“…Using CFD software Fluent [64], we can simulate the solutions of β under different δ r . The specific numerical values of the hydrodynamic coefficients used in the simulation are shown in Table 2.…”
An accurate motion model and reliable measurements are required for autonomous underwater vehicle localization and navigation in underwater environments. However, without a propeller, underwater gliders have limited maneuverability and carrying capacity, which brings difficulties for modeling and measuring. In this paper, an extended Kalman filter (EKF)-based method, combining a modified kinematic model of underwater gliders with the travel-time differences between signals received from a single beacon, is proposed for estimating the glider positions in a predict-update cycle. First, to accurately establish a motion model for underwater gliders moving in the ocean, we introduce two modification parameters, the attack and drift angles, into a kinematic model of underwater gliders, along with depth-averaged current velocities. The attack and drift angles are calculated based on the coefficients of hydrodynamic forces and the sensor-measured angle variation over time. Then, instead of satisfying synchronization requirements, the travel-time differences between signals received from a single beacon, multiplied by the sound speed, are taken as the measurements. To further reduce the EKF estimation error, the Rauch-Tung-Striebel (RTS) smoothing method is merged into the EKF system. The proposed method is tested in a virtual spatiotemporal environment from an ocean model. The experimental results show that the performance of the RTS-EKF estimate is improved when compared with the motion model estimate, especially by 46% at the inflection point, at least in the particular study developed in this article.
“…Using CFD software Fluent [64], we can simulate the solutions of β under different δ r . The specific numerical values of the hydrodynamic coefficients used in the simulation are shown in Table 2.…”
An accurate motion model and reliable measurements are required for autonomous underwater vehicle localization and navigation in underwater environments. However, without a propeller, underwater gliders have limited maneuverability and carrying capacity, which brings difficulties for modeling and measuring. In this paper, an extended Kalman filter (EKF)-based method, combining a modified kinematic model of underwater gliders with the travel-time differences between signals received from a single beacon, is proposed for estimating the glider positions in a predict-update cycle. First, to accurately establish a motion model for underwater gliders moving in the ocean, we introduce two modification parameters, the attack and drift angles, into a kinematic model of underwater gliders, along with depth-averaged current velocities. The attack and drift angles are calculated based on the coefficients of hydrodynamic forces and the sensor-measured angle variation over time. Then, instead of satisfying synchronization requirements, the travel-time differences between signals received from a single beacon, multiplied by the sound speed, are taken as the measurements. To further reduce the EKF estimation error, the Rauch-Tung-Striebel (RTS) smoothing method is merged into the EKF system. The proposed method is tested in a virtual spatiotemporal environment from an ocean model. The experimental results show that the performance of the RTS-EKF estimate is improved when compared with the motion model estimate, especially by 46% at the inflection point, at least in the particular study developed in this article.
“…The distance between the boundaries of the calculation domain and module is more than 2 L in the longitudinal direction and more than L in the lateral and vertical direction when the module has its maximum moving range [22]. The flow is stable between the module and the inlet surface and does not cause backflow within 2 L [23].…”
In underwater towing operations, the drag force and vertical offset angle of towropes are important considerations when choosing and setting up towing equipment. The aim of this paper is to study the variation in drag force, vertical offset angle, resistance, and attitude for towing operations with a view to optimizing these operations. An underwater experiment was conducted using a 1:8 scale physical model of a subsea module. A comprehensive series of viscous Computational Fluid Dynamics (CFD) simulations were carried out based on Reynolds-averaged Navier–Stokes equations for uniform velocity towing. The results of the simulation were compared with experimental data and showed good agreement. Numerical results of the vorticity field and streamlines at the towing speeds were presented to analyze the distribution of vortexes and flow patterns. The resistance components were analyzed based on the numerical result. It was found that the lateral direction was a better direction for towing operations because of the smaller drag force, resistance, and offset angle. Similar patterns and locations of streamlines and vortexes were present in both the longitudinal and lateral directions, the total resistance coefficient decreases at a Reynolds number greater than that of a cylinder.
“…The speed range for most AUVs ranges from 3 to 5 kn; therefore, the first two speeds were used for appendage optimization for subsequent chapters, and the last three speeds were used to verify the accuracy of the calculation method. Works by Wu [10] and Dantas and Barros [11], and our previous investigation [6,12] were referred to conducted the validation procedure. As shown in Fig.…”
Navigational range is an important attribute of autonomous underwater vehicles (AUVs), and drag reduction efforts have been pursued to improve overall efficiency. Improved efficiency results in a more capable vehicle over all. Historically, the majority of research focused on drag reduction has been concentrated on the optimization of vehicle hull geometry. The influence of the hull appendages on drag, however, has been largely ignored owing to their smaller size. In this study, the impacts of appendage size and position on vehicle drag are investigated using a computational fluid dynamics method. The results indicate that appendages increase more drag because of their impact on the development of turbulence. The investigation of the interactions between multiple appendages fixed on a vehicle hull shows that optimization is necessary for drag reduction. This paper presents an arrangement optimization method for AUV appendages based on the Kriging approximation model and the multi-island genetic algorithm. The results of the optimization show that appendage influence on hydrodynamic performance is directly proportional to its size, and that a distributed arrangement is beneficial for drag reduction.
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