In this study, the basic configuration and operation concept of a CO₂ terminal were identified by conducting a system engineering process. The performance goal of a CO₂ terminal was determined by requirement analysis. Then, functions and timelines were derived by functional analysis to meet the performance goal. Equipment to perform the functions were defined and finally, a process flow block diagram of the CO₂ terminal was acquired. The CO₂ terminal in this study consisted of three parts. First, the CO₂ loading/unloading part is responsible for liquid CO₂ unloading from the carrier and loading vapor CO₂ onto the carrier. Secondly, the liquid CO₂ transmission part extracts liquid CO₂ from the storage tanks and increases the pressure until it satisfies the offshore pipeline transportation condition. The vapor-treatment part collects boil-off gas, generates vapor CO₂, and charges the storage tanks with vapor CO₂ to control the pressure of the storage tanks that discharge liquid CO₂. Finally, the study results were compared with a liquefied natural gas (LNG) terminal. The biggest difference between the CO₂ terminal in this study and the LNG terminal is that a vaporizer is essential in the CO₂ terminal due to the smaller storage capacity of the CO₂ terminal and, therefore, the lower amount of boil-off gas.

Autonomous underwater vehicles have long been used in marine explorations, and their application in recent polar expeditions is particularly noteworthy. However, the complexity and extreme conditions of the polar environment pose risks to the stable operation of autonomous underwater vehicles. This study adopted the methodology of fuzzy fault tree analysis to deeply analyze the operational risks of autonomous underwater vehicles in polar environments. While traditional fault tree analysis maps the causal relationships and probabilities between basic and intermediate events, fuzzy fault tree analysis models the uncertainty of data and determines the failure probability by integrating expert opinions. This study revealed that polar environment-induced failures play a more substantial role in autonomous underwater vehicle loss in polar regions than inherent system failures. The study identified ‘recovery failure’ and ‘poor communication’ as the major risk factors facing autonomous underwater vehicles in polar environments, exhibiting the highest failure probabilities. Specifically, among various polar environmental factors, ‘large ice concentration’, ‘ice thickness’, and ‘roughness of ice underside’ under ‘bad’ conditions were found to have a significant impact on the autonomous underwater vehicle’s failure probability. The fuzzy fault tree analysis method in this study successfully filled the gap created by the absence of historical data by effectively incorporating expert opinions, enabling a quantitative presentation of the impact of polar environments, which has been previously difficult to convey in qualitative terms.