Considering the complexity and fuzziness of railway operation emergencies, this study proposes a variable fuzzy evaluation model to assess emergency management capability. Based on the four-stage emergency management framework—prevention, preparedness, response, and recovery—an index system consisting of 17 evaluation indicators for railway emergency management capability is established, with reference to the "dual prevention mechanism" for value assignment. To ensure scientific rigor and reliability, subjective weights obtained through Principal Component Analysis (PCA) are integrated with objective weights derived from the CRITIC method, thereby forming a combined subjective–objective weighting model. Using the "10·15" Beihe Railway passenger train derailment accident in Heilongjiang Province as a case study, four different parameter combinations of the variable fuzzy evaluation method are applied to calculate the grade characteristic values of emergency management capability. The results indicate that the evaluation level of emergency management capability for railway operation emergencies is Grade III (moderate), with potential for advancement to Grade II (stronger). Recommendations for enhancing the emergency management capability of railway operation emergencies are provided, thereby verifying the scientific validity and rationality of the proposed model.

In order to study the influence of tunnel excavation by a drilling and blasting method on the ground surface, a method of predicting ground surface vibration waveforms suitable for actual drilling and blasting tunnelling engineering is established. First, based on the theoretical solution of surface vibration waves caused by spherical charge blasting, a more concise surface vibration wave function of spherical charge that is suitable for practical engineering is constructed. The correctness of the constructed waveform function is verified by the measured data. Second, the waveform function of surface vibration waves caused by cylindrical charge explosions perpendicular to the tunnel working face is obtained by superposition of the spherical charge. Then, the surface vibration response of the unexcavated section during tunnel blasting is calculated using the vibration wave superposition method. In the excavated section, the influence of the hollow effect of the tunnel on the vibration wave propagation was considered, and the surface vibration response of the tunnel was analysed using conformal transformation and vibration wave superposition. Finally, based on actual engineering, the correctness of this blasting vibration prediction method is verified using field test data.

The "Identification of Major Hazard Sources for Hazardous Chemicals" establishes regulations for production, storage, use, and trading of hazardous chemicals. However, it lacks provisions for transportation – a mobile hazard source requiring specialized attention. As China's primary mode of hazardous chemical transport remains road transportation, which offers flexibility, cost-effectiveness, and efficiency, the challenges persist. Given the inherent risks of flammability, explosiveness, and corrosiveness, coupled with unpredictable factors during transit (particularly in tankers where uncertainties are most pronounced), accidents involving hazardous chemical tankers can have catastrophic consequences. To minimize accident rates, conducting risk assessments for road transport is crucial. This study employs Bayesian networks derived from junction graphs, integrates triangular fuzzy theory, and applies expert-weighted similarity aggregation to synthesize expert opinions. Through posterior probability analysis, sensitivity testing, and importance evaluation, key factors contributing to tank ruptures are identified. The developed dynamic risk assessment model for road transport of hazardous chemical tankers utilizes GeNle software to address uncertain risk factors.

With the rapid development of the logistics industry, people have higher and higher requirements for the timeliness of logistics. As a new mode of transportation, high-speed rail freight express can effectively reduce the environmental pollution caused by road transportation, and is of great significance in promoting the sustainable development of high value-added and small-batch cargo transportation. Railway enterprises use high-speed rail train confirmation cars, idle carriages, large luggage storage and other locations to carry out high-speed rail express transportation, giving full play to the advantages of high-speed rail transportation, but while improving economic and social benefits, it also poses challenges to the safety of high-speed rail operation. In this paper, the high-speed rail freight safety evaluation is taken as the research object, and the combination of analytic hierarchy process (AHP) and cloud model model is used to construct a high-speed rail freight safety evaluation model based on AHP-cloud model. Through the analysis of the influencing factors of high-speed rail freight safety, the key factors affecting safety were determined, and the AHP method was used to analyze the weight of each factor, and then combined with the cloud model model to quantify the safety evaluation criteria to obtain the safety evaluation grade. Finally, the feasibility and effectiveness of the model are verified by examples.