Quantitative Evaluation of Safety Resilience of Large-Scale Oil Tank Area System Based on Improved IRML

Abstract As a key link in ensuring oil and gas supply and national strategic reserves, large-scale oil storage tank areas have dual attributes of energy security and public safety. Large tank farms tend to be large-scale, systematic, complex, and intelligent, with a wide variety of equipment types and high levels of automation within their systems, as well as numerous cascading failures and secondary disasters. To ensure the safe operation of large-scale oil and gas tank areas, this paper proposes a quantitative evaluation method for the safety resilience of large-scale oil and gas tank area systems based on improved IRML. On the basis of the directed regular network of the oil and gas tank area system, the reconnection probability is introduced to generate a small-world network. At the same time, three time parameters from IRML are introduced, and the time parameter definition is related to the degree of local aggregation in the network. The dynamic propagation and evolution characterization of failures within the network are carried out to obtain the system safety resilience curve and quantitatively evaluate the overall safety resilience of the system in emergency scenarios. This model achieves a balance between model complexity and model accuracy, while retaining the characteristics of short paths and high clustering in the tank farm system network at low complexity modeling, while avoiding the influence of subjective factors on the resilience assessment results. This paper takes a grid arranged tank area as an example to simulate the safety resilience of the tank area system under the sudden events of personnel misoperation causing abnormal instructions and tank corrosion leakage. The instantaneous resilience curve of the system over time domain is obtained, and the calculated values for different scenarios are 0.9012 and 0.7568, respectively. The model achieves accurate evaluation and analysis of the resilience of large-scale oil and gas tank area systems under different emergencies, providing a good theoretical basis and decision-making basis for ensuring tank area safety and deploying safety guarantee technical measures.