Ship performance evaluation is an essential procedure for verifying compliance with the shipowner’s requirements and enhancing operational safety and efficiency. Sea trials are generally conducted to evaluate ship performance, such as resistance, FOC (Fuel Oil Consumption), and maneuvering performance, in a real-world marine environment. However, conducting sea trials for repeated verification is often impractical due to substantial costs, time constraints, and weather limitations that hinder consistent data collection. These limitations make it difficult to repeatedly evaluate ship performance under various sea states. Accordingly, an alternative method for consistently evaluating ship performance without relying on sea trials is required.
This study proposed a method for the virtual modeling and performance prediction of a ship to replace sea trials. The proposed method consists of three main parts: modeling a virtual ship, implementing a virtual marine environment, and predicting ship performance through virtual sea trials. These parts were designed to enable ship performance to be predicted under controlled, repeatable conditions. First, the virtual ship was modeled by integrating hardware systems and software modules. These systems and modules emulate the major elements of a real ship, such as the power and propulsion systems, the control system, and the sensor system. In particular, the virtual ship emulates hardware systems, such as the engine dynamics of the power and propulsion systems. It also calculates ship maneuvering motion using the MMG (Maneuvering Modeling Group) model. By reflecting the characteristics of the hardware systems and software modules, the virtual ship can predict ship performance based on the configurations of the major elements. Second, the virtual marine environment was implemented to reproduce the characteristics of a real-world marine environment. It incorporates environmental loads induced by various marine conditions, such as currents, winds, and waves. This allows the virtual ship to exhibit the responses of a real ship under various sea states. Finally, virtual sea trials were conducted following the standard procedures, including speed-power and turning tests. Through the virtual sea trials, the proposed method predicts ship performance such as resistance, FOC, and maneuvering performance according to the sea state. This prediction follows ISO 15016, the international guideline for analyzing the speed and power performance of a ship based on sea trial data.
To validate the proposed method, virtual sea trials were conducted in the virtual marine environment under various sea states, with the virtual ship operating along a predefined route. From these virtual sea trials, the results of the speed-power and turning tests were obtained. The results showed that the proposed method effectively predicts ship performance based on sea state. In addition, the effect of the configurations of the major elements on ship performance was analyzed by comparing different configurations under the same sea states. Consequently, the predicted ship performance varied across configurations of the major elements. This result indicated that the proposed method can reflect the influence of the configurations of the major elements on ship performance through virtual sea trials. Therefore, the proposed method can significantly reduce reliance on costly and time-consuming sea trials.
In conclusion, this study proposed a method for the virtual modeling and performance prediction of a ship to replace sea trials. The results of the virtual sea trials showed that the proposed method effectively predicts ship performance under various sea states and reflects the influence of the configurations of the major elements. Therefore, the proposed method provides a reliable, repeatable, and scalable means of predicting ship performance in a virtual marine environment. Future work will focus on improving the modeling method using ship operational data and on extending the proposed method to various operation scenarios.