Byeong-Cheol Park

Recently, various dynamic risk analysis methods have been suggested for estimating the risk index by predicting the possibility of accidents and damage in real time. It is necessary to quickly estimate the risk of an accident by predicting the probability and consequences of accidents, which are quantitative criteria for ship risk assessment. This study aimed to develop an algorithm for predicting the consequences of accidents in real time to perform a dynamic risk assessment and, using this algorithm, formulate a ship accident–response procedure that can be used in fire accidents during LNG bunkering. The risk of fire was estimated by predicting the hole size due to changes in the liquefied natural gas (LNG) transport conditions and the consequence based on the fire accidents scenario in LNG-fueled ships. The prediction model was trained with the hole prediction data using Ansys CFX and with the consequence data using DNV Phast, and the consequences of fire were compared and evaluated by applying the trained results. A method for estimating the size of the fire based on the predicted consequence is proposed, which supports fast decision making in fire accidents during LNG bunkering by identifying the potential size of the fire at the beginning of an accident.

Structural analysis, based on a global ship model, is vital for examining the structural strength and safety of a hull. In the “NASTRAN” global ship model, only the structural members and cargo tank of a ship are modeled and the outfit, electric system, and other tanks and liquid are omitted from the model. The additional weight of these omitted elements, however, constitutes part of the light weight of the ship and must be considered in conducting an accurate structural analysis of the ship. Generally, the weight of these omitted elements is calculated using the trim and stability information of the ship and is then added to the model. In such cases, the center of gravity of the global ship model, which now includes the weight of these omitted elements, must be adjusted to the target center of gravity required for the analysis. In this study, an algorithm was developed to satisfy the target center of gravity while distributing the weight of these omitted elements to the global ship model using Gaussian elimination. The algorithm was developed using C#, and its accuracy was verified by applying it to the global ship models.

Directional drilling involves three sections—vertical, curved, and horizontal—and is used for drilling offshore wells and mining unconventional resources. The initial design of a well trajectory is important because the total length of the well trajectory is associated with the drilling cost; furthermore, the drag force and torque may cause buckling and damage the drill pipe. The well trajectory should be optimized considering the length and load of drill pipes. In this study, a new method of optimizing directional well trajectory is used to formulate the objective function considering the length, drag, and torque. To verify the applicability of this method, we applied it to an actual oil well and a theoretical oil well. The results obtained show that the use of the proposed method in the initial design of drilling trajectory can reduce the torque by up to 15%, drag by 2.6%, and length by 8.5% for the two models used in this study. This method is safer as it reduces the risk of buckling compared to the design that relies on the previous designer’s experience, and it reduces the trajectory length; thus, it can save time and costs of drilling.