A quantitative risk assessment model for lightning-induced failures in natural gas automated metering systemsOA

As one of the most probable natural hazards leading to technological disasters,lightning can easily damage analytical instruments in oil and gas stations,resulting in data loss and operational anomalies.Compared with other equipment,Natural Gas Automated Metering Systems(NGAMS),which comprise various precision analytical instruments,are more susceptible to lightning strikes.This vulnerability often leads to production shutdowns,inaccurate metering,and commercial disputes.A quantitative risk assessment model for lightning-induced failures in NGAMS is proposed to enhance the integrity management of metering stations.The model consists of a lightning failure probability model and a consequence evaluation method that incorporates reputational loss.First,a lightning identification criterion is established based on the electro-geometric model,and a basic lightning probability model is developed using Monte Carlo simulations.Second,a basic failure probability model is constructed by modeling the system''s equivalent circuit and incorporating the insulation withstand characteristics of the equipment.Two correction factors,specifically the location factor and lightning protection measures,are subsequently incorporated to establish the comprehensive lightning failure probability model.Furthermore,a reputational loss evaluation method is proposed by developing a reputation loss indicator system and integrating the Z-BWM method with cloud model.Case study results show that when the average lightning probability is 1.03×10^(-2),the maximum system failure probability reaches 4.14×10^(-5),representing a 35.29%increase over the inherent failure probability.The corresponding reputational loss is classified as low risk,verifying the effectiveness and practicality of the proposed model.