In order to further enhance the fire safety level of communities in China, a total of 366 community fire-related papers indexed in the CNKI database (1996-2024) were analyzed using Citespace software to generate keyword co-occurrence, timeline maps, and institutional knowledge networks. Publication volume, journal distribution, institutions, topics, and hotspots were systematically examined. The results show that core research forces are concentrated in local fire agencies and affiliated universities, with untapped potential for collaboration. The domain exhibited multidimensional trends, including social-physical space analyses, shifts from single-subject to multi-party governance, and alignment with the "big security and big emergency" framework. Four evolutionary stages were identified: germination (1996-2000), system construction (2001-2011), expansion (2012-2017), and connotation improvement (2018-2024). Current priorities emphasize emergency-firefighting integration, theory-practice synergy, and technology-driven smart fire communities, which are recognized as critical future research directions.

To improve the stability and safety of highway networks in plateau mountainous areas, an evaluation index system for critical nodes was established by selecting five indicators: degree centrality, betweenness centrality, closeness centrality, travel time weight, and adjacent node travel time degree. A critical node identification method integrating topological structure and traffic functionality was proposed. Taking the highway network in western Sichuan Plateau mountainous region as a case study, the differential performance of three improved algorithms was investigated. This algorithms included modified LeaderRank, PageRank, and degree centrality. Their performance was examined in identifying critical nodes within an undirected weighted network framework. Additionally, the variations in network efficiency and connectivity rate under node failure scenarios were systematically examined. The results demonstrate that the three algorithms exhibit distinct prioritization in assessing node criticality. Node failure sequences ranked by the modified LeaderRank algorithm induce the most rapid and significant decline in both network efficiency and connectivity rate.

In order to enhance the capacity of urban flood prevention and disaster reduction, taking Zhenba County as an example, this paper explores the coupled disaster formation process and risk assessment methods of flood disasters. By analyzing the rainfall data and flood disaster statistics in recent years, the frequent occurrence and severity of flood disasters in this area as well as the huge losses they have caused to the economy and society were revealed. High-precision terrain data was obtained through unmanned aerial vehicle technology and combined with the SWAT for flood simulation, providing accurate disaster data support. A multi-factor risk assessment matrix was constructed, and the comprehensive flood risk index was obtained through normalization processing. The risk assessment results show that 14 areas with grade IV risks are identified, and the simulation results of the model are highly consistent with the actual situation. The research results indicate that the constructed coupled disaster formation simulation and risk assessment method can accurately identify high-risk areas. Effective countermeasures are proposed for high-risk areas, including improving flood control capacity, strengthening monitoring and early warning, conducting disaster prevention and education, and strengthening land planning and management.

To analyze the synergistic relationship among urban emergency organizations during institutional reforms, 24 natural disaster-specific emergency plans from Xi'an city were used as the data sample. Social network analysis was employed to examine the coordination and collaboration between departments involved in emergency response, mitigation, and rescue during natural disasters. From a temporal perspective, the dynamic changes in the network structure were explored, and the characteristics of indicators such as density, centralization, and average distance were assessed. Using a "coherence and constraint" two-dimensional framework, institutional roles were classified and analyzed from three dimensions: institutional characteristics, functional positioning, and organizational structure. The CONCOR(Convergence of Iterated Correlation) algorithm and E-I index method were applied to depict the internal logic of network governance structures and the evolution of organizational relationships. The results show that the concentration of the emergency organization collaborative network increased from 0.577 6 to 0.723 5 after the institutional reform, indicating that the network structure shifts from a decentralized network with loose collaboration among multiple entities to a tightly-knit network centered around the Xi'an Bureau of Emergency Management. The highest core degree of institutions increases from 0.342 to 0.369, while the lowest constraint degree decreases from 0.166 to 0.087, reflecting a trend toward the unification of command responsibilities. The network organization follows a core-periphery governance structure, with the boundaries between core and peripheral organizations becoming increasingly clear and reinforced.

In order to improve the emergency response capacity of urban flooding disasters, an emergency response capacity assessment model based on the combination of improved DS evidence theory and FBN was proposed. Firstly, from the whole process of disaster emergency management, the urban flood disaster emergency response capacity assessment index system was established and mapped into a Bayesian network (BN) model. Then, to address the problems of information uncertainty and strong subjectivity in the assessment process, the improved DS theory was introduced to determine the index weights. The expert knowledge combined with the fuzzy set was used to quantify the prior probability of the root node. The accident tree was applied to analyze the key indexes, and the Sorting center of mass method was used to assign basic event probabilities. The probability of flooding disaster risk was calculated through the BN model. Emergency response capacity assessment and reasoning analysis were carried out on the basis of the above results. Finally, take the main urban area of Zhengzhou city as an example, GeNIe4.0 software was used to generate the BN model of emergency response capacity assessment of flooding disaster, and the emergency response capacity level and sensitive indexes of flooding disaster in the city were obtained. The results show that the emergency response capacity of the main urban area of the city is good. The sensitive indicators affecting the emergency response capacity are timeliness of the emergency response, normality of the warning information release, professionalism of the emergency response and accuracy of flooding information feedback.

In order to effectively prevent construction safety accidents，a safety responsibility network model of the five responsible parties was developed based on complex network topology characteristics to reveal the nonlinear coupling mechanism of their safety responsibilities，supported by accident case studies. First，relevant regulations，standards，and literature were analyzed to extract safety responsibility checklists for each party，and a responsibility matrix was constructed. Subsequently，Neo4j software was utilized to visualize the network diagram illustrating the safety influence relationships among the five parties in construction projects. Finally，topological metrics were applied to explore the interdependencies between the parties across multiple dimensions. The results indicate that the construction client plays a central and dominant role in project safety，with particularly significant influence on the contractor. The contractor's impact is primarily concentrated within its organizational boundaries，and its responsibility implementation is susceptible to external influences from other parties. The survey and design units indirectly affect other parties through the construction client. The supervision unit maintains systemic balance and regulation through monitoring and feedback mechanisms. The identification of critical decision-making nodes and passive response factors provides network topology-based evidence for differentiated management of responsible parties.

To address the issue of natural coal ignition in goaf under normal fault geological structures，the oxygen consumption rate and heat release intensity of coal samples were measured using a temperature-programmed oxidation device. Based on a porous media model of the goaf and the gas component transport equation，a numerical model for CO₂ injection via side pressure into the goaf influenced by normal faults was established. The numerical model was used to simulate the mechanism by which the variation in the distance between the working face and the fault affects the width of spontaneous combustion oxidation band in the goaf，and analyze gas migration characteristics under different CO₂ injection locations and flow rates. The results indicate that as the distance between the working face and the fault increases，the width of the oxidation band initially increases and then decreases，reaching a maximum width at 70 m from the fault. With the increase of CO₂ injection depth，the oxidation band width initially decreases and then increases again，reaching a minimum width when the CO₂ injection position is 40 m from the working face. Furthermore，with the increase of CO₂ injection volume，the width of the oxidation band width decreases following a negative exponential trend. When the CO₂ injection rate is 1000m³/h and CO₂ volume fraction at the working face is below 0.4% for safety，width of the oxidation band reaches its minimum.

In order to reduce the risks associated with the continuous growth of airport flight area size and flight volume，the safety resilience assessment of airport flight areas was carried out. First，risk factors were identified by analyzing the historical data of airport flight zones. Second，key risk factor weights were quantified，and a SD-based safety resilience assessment model for airport flight zones was constructed to propose safety resilience indicators. Then，the safety resilience of airport flight zones was assessed through simulation analysis，and targeted enhancement strategies were proposed. Finally，a large domestic airport flight area was taken as the research object to assess its safety resilience. The results show that among the personnel factors，the performance of the flight crew has the greatest impact on the level of operational safety resilience. By controlling the flow in the controlled airspace，enhancing safety awareness and increasing management inputs，the operational safety resilience of the flight area is improved by 9.11%. Among the environmental，equipment and management factors，the degree of improvement of the equipment updating mechanism has the greatest impact on the operational safety resilience level. By accelerating the frequency of equipment renewal，improving equipment deficiencies and increasing management inputs，the operational safety resilience of the flight area is increased by 21.49%.

To address the issues of complex environmental interference and low recognition rates in early-stage tunnel fire detection，an improved YOLOX-based detection method，YOLOX-T，was proposed. The proposed method incorporated a NAM into the YOLOX network to suppress environmental noise and interference，thereby enhancing the model's robustness. A weighted BiFPN was integrated to improve multi-scale feature extraction and fusion. Furthermore，an α-IoU(Intersection over Union) loss function was employed to enhance the detection accuracy of early-stage tunnel smoke and flames，which often exhibit indistinct contours. Addressing the scarcity of publicly available datasets，a tunnel fire dataset encompassing both real-world and simulated scenarios was constructed through web data acquisition，simulated fire experiments，and the augmentation of existing datasets. Experimental results on the self-built dataset demonstrate that，compared to the original YOLOX model，the YOLOX-T method achieves improvements of 1.89% in mean Average Precision (mAP@0.5)，0.88% in mAP@0.5~0.95，4.57% in precision，and 5.45% in recall. The improved algorithm can achieve better detection performance.

In order to effectively improve the comprehensive prevention and control ability of coal mine water disaster accidents，the complex network and robustness analysis method were used to explore the key causes of accidents. According to the report of 111 typical coal mine water disaster cases in China in the past 40 years，an unweighted directed network of coal mine water disaster was constructed. The weights of each cause，such as degree，clustering coefficient and betweenness centrality at different scales of the network were calculated，and the key causes were excavated. The damage of intentional attack to the cause network under three different strategies was evaluated，and the optimal solution of systematic prevention and control was sought. The results show that the coal mine water disaster cause network has the characteristics of small world，and the causes are closely related. The attack ranked by degree has the greatest damage to the model. The corresponding key causes include organizing workers to carry out risky operations，failing to implement the management responsibility of water prevention and control technology，failing to carry out water exploration and drainage work as required，illegal organization of production operations，imperfect safety management institutions，inadequate hidden danger investigation，loopholes in coal mine safety supervision and supervision，and failure of higher-level units to perform safety management responsibilities.