https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/9816 2026-05-02T13:52:28Z https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/11012 Title: CFD 기반 자항 해석의 격자 민감도 정량 평가 Authors: 안준범; 김백현; 이상봉; 심민경; 손석호; 김정중 Abstract: This study performs resistance and self-propulsion simulations for four ship types using computational fluid dynamics(CFD) and evaluates the impact of grid resolution on prediction accuracy and numerical convergence. A total of 56 cases were analyzed by applying coarse, medium, and fine mesh systems. Convergence behavior was assessed based on the Grid Convergence Index(GCI) methodology. Among the 56 cases, 42 were included in the GCI analysis, showing order of convergence(p) greater than 1.5 and grid uncertainty(UG) below 3% in most conditions. In particular, when over 10 million cells were used, simulation results showed consistent trends across different speeds within the same hull form, indicating robust convergence and reliability. Although a few cases were excluded due to irregular convergence behavior, their impact on the overall tendency was negligible. The findings provide practical guidelines for grid arrangement and uncertainty quantification in CFD-based ship performance predictions. 2025-12-01T00:00:00Z https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/11232 https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/11346 Title: A Simulation-Based Backup Monitoring System for Remote Operation Centers Under Degraded Communication Conditions Authors: Jo, Hyun Jae; Kim, Geonwoo; Yim, Geun tae 2025-10-21T00:00:00Z https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/11411 Title: Exploring feasibility of UAV-Based Situational Awareness Support for Maritime Autonomous Surface Ships through Scenario-Based Sea Trial Authors: Kim, Dong Eon; Jo, Hyun Jae; Youn, Taejun; Yim, Geun tae Abstract: This study investigates the feasibility of employing unmanned aerial vehicle (UAV) to enhance the situational awareness capabilities of Maritime Autonomous Surface Ships (MASS), thereby improving the reliability of their operations. However, fixed situational awareness sensors on MASS, including cameras, LiDAR, and radar, are subject to inherent physical limitations due to their static installation, reducing their effectiveness in dynamic and complex navigational environments. To address these limitations, data collected from scenario-based real-sea trials were applied in simulations to evaluate the effectiveness of UAV assisted situational awareness. For this purpose, we designed and conducted trials using the sea-trial testbed vessel HaeyangNuri. The representative operational scenario was set in a geographically constrained channel. For the simulation, the vessel’s motion was modeled using the Velocity Obstacle method, and a weighted exponential model, incorporating the distance and time to the closest point of approach (DCPA and TCPA), was developed to quantitatively assess collision risk. The results demonstrated reduced collision risk and improved operational stability when UAV were employed. These findings highlight the potential of UAV to support MASS navigation, and future work will focus on developing a robust MASS？UAV cooperative framework for broad operational applications to further enhance the operational reliability of MASS. 2025-10-21T00:00:00Z