clustering ultimately determining the ignition point location. Simulation results demonstrate the method's effectiveness in analyzing spread patterns and tracing ignition points, overcoming limitations of traditional manual surveys such as low efficiency and subjectivity. By transforming expert knowledge into reusable intelligent algorithms, the approach reduces subjective dependence and achieves intelligent ignition point tracing, providing efficient, objective technical support for forest fire investigations.