Seaport infrastructure risk assessment for hazardous cargo operations using Bayesian networks.

Area of Science:

• Maritime Safety
• Risk Management
• Infrastructure Resilience

Background:

• Seaport infrastructure recovery from hazardous cargo accidents is resource-intensive and time-consuming.
• The risks to seaport infrastructure from hazardous cargo operations are not sufficiently understood.
• This study addresses the knowledge gap concerning hazardous cargo risks in seaports.

Purpose of the Study:

• To comprehensively examine the risks to seaport infrastructure stemming from hazardous cargo operations.
• To identify critical risk factors and their interdependencies.
• To propose practical risk mitigation strategies.

Main Methods:

• Literature review, incident report analysis, and expert consultations.
• Development of Conditional Probability Tables (CPTs) using expert judgments and logistic regression.
• Risk analysis conducted via Bayesian networks (BN) with sensitivity analysis.

Main Results:

• Fire and explosion (8.73%), corrosion (5.88%), and improper handling (5.61%) are primary risk contributors under typical conditions.
• Improper handling and corrosion significantly amplify risk, by 153% and 96% respectively.
• Sensitivity analysis identified critical risk factors influencing seaport infrastructure.

Conclusions:

• Proactive risk management is essential for seaport infrastructure resilience.
• Technological solutions like tracking systems, AR/VR training, and automation can reduce human error and enhance safety.
• Implementing suggested measures can ensure uninterrupted seaport operations and minimize accident impacts.