Analyzing the dynamic domino effect in fuel truck parking lots

Fuel truck parking lots are crucial components of transportation networks, facilitating the storage and organization of fuel trucks to ensure efficient fuel distribution. These facilities play a vital role in minimizing transportation delays and reducing emissions. However, the proximity of fuel tanks in these lots poses inherent risks, including fire, explosions, and domino accidents. The present study aimed to analyze the domino effect in fuel truck parking lots. To achieve this, a hybrid approach combining the Dempster-Shafer Theory (DST) method with the Bayesian networks (BNs) was employed for quantitative cause-consequence analysis. Additionally, empirical equations were utilized to model the consequences, followed by the dynamic analysis of the domino effect using the Multi-Agent (MA) method. The accuracy of the introduced hybrid method was evaluated through a case study conducted at one of the most sizable parking lots. The study demonstrated the effectiveness of proposed approach in quantifying risks and identifying mitigation strategies, highlighting its applicability in real-world scenarios. Moreover, the proposed hybrid model offers a scientifically rigorous framework for handling uncertainty, providing valuable insights for enhancing safety measures and mitigating risks in fuel truck parking lots.