In order to optimize the community emergency supplies reserve, the concept of BCM was introduced to study the multi-objective optimization model of community emergency supplies reserve. Firstly, the key services and related emergency supplies after the disaster were identified, and the community emergency support capacity was quantified by constructing the post-disaster living standard change curve. Secondly, a multi-objective optimization model for material reserves with the maximum guarantee capacity and the minimum cost is proposed. Finally, the numerical examples were solved and the sensitivity analysis of the key parameters was carried out. The results indicate that as the minimum business continuity objective increases, the level of emergency material reserves increases, enhancing the community emergency support capacity. The reserves show a priority order, with lower-cost items being increased first. Under the same level of emergency material reserves, enhancing community emergency response and handling capabilities can improve the community emergency support capacity. Moreover, as the reserves of emergency materials in a community grow, the significance of these capacities in improving the emergency support capacity becomes increasingly pronounced. The emergency material reserve optimization model constructed from the perspective of business continuity can enable the community to provide basic living guarantees for residents after emergencies.

In order to investigate the impact differences of inter-layer and intra-layer passenger flow transfer proportions after stations failure on the invulnerability of the metro network, a multi-layer directed weighted metro network model was constructed, considering the train running time between stations, station dwell time, passenger transfer walking time, and waiting time. Station initial loads were determined by the actual passenger flow, and the station capacity was calculated using a nonlinear load-capacity model. Stations were sequentially targeted based on their relative importance. The maximum connected subgraph ratio and passenger travel efficiency ratio were selected as the metrics to measure the invulnerability of the metro network. An empirical analysis using the 2021 Xi'an metro network was conducted to study the effects of different inter-layer and intra-layer passenger flow transfer ratios and different capacity adjustment coefficients on the network's invulnerability. The results show that when the inter-layer passenger flow transfer ratio is 0.7, the impact on the invulnerability of the multi-layer metro network is minimal. When the capacity adjustment coefficients are set at b = 0.6 and c = 0.8, appropriately improving station service levels can enhance the network's invulnerability. As the number of attacked stations increases, the invulnerability of the metro network gradually decreases. Under the same attack conditions, the multi-layer directed weighted metro network demonstrates stronger invulnerability compared to the single-layer network, and the network's invulnerability is further reduced when cascading failures are considered.

To clarify the role of the emergency organization in breaking the disaster chain during the execution of emergency tasks and describe the evolution process of the collaborative network, taking the Shulan rainstorm in 2023 as an example, emergency task was regarded as the bridge connecting the disaster event and the emergency organization. The topological structure of the rainstorm disaster chain network and emergency organization network was analyzed. The effect of collaborative network was measured by taking the total amount of vulnerability reduction at the edges of the disaster network controlled by emergency organizations at each stage during the execution of tasks as the standard. The results indicate that disaster events caused by heavy rain exhibit high clustering effects, significant mutual influence, and short disaster paths. In the emergency organization network, most highly centralized organizations are government entities, which have strong capabilities to directly interact with other nodes. By contrast, organizations with low centrality, primarily enterprises and social organizations, tend to be more independent from other nodes. Each emergency organization can coordinate and control critical disaster events and disaster chains with greater vulnerability. In the stage of clearing and resettlement, the number of emergency tasks, disaster-response organizations, and broken chains is the highest, and the total amount of edge vulnerability reduction is also the greatest. By contrast, during the stages of emergency rescue, recovery and reconstruction, early warning and response phases, edge vulnerability reduction decreases sequentially.

To improve the emergency evacuation ability of miners, simulation models of roadway bifurcation angles (45, 60, 90, 135, 180°) were constructed for horizontal roadway and inclined roadway, respectively. Based on social force theory, the changing characteristics and main forces of roadway bifurcation angles with evacuation time were analyzed, and a relationship model between roadway bifurcation angles and evacuation parameters was established. The orthogonal test was used to investigate the influence of the length, width and position of obstacles on the evacuation efficiency of miners. The results showed that the evacuation process of roadway could be divided into queue passage stage, competitive balance stage and social force effect stage, and the evacuation time decreased with the increase of roadway bifurcation angle, which followed with the cubic polynomial relationship. The optimum bifurcation angle was determined to be 135°. The order of the influence of obstacles on evacuation efficiency is the width of the obstacle> the length of the obstacle > the position of the obstacle, and the width of the obstacle has an exponential relationship with the evacuation time. Taking the roadway bifurcation angle, slope and obstacle width as the static influence coefficients, the calculation shows that under the optimal bifurcation angle, the equivalent length of the roadway is significantly affected by the obstacle width when the obstacle width is greater than 2 m.

In order to solve the multi-period and multi-batch relief delivery problem under flood disaster scenarios, a routing model was constructed for collaborative relief delivery of trucks and assault boats by comprehensively considering factors such as the dynamic changes of disaster situations, and the collaborative transportation of trucks and assault boats. The objective of the model was to minimize the total distribution time within each period. A HHA, which combines the improved ant colony algorithm(IACA) with a genetic algorithm(GA), was designed for solving this problem. Compared with the ant colony algorithm and the simulated annealing algorithm, the experimental results show that the HHA provides truck-assault boat collaborative distribution routing solutions under the dynamically changing disaster situations in a relatively short time. The HHA effectively reduces the total distribution time and improves the efficiency of relief delivery. The rationality, feasibility, and effectiveness of the HHA were demonstrated. The number of flooded areas and the number of assault boats have a significant impact on the routing of relief delivery. Emergency logistics decision-making departments should weigh the disaster situation and resource allocation of each flooded area, and dispatch a reasonable number of assault boats to ensure the efficiency of relief delivery.

In order to enhance the safety and operational maintenance capabilities of tunnels, a quantitative evaluation framework and design methodology for FRP-PCM composite reinforcement in diseased tunnels was established through cross-sectional ultimate bearing capacity analysis. Numerical tests were conducted using the finite difference method to analyze the stability of FRP-PCM-reinforced diseased tunnels. Tunnel safety assessment was performed based on the sectional ultimate bearing capacity curve, commonly referred to as the M-N curve. A safety factor α of the M-N curve was proposed to enable a quantitative evaluation of the reinforcement effect. Based on this framework, a design and selection scheme for FRP was established, incorporating tunnel design specifications. The analysis reveals that when cavities exist at the crown of the tunnel, both the crown and shoulders exhibit higher risk levels according to the M-N curve. Furthermore, under conditions of poorer surrounding rock quality, greater lining concrete deterioration, and increased loosening pressure height, the reinforcing effect of the FRP-PCM method becomes more significant. For cases with an 80% degradation degree, Class V surrounding rock, and a loosened pressure height of 2D, the application of different types of FRP reinforcement reduces the safety factor of the M-N curve by 23%-32%, thereby significantly improving the structural safety of the lining. By leveraging the M-N curve's safety coefficient, an appropriate FRP type can be selected for defective lining reinforcement based on factors such as rock quality, loose pressure height, and lining conditions.

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.

To address the perception inaccuracies of autonomous mining trucks in open-pit mines under low-visibility and low-illumination conditions—issues that may lead to obstacle collisions. This paper was proposed a multimodal fusion-based obstacle detection method to enhance detection accuracy and operational safety in complex environments. Firstly, local Feature matching at light speed (LightGlue), was employed to achieve spatial alignment between thermal infrared and visible light images, thereby avoiding spatial misalignment and geometric distortion prior to fusion. Secondly, in the modality feature extraction and fusion stage, a Dual-Modality Feature Fusion (DMFF) module was incorporated into the improved dual-branch backbone network. The extraction capability of dual-modality features was enhanced and fusion was performed through feature compression and cross-modal feature enhancement. An iterative learning method was then introduced to effectively match the complementary information between modalities, generating a fused dual-modality feature map and improving multimodal detection performance. Finally, the fused feature maps at multiple scales were input into the detection head. They were combined with bounding box regression and classification prediction for precise detection. Experimental results demonstrate that the proposed method achieves excellent obstacle detection performance in challenging scenarios with low visibility. Specifically, it achieves a mean Average Precision (mAP@0.5) of 90.8%, and an F₁-score of 0.887, outperforming existing methods in both accuracy and speed. Moreover, the proposed approach exhibits lower false positive and miss detection rates, effectively ensuring the safe navigation of autonomous mining trucks in complex operational environments.

The nuclear power display control system is a typical cross-screen interaction scenario in which the manipulator must accurately and rapidly monitor and respond to multiple sources of fault alarms, and the attentional capture effect plays a critical role. This study designed variables from the two dimensions of cross-screen interaction and fault alerts. In a single trial, variables such as the number of cross-screens, cross-screen orientation, the number of alerts, alert level, and alert location were set in random combinations. Eye-tracking technology and behavioral experiments were conducted to capture operators' visual attention behavior under different interaction conditions. The research reveals that an increase in the number of cross-screen displays adversely affects the attention capture effect, causing operators to frequently shift their perspectives to locate target stimuli and reducing task efficiency. As the number of alerts increases, there is a declining trend in the number and duration of fixations, indicating that excessive alert signals may lead to information overload and hinder operators' in-depth processing of individual alerts. High-level alerts effectively capture attention and facilitate rapid responses. In the future, considering the distribution of users' attention and task efficiency in cross-screen behavior scenarios, by optimizing the layout of monitoring screens and the fault alert system, improving alert design, and reducing the need for perspective transfer, the safety and reliability of alert detection task operations can be enhanced.

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.