In order to more effectively and accurately judge the gas concentration field，temperature field，and flow field distribution in the goaf during the mining of extra thick coal seams，and thereby determine the self-ignition risk area for layered mining of extra thick coal seams，taking the 172307 working face of Lingquan mine as an example，numerical simulation technology was used to establish a mathematical model of coal spontaneous combustion in the goaf for layered mining of extra thick coal seams based on the coupling mechanism of multiple fields in the goaf. Combined with the distribution models of coal oxygen consumption rate，heat release intensity，critical oxygen concentration for spontaneous combustion，porosity and permeability，the evolution law of the spontaneous combustion risk zone for layered mining of extra thick coal seams in a stable state was obtained through the simultaneous solution. The results show that in the upper layered goaf，the high oxygen concentration area and the high-temperature area are mainly located near the stop mining line and in the upper part of the intake and return air tunnels，and the main air leakage area is located at the stop mining line. In the composite goaf，the high oxygen concentration area is mainly located on the inlet and return air sides. As it moves towards the deeper part of the goaf，the oxygen concentration shows a decreasing trend. And a local high-temperature zone resembling an ellipse appears at a certain distance from the coal mining face.

In order to solve the problem of insufficient research on the non-uniform mixed explosion characteristics of hydrogen leakage in the tunnel，the numerical simulation software Fluent was used to establish a tunnel model with the length，width and height of 60，6.46 and 5.5 m，respectively. The non-uniform mixed explosion characteristics of hydrogen at the ignition time of 75 and 100 s and at ignition positions above and behind the vehicle were studied. The results show that the hydrogen leakage volume fraction field is not uniformly distributed in the tunnel scenario. After the explosion，the pressure wave reflects from the tunnel wall and propagates to the exit at both ends of the tunnel. In the process，the intensity of the pressure wave decreases continuously. The propagation characteristics of the blast wave formed by different ignition positions are obviously different. The influence of the explosion location on explosion overpressure is greater than hydrogen volume fraction. At the same time，the overpressure of ignition behind the vehicle is generally greater than that of ignition above the vehicle. The peak pressure at the position 2 m behind the vehicle can reach about 100 kPa. The rear ignition position within 2 m will cause serious injury or even death to the human body，and personnel within 4 m of the rear ignition position will suffer different degrees of injury.

Inattentional blindness is a human error related to selective attention or inattention. In order to reduce safety accidents caused by inattentional blindness in high-altitude work among construction workers，30 participants were selected for an experiment to analyze the importance of inattentional blindness in the failure of safety risk perception，as well as the personality trait-related factors that affect inattentional blindness and the failure of safety risk perception，and to establish practical safety management strategies. The results show that inattentional blindness accounts for 50% of the failure of safety risk perception. In addition，personality traits have a significant relationship with inattentional blindness and failure of safety risk perception，with extraversion，conscientiousness，and openness significantly correlated with inattentional blindness and failure of safety risk perception. Workers with low extraversion，high conscientiousness，and low openness have lower proportions of safety risk perception failure and inattentional blindness.

In order to understand the research status and development trends of evacuation lighting in disaster scenarios，based on Citespace and literature visualization tools，408 articles as samples up to July 2023 were selected from the core journal database of China National Knowledge Infrastructure (CNKI) and Web of Science (WOS)，and analyzed from the aspects of publication year，journal source，author organization，topic clustering and keywords. Results show that this topic has appeared a rapid upward trend in English literature in the past 10 years. Most of the researchers are from the United States and China. There has been no significant growth in Chinese literature during the same period. The research in China focuses on building fire evacuation，and some nighttime disaster-appropriate lighting. English focuses on a variety of disaster scenarios，which tends to extend from indoor evacuation lighting to outdoor evacuation lighting. The research method is mainly technical application and problem induction in Chinese，and experimental simulation and behavioral research in English. Its research method from real scene simulation to model calculation combined with virtual reality is worthy learning. It is necessary to strengthen research on evacuation lighting in various disaster types and multiple scenarios，and explore evacuation lighting methods suitable for disaster evacuation in outdoor environments in the future.

In order to achieve a quantitative evaluation of individual pilot's exceedance risk，a refined evaluation model for pilot's individual exceedance risk was established based on QAR data and the flight operations quality assurance(FOQA) monitoring items. Firstly，according to accident statistics，International Civil Aviation Organization (ICAO) and the core risks divided by the FOQA station，the FOQA monitoring items associated with the three types of core risks were selected as the evaluation indexes，and the risk value for each core risk of the individual pilots was calculated. In the next step，the weight of each core risk value was calculated by entropy weighted TOPSIS. Then，the refined evaluation model for the pilot's individual exceedance risk was established. Finally，the model was applied to the quantitative evaluation of actual flight risk. By collecting 9 317 pieces of multi-source fusion data from the FOQA station of Civil Aviation Administration of China (CAAC)，the individual exceedance risk of the pilots were quantified，the ranking of individual pilots' exceedance risk was obtained，and the pilot's individual exceedance risk levels were also divided with the use of K-means clustering algorithm. The results show that the model can quantify and rank 1 693 individual pilots' exceedance risk，and divide the pilot's exceedance risk into three types，including high risk，medium risk and low risk.

In order to improve the safety and intelligence level of forklift truck，a forklift stability warning method based on multi-core parallel digital twin is proposed. First，the open-source high-precision inertial navigation sensor is used to evaluate the driver's operating habits and road smoothness，and then drive the digital twin operation. Secondly，the optimization algorithm is used to calculate the limit operating parameters that meet the stability conditions，such as the highest load and the fastest driving speed. Then，two acceleration strategies are proposed，which use the open source C language compiled solver and multi-core Central Processing Unit (CPU) in parallel，to shorten the optimization iteration time. Finally，taking a forklift truck as the test object，the accuracy of the measurement of the flight control system is verified，and the real-time performance of the digital twin stability early warning method is analyzed. The results show that the flight control system has high monitoring accuracy，the theoretical calculated values are basically consistent with the collected values，and the longitude and latitude deviation of global positioning system (GPS) is about 1 m. The digital twin program has a faster prediction speed. The digital twin compiled by the open source C language is 3 times faster than the Simulation X3.8 platform，and the parallel digital twin method is 20 times more efficient than the simulation platform.

In order to avoid the accident of CO poisoning in coal mines，according to the principle of adsorption catalysis，CuCl-CeO₂，a composite CO scavenger with both adsorption and catalytic properties，was prepared by thermal dispersion method using rare earth oxide CeO₂ as catalyst carrier and CuCl as adsorbent. The CO elimination performance of CuCl，CeO₂ and CuCl-CeO₂ was studied by cone calorimeter. At the same time，the peak pressure of gas explosion and the CO elimination effect of CuCl-CeO₂ were studied by a 20 L explosion ball-gas chromatography system. The results show that the CuCl-CeO₂ composite scavenger can effectively reduce the release rate of CO during the whole heating process，and its elimination performance is better than that of CuCl or CeO₂ alone. When the mass fraction of CuCl is 50 %，the CO elimination rate of CuCl-CeO₂ is the highest，reaching 88.0 %. With the increase of CuCl-CeO₂ mass concentration，the peak pressure of gas explosion gradually decreases，the time to reach the peak pressure of explosion is significantly delayed，and the amount of CO released is also decreasing. When the mass concentration of CuCl-CeO₂ is 1.00 g/L，the effect of explosion suppression and CO elimination is the best. The peak pressure of gas explosion is reduced from 0.508 MPa to 0.387 MPa，the time to reach the peak pressure of explosion is delayed from 237.6 ms to 483.2 ms，and the volume fraction of CO is reduced from 0.879 7% to 0.108 9%，which effectively reduces the peak pressure of gas explosion and CO release.

The properties and risk characteristics of grey rhinos have been deeply investigated and used，which are new emerging concepts and metaphor theories in risk management areas. To prevent and mitigate risks and challenges nowadays，it is urgent to systematically investigate the grey rhino-related contexts. The risk classification system，evolutionary mechanism，and management strategies of grey rhinos were explored by integrating existing theoretical models and risk classification approaches. The results indicated that the grey rhino risk was attributed to objective environmental factors and subjective cognitive factors. Moreover，the grey rhino risk can be divided into hidden，stationary，and collisional gray rhinos based on properties，cognitive，state，time，spatial，and subject perspectives. The risk development trend of each grey rhino species was evaluated based on the mechanism of risk perception，risk distance，and risk framework influence factors. Furthermore，an evolutionary framework of "accumulation-fluctuation-mutation" within a complicated system was proposed to develop risk management strategies and improve cognitive abilities by identifying hidden gray rhinoceroses that were not easily perceived. The innovative idea is strengthened to resolve static grey rhinos of normalized coexistence，and agile mode is created to deal with sudden bursts of collision gray rhinos.

To address the limitations of large language models in safety engineering，such as the corpus size，input processing capabilities and privacy concerns，ChatSOS，a Q&A system based on large language models，was developed. Based on 117 explosion incident reports from 2013 to 2023，a vector database to enhance the system's capability was constructed. ChatSOS integrated prompt engineering and external knowledge base to retrieve and analyze relevant data from the database. Compared to ChatGPT，ChatSOS integrated the external knowledge base，so that the big language model could retrieve the relevant corpus from the database according to the user's input information and make in-depth analysis. The results show that ChatSOS excels in in-depth professional problem analysis，autonomous task allocation，and providing detailed summaries and recommendations based on incident reports. By combining with the external knowledge database，the limitations of the large language model's professional corpus in safety engineering are overcome，which prevents performance degradation associated with fine-tuning on new datasets，broadens the application of large language models in this field，and paves the way for future advancements in automation and intelligent systems.

In order to solve the unreasonable problem of coal mine safety investment structure and decision scheme，the safety investment evaluation system was established to comprehensively evaluate the decision scheme of a coal mine over the years. Firstly，based on the perspective of safety value，considering the relationship between safety function and safety output，eight evaluation indexes were selected to construct the safety investment evaluation system of coal enterprises. Secondly，entropy weight method and analytic hierarchy process (AHP) were used to determine the index weight comprehensively. Finally，the SPA-TOPSIS method was used to analyze and evaluate the 2012-2022 decision scheme of a coal mine，and the evaluation scheme was optimized and the improvement suggestions for practical problems were proposed. The results show that the coal mine enterprises should pay more attention to the investment in safety education and industrial health indicators. Coal mine enterprises should comprehensively consider the safety function needs and safety output benefits when making safety investment decisions and reasonably adjust the focus of future safety investment decision by referring to the optimal investment allocation.