Simulated Maneuvers Research Articles

Manoeuvring in shallow and confined water with model predictive track controllers

Abstract Autonomous and computer-assisted navigation, for example through portable pilot units and data-driven decision supportive systems, is in full development. Remote-controlled vessels (manned but without a captain steering continuously on board) are used in Belgium (by Seafar in inland shipping) but also in other countries. A model predictive controller has been used to investigate environmental and operational parameters for the passage of the river Seine in Paris by different ship types. These fast-time simulations have been compared with simulations in real time executed by skippers on a ship manoeuvring simulator or measured real life tracks. A good predictability of the real situation requires accurate manoeuvring models. But what if this accuracy cannot be guaranteed? An illustration is made by comparing the tracks if, in the prescience prediction phase for the controller, wind or bank effects are neglected or doubled. The development of model predictive deep reinforcement learning control algorithms for navigation will be one of the challenges of the Data-driven Smart Shipping project that started May 2024.

Investigation of Vessel Manoeuvring Abilities in Shallow Depths by Applying Neural Networks

A set of planar motion mechanism experiments of the Duisburg Test Case Post-Panamax container model executed in a towing tank with shallow depth is applied to train a neural network to analyse the ability of the proposed model to learn the effects of different depth conditions on ship’s manoeuvring capabilities. The motivation of the work presented in this paper is to contribute an alternative and effective approach to model non-linear systems through artificial neural networks that address the manoeuvring simulation of ships in shallow water. The system is developed using the Levenberg–Marquardt backpropagation training algorithm and the resilient backpropagation scheme to demonstrate the correlation between the vessel forces and the respective trajectories and velocities. Sensitivity analyses were performed to identify the number of layers necessary for the proposed model to predict the vessel manoeuvring characteristics in two different depths. The outcomes achieved with the proposed system have shown excellent accuracy and ability in predicting ship manoeuvring with varying depths of shallow water.

Numerical simulations of the ONRT ship maneuvering in calm water and head waves with the partially rotating grid method

This research delves into the maneuverability aspects of a model-scale ONRT surface combatant ship using Computational Fluid Dynamics (CFD) simulations. A key aspect of this study is the comparison of the actuator disc (AD) model and the partially rotating grid (P) method in calm water, complemented by an in-depth analysis of the P method for simulations in waves. Utilizing these methods, the study investigates the performance of the ship in propeller open water, self-propulsion, and complex maneuvers like turning circle and zig-zag. Key findings highlight the superiority of the P method in closely aligning with experimental data, particularly in capturing complex dynamics of ship maneuvers. This research underscores the critical role of propeller side force in maneuvering simulations, a factor often neglected in simpler models like the AD. Maneuvers in head waves are also examined, revealing the nuanced effects of wave orientation on the stability and maneuverability of the ship. This study highlights the effectiveness of CFD in simulating ship maneuvers and the need for ongoing refinement of these techniques to improve accuracy and reliability.

Research on digital twin architecture of ship maneuverability simulation for system model

Abstract With the development of civil and military requirements, ship maneuverability simulation systems tend to be complicated, and the traditional simulation methods are difficult to meet in terms of the development needs of digitalization. The joint simulation technology based on the FMI standard can realize the digital twin of complex system models, which can solve the difficult problem of multidisciplinary and multi-sub-system integration simulation. This paper analyzes the current domestic and foreign research content on joint simulation technology, digital twin technology, and complex system modeling, takes a typical Z-type maneuverability test as an example, establishes a multidisciplinary and cross-platform subsystem model, and designs and develops a ship maneuverability joint simulation algorithm and system software for the complex system model. The simulation results verify the effectiveness of the system modeling technique and the joint simulation technique based on FMI. Based on this system, the whole framework of the ship maneuverability simulation system, which is based on digital twins, is designed. According to the development requirements of ship maneuverability simulation, the main design framework, key technology, and implementation approach of this research method are given, which provides basic methods and ideas for the digital research of ship maneuverability simulation.

Uncertainty Analysis and Maneuver Simulation of Standard Ship Model

Maneuver simulation of a standard ship model gives indication of numerical accuracy. In the numerical calculation of ship maneuvering, uncertainty analysis is a necessary step to ensure the accuracy of the calculation. In this study, uncertainty pair analysis is carried out in the simulation of the turning circle motion of the standard ship model ONRT in waves. According to the uncertainty analysis procedure recommended by the International Towing Tank Conference (ITTC), the change of ship resistance caused by the number of grids is studied to determine the influence of grid density on the numerical prediction. The simulation of turning motion in waves is carried out based on the uncertainty analysis. It is found that the minimum number of overset grids for this simulation is 1.4 million. The numerical results are fairly accurate compared to experimental results, and this technique provides a method with low calculated cost for this simulation.

Bank interaction effects on ships in 6 DOF

This paper presents the used mathematical formulations to predict ship bank interaction in six degrees of freedom (6 DOF) as applicable in a ship manoeuvring simulator. The mathematical models are based on a comprehensive database (+10,000 model tests carried out in a towing tank) and are capable to cope with a variety of realistic cross sections, based on a limited set of coefficients. Compared to previous publications on bank effects, the lateral force of these bank effects with point of application at the forward perpendicular, is now predicted with an alternative mathematical model that offers the same predictability as the original one, but that better describes the physical background. Moreover, new formulations are included to predict the bank induced components of the ship in the vertical plane (heel, midship sinkage and trim). Although these tend to be neglected, the experimental results show that the effect of confinement and eccentricity can be significant and that a 6 DOF mathematical model is needed for a correct prediction of the manoeuvring behaviour.A difficulty that is still present is the correct separation of the open water contribution and the contribution due to confinement. This is especially the case for rather high displacement ship models, such as the KVLCC2 tanker, in the 7 m wide towing tank, that even sense the tank walls when being towed on the centreline. This topic will be coped with in future publications, along with an extension for ships that sail with a drift angle.

MMG 3DOF model identification with uncertainty of observation and hydrodynamic maneuvering coefficients using MCMC method

The trajectory prediction using ship maneuverability mathematical models is one of the essential technologies implemented in autonomous surface ship. Several ship maneuverability mathematical models and each one with a particular hydrodynamic coefficient approximation using towing tank tests are existed. However, it is presented difficult to directly inverse estimate the hydrodynamic maneuvering coefficients of a ship maneuverability mathematical model from operational data consisting of ship trajectory and maneuvering operation records. This paper proposed a method for estimating the hydrodynamic maneuvering coefficients of the MMG 3DOF model using three types of time-series ship motions (surge, sway, and yaw velocity) as observed data. In the assumption of this paper, there is uncertainty in observations and the hydrodynamic maneuvering coefficients of the MMG 3DOF model. The proposed method outputs samples of the simultaneous posterior probability distribution of the hydrodynamic maneuvering coefficients by the MCMC method using the observed data and stochastic model. A robust trajectory with a wide range can be presented by conducting ship maneuvering simulations using these samples. To verify the feasibility of the proposed method, this paper conducted observation system simulation experiments (OSSE) using the KVLCC2 L7 model and applied the proposed method to several free-running model ship tests. Results showed that on the assumption that MMG 3DOF model can explain the ship's state and trajectory in real world, the proposed method can estimate the ship hydrodynamic maneuvering coefficients of the MMG 3DOF model corresponding to the observed ship trajectory and control data including the error of observed data.

AGV maneuverability simulation and design based on pure pursuit algorithm with obstacle avoidance

This paper discusses the simulation of an automated guided vehicle (AGV) with the differential-drive mobile robot (DDMR) concept. Using this wheel configuration, the AGV can maneuver in tight workspaces. However, controlling a self-driving AGV with obstacle avoidance is not easy. Therefore, this paper proposes a control system to drive an AGV with several process stages. First, a kinematic model is formulated to represent the AGV with the concept of two wheels that can be controlled differentially. In the second stage, the pure pursuit control method is applied to the model so that the AGV can follow the waypoint coordinates determined and combine them with obstacle avoidance. Finally, the effectiveness of the control system was verified using simulation. The look-ahead parameter with a value of 0.2 meters shows optimal results so that pure pursuit control can reach all waypoint coordinates. Based on this simulation, the AGV prototype was then designed, assembled, and equipped with an internet of things-based obstacle avoidance system. While the simulation proves promising, the anticipated challenges identified in the AGV field test, such as GPS inaccuracies and signal obstructions, underscore the need for ongoing improvements in real-world applications.

Edukasi dan Simulasi Heimlich Manouver sebagai Upaya Penanganan Tersedak Anak Usia PAUD

Background: Choking is an emergency that can occur in children and requires immediate help. This activity aims to increase participants' knowledge and skills in carrying out first aid measures in cases of choking. Method: The partners in this activity are 53 PAUD mothers. The activity was carried out using a presentation using a choking management leaflet, then continued with a Heimlich maneuver simulation utilizing a child's phantom. Results: The participants' knowledge and skills increased, as indicated by their ability to answer questions from the presenter and demonstrate the Heimlich manouver correctly. Conclusion: Educational actions and Heimlich Maneuver simulations can improve participants' knowledge and skills in providing first aid for choking incidents in PAUD and Kindergarten children.

Determination of Maneuvering Force Coefficients for a Destroyer Model with OpenFOAM

_ Ship maneuvering performance can be predicted using various methods, including physical model tests, rapid simulations using coefficient-based forces, and high-fidelity computational fluid dynamics. This article considers the application of computational fluid dynamics for the prediction of hull force coefficients to be used as inputs to rapid maneuvering simulations. The open-source software OpenFOAM was used to simulate forces on the destroyer model DTMB 5415 for steady drift, oscillatory pure sway motion, and oscillatory yaw motion. Recommendations are provided regarding best practices in a number of areas, including domain size, mesh refinement, time step size, and turbulent modeling. Predicted forces for steady drift angles up to 12 degrees are typically within 10%of experimental values. For oscillatory sway and yaw motions, predicted forces are typically within 25%of experimental values. Keywords maneuvering; OpenFOAM; best modeling practices

A Weighted Feature Fusion Model for Unsteady Aerodynamic Modeling at High Angles of Attack

Unsteady aerodynamic prediction at high angles of attack is of great importance to the design and development of advanced fighters. In this paper, a weighted feature fusion model (WFFM) that combines the state-space model and neural networks is proposed to build an unsteady aerodynamic model for the precise simulation and control of post-stall maneuvers. In the proposed model, the influences of the physical model on neural networks are considered and adjusted by introducing a standardization layer and a new weighting method. A long short-term memory (LSTM) network is used to fuse two mappings: one from flight states to aerodynamic loads, and the other from low-fidelity data to high-fidelity data. Data from wind tunnel oscillation experiments at high angles of attack using a new kind of wire-driven parallel robot and the traditional tail support are used for verifying the proposed aerodynamic model. The output of the WFFM is also compared with predictions from other models, such as the state-space model, single LSTM model, and feature fusion model not including a feature weighting layer. Results demonstrate improved accuracy of the proposed model in the interpolation and extrapolation tests. Furthermore, the WFFM is applied to the flight simulation of F-16 with different control inputs. Compared with conventional models, the WFFM shows improved accuracy and better generalization capability.

State estimation of buses: A hybrid algorithm of deep neural network and unscented Kalman filter considering mass identification

Accurately obtaining vehicle state parameters is a crucial prerequisite for active safety control. However, key stability parameters of buses, such as sideslip angle and roll angle, are difficult to measure directly. Moreover, changes in the bus mass during the driving route can impact the vehicle state. To tackle these challenges, we identify the bus mass before state estimation, and propose a hybrid state estimation algorithm based on deep neural network (DNN) and unscented Kalman filter (UKF). First, the mass is identified using the recursive least squares (RLS) method based on longitudinal dynamics at each start of bus, and the yaw and roll moment of inertia are adaptively adjusted based on the identified mass. Second, a composite DNN combining the convolutional neural network (CNN), gated recurrent unit (GRU), and attention mechanism is designed to estimate sideslip and roll angles. As for the training dataset, it is acquired from different maneuvers simulated by TruckSim. Third, a UKF estimator is established based on 4-degree of freedom (DOF) vehicle dynamics model and magic tire formula, and the estimated values of DNN are inserted into UKF estimator as virtual observations. Finally, the proposed hybrid algorithm is validated through simulation maneuvers and real driving maneuvers based on MATLAB/Simulink and TruckSim software. The comparative results demonstrate that the proposed algorithm outperforms individual DNN estimation and UKF estimation, enhancing both estimation accuracy and reliability.

Foreword: Special issue on the Power-to-Melt and Maneuverability (P2M) Simulation Exercise

Foreword: Special issue on the Power-to-Melt and Maneuverability (P2M) Simulation Exercise

Global Path Planning for Autonomous Ship Navigation Considering the Practical Characteristics of the Port of Ulsan

This study introduces global path planning for autonomous ships in port environments, with a focus on the Port of Ulsan, where various environmental factors are modeled for analysis. Global path planning is considered to take place from departure to berth, specifically accounting for scenarios involving a need to navigate via anchorage areas as waypoints due to unexpected increases in port traffic or when direct access to the berth is obstructed. In this study, a navigable grid for autonomous ships was constructed using land, breakwater, and water depth data. The modeling of the Port of Ulsan’s traffic lanes and anchorage areas reflects the port’s essential maritime characteristics for global path planning. In this study, an improved A* algorithm, along with grid-based path planning, was utilized to determine a global path plan. We used smoothing algorithms to refine the global paths for practical navigation, and the validation of these paths was achieved through conducting ship maneuvering simulations from model tests, which approximate real-world navigation in navigational simulation. This approach lays the groundwork for enhanced route generation studies in complex port environments.

Power Prediction and Manoeuvring Study for an Inland Class Vessel

The paper explores the propulsive power requirements and manoeuvring capabilities of a popular class of inland bulk carriers in Bangladesh. After the initial verification study, model-scale CFD simulations are performed in calm, open waters at different speeds to assess hull resistance. The resistance results are then extrapolated to full scale for calculating propulsion power requirements. Subsequently, manoeuvring simulations are performed using PMM motions to evaluate static drift, pure sway, and pure yaw scenarios to calculate manoeuvring coefficients. Following this, model-scale resistance simulations in restricted waters are performed to estimate the minimum power needed for propulsion in heavy monsoon currents based on common inland waterway dimensions in Bangladesh. Finally, full-scale simulations are performed in open water to investigate the scale effect on resistance (thus power) prediction. The study confirms that the installed power in the vessel is adequate for safe navigation within Bangladesh’s inland waters. Although model-scale CFD studies are generally unsuitable for resistance prediction, the study suggests that extrapolated results often offer conservative estimates for power prediction. In cases of resource limitation, these simulations can prove beneficial since conservative estimations somewhat ensure the vessel’s propulsion and manoeuvrability in extreme conditions.

Validation of 4DOF maneuvering coefficients optimization using hydrodynamic force and moment estimated from free-running model test results

The present study concerns validation of data-driven modeling for ship dynamics from free-running model test results, in terms of estimation of hydrodynamic force and moment, maneuvering coefficients, and maneuver simulation results. An estimation method for the hydrodynamic force and moment from the acceleration of a surface combatant model ship is suggested and compared with the conventional ship dynamics modeling. The hull dynamics modeling relates the motion and hydrodynamic force and moment is developed by optimizing maneuvering coefficients which leads to minimum loss function of hydrodynamic force and moment and maneuvering criteria. The maneuvering coefficients of the dynamics model is compared with a conventional system-based dynamics model. Lastly, the maneuvering simulation results are compared to the free-running model test results. The suggested model adequately predicts hydrodynamic force and moment in highly coupled sway and yaw motion.

Limit protection systems for safety operational envelope of submarine

To enhance the operational stability of submarines, this study conducts a comparative analysis of three pitch limit protection systems based on the reference model, potential function, and dynamic trim algorithm. The proposed depth limit protection system adjusts the depth command by comparing the desired depth, calculated by the outer-loop controller, against a predefined depth limit. Similarly, the pitch limit protection systems modify the command pitch calculated by the inner-loop controller to ensure it does not exceed the pitch limit. Submarine maneuvering simulations were conducted to verify the performance of the envelope protection system, which comprises depth and pitch limit protection systems. Simulation results confirmed the effectiveness of these methods, with the dynamic trim algorithm demonstrating superior control efficiency. This study advances submarine safety and stability by developing and validating advanced pitch limit protection systems.

Dynamic Oblique Towing Test (DOTT) to calculate the ship's hull maneuvering derivatives

An accurate and time-efficient numerical method is developed to find the hydrodynamic maneuvering derivatives with only a single simulation by computational fluid dynamics. The method is based on the oblique towing test by introducing an oscillatory variation to the model ship drift angle as time progress. The fluid flow velocity and direction are fixed during the simulation but the orientation of the model ship is changing sinusoidally with respect to the fluid flow with a certain amplitude and frequency. The velocity and acceleration of the model ship are calculated using the kinematic relationships and the forces and moment on the model ship are computed in a time period while the model ship drift angle is changing. The method is named dynamic oblique towing test (DOTT) and is applied to a container model ship and a surface combat model. The hydrodynamic maneuvering derivatives are obtained by an optimized curve fitting using Genetic Algorithms. The results of the computation in coefficient derivation and maneuver simulation indicate the accuracy and time efficiency of the method.

Influence of drift angle on the propulsive efficiency of a fully appended container ship (KCS) using Computational Fluid Dynamics

To estimate the powering and manoeuvring performance of the ship in a real seaway, it is essential to accurately determine forces acting on the hull, propeller, rudder and their interaction effects when operating at an angle of drift. The rotating propeller alters the fluid flow around the upstream hull and the downstream rudder. Likewise, when a non-zero drift or rudder angle is applied, significant crossflow is generated across the propeller plane, changing the wakefield and the actual performance of the propeller. A study is conducted to analyse the hull–propeller–rudder interaction of the benchmark KRISO Container Ship (KCS) in calm water using Computational Fluid Dynamics (CFD). The KCS is studied at drift angles of −10°, 0°and ＋10°, combined with a series of rudder angles (−35°to ＋35°), which can represent quasi-static phases of an actual ship manoeuvre. The propeller is modelled using two body force models, Blade Element Momentum Theory and the Yamazaki model. Good agreement is found between experimental and numerical results when predicting hull forces and wave patterns at drift, providing a good reference for experimental measurement of the hull and its appendage forces at drift and future validation of actual dynamic manoeuvring simulations.

Path Planning for Automatic Berthing Using Ship-Maneuvering Simulation-Based Deep Reinforcement Learning

Despite receiving much attention from researchers in the field of naval architecture and marine engineering since the early stages of modern shipbuilding, the berthing phase is still one of the biggest challenges in ship maneuvering due to the potential risks involved. Many algorithms have been proposed to solve this problem. This paper proposes a new approach with a path-planning algorithm for automatic berthing tasks using deep reinforcement learning (RL) based on a maneuvering simulation. Unlike the conventional path-planning algorithm using the control theory or an advanced algorithm using deep learning, a state-of-the-art path-planning algorithm based on reinforcement learning automatically learns, explores, and optimizes the path for berthing performance through trial and error. The results of performing the twin delayed deep deterministic policy gradient (TD3) combined with the maneuvering simulation show that the approach can be used to propose a feasible and safe path for high-performing automatic berthing tasks.