Aeri Cho

Unmanned underwater vehicles (UUVs) are essential tools for marine exploration, research, and surveillance. Accurate state estimations are critical for effective navigation, but conventional methods, such as Doppler velocity logs (DVLs) and inertial navigation systems, are expensive and vulnerable to environmental conditions. Inspired by the biological lateral line system in fish, this study proposes an enhanced pressure variation model (PVM) that estimates the velocity and drift angles using the data from pressure sensors. The improved model introduces unified regression coefficients and accounts for nonlinear flow effects, reducing the reliance on motion-specific parameters and increasing the adaptability across various maneuvering conditions. The model was validated by conducting extensive computational fluid dynamics (CFD) simulations across multiple motion scenarios. The enhanced PVM achieved high estimation accuracy while maintaining robustness under different dynamic conditions. The contributions of this study include the following: (1) a refined estimation framework using a unified coefficient model, (2) a low-cost, environment-resilient alternative to traditional systems, and (3) verified reliability through CFD-based performance evaluations. Future work will focus on experimental validation, extending the performance to large-angle motions, and developing a real-time data processing module to enable in situ application. This approach supports more autonomous and reliable UUV navigation for marine robotics and underwater missions.

When a submarine moves near the free surface, the lift and drag characteristics that act on it are different compared to when in deep water; for example, waves on the free surface cause submarine motions that are not seen in deep water conditions and lead to changes in speed, fuel efficiency, safety, and maneuverability. To accurately predict the maneuverability of a submarine, it is necessary to consider how both maneuvering and seakeeping performance are affected by free-surface effects during the design stage. In this study, the unified maneuvering and seakeeping dynamic model is proposed. In the maneuvering performance analysis, hydrodynamic forces in the horizontal plane were calculated using STAR-CCM+. In the seakeeping performance analysis, the 6-DOF motions of the submarine and the mean wave drift forces in the horizontal plane were calculated using Ansys AQWA. Since the maneuvering motion component has a relatively long period and the seakeeping motion component has a relatively short period, the unified maneuvering and seakeeping dynamic model for a submarine moving near the surface was established using a two-time-scale approach. Using the established unified maneuvering and seakeeping dynamic model, turning circle simulations were performed in both calm water and in waves. In calm water, there were no significant differences as depth was varied. However, in irregular waves, significant differences were found in the trajectories and motion variables as depth varied. These findings underscore the necessity of accounting for sea surface conditions when operating near the free surface to ensure safety and avoid potentially hazardous scenarios during submarine operations.

Investigating ship motion under real conditions is vital for evaluating the seakeeping performance, particularly in the design process stage. This study examined the influence of the principal particulars of a trawler on its seakeeping performance. The wave conditions in the Bering Sea are investigated using available data. The length-to-beam (L/B) and beam-to-draft (B/T) ratios of the ship are changed by 10% for the numerical simulation. The response amplitude operator (RAO) motion, root mean square (RMS) value and sensitivity analysis are calculated to evaluate the influence of the trawler dimensions on ship motions. The peak RAO motion affected the ship motions noticeably because of the resonance at the natural frequency. The L/B and B/T ratios are important geometric parameters of a ship that significantly influence its RMS motion, particularly in the case of roll and pitch. The change in the B/T ratio has a good seakeeping performance based on a comparison of the roll and pitch with the seakeeping criteria. The present results provide insights into the seakeeping performance of ships due to the influence of the principal dimensions in the design stage.

This study presents a pressure variation model (PVM) derived from the regression analysis of dynamic pressure computed through numerical analysis to estimate the velocity of underwater vehicles. Furthermore, the drift angle estimation algorithm was developed using predicted velocities from PVM and pressure sensor differences. This approach estimates the single-motion states of underwater vehicles, such as straight, turning, and gliding. Furthermore, it confirms the viability of state estimation even in multiple motions involving turning and gliding motion with a drift angle and spiral motion. The comparison with numerical analysis results validated prediction accuracy within 15%.