Ship handling simulators are used for training and for verifying port operational limits by recreating maneuvering environments using actual bridge equipment and visual systems. They support critical decisions required for safe navigation, such as whether a new large vessel can safely enter a port or what wind speeds and wave heights should be set as operational limits.
At the core of these simulators lies the ship motion model, which describes vessel behavior using mathematical equations. Jinpei Kato, General Manager of the Simulator Technical Division at MOL Maritex Co.,Ltd., has been involved in the development of ship handling simulators and ship motion models for nearly 20 years. We spoke with Mr. Kato about ship motion modeling technology and how it is applied in practice.
Kato:
A ship handling simulator recreates a vessel’s bridge using real hardware, with surrounding screens that virtually reproduce the maneuvering environment. For example, in our simulator room in Tokyo, visual scenes are projected onto large cylindrical wall screens and a floor screen using multiple projectors. When standing within the immersive visuals, it truly feels as if you are on an actual ship’s bridge.
(Source: MOL Maritex Co., Ltd.)
As for hardware, the simulator is equipped with real‑equivalent equipment such as steering systems, engine telegraphs, radar, ECDIS (Electronic Chart Display and Information System), communication devices, and various navigational instruments. Combined with software that recreates environmental conditions—wind, waves, currents, visibility, and surrounding vessels—and a ship motion model that calculates how the ship responds to these forces, they form a complete simulator system.
From left to right: steering stand, radar, and ECDIS. Ship handling environment using real‑equivalent navigational equipment
(Source: MOL Maritex Co., Ltd.)
Kato:
The primary users are captains and navigation officers from the MOL Group. Before boarding an actual vessel, the team—including the captain—undertakes training together, primarily through BRM (Bridge Resource Management), which focuses on team-based decision-making and coordination.
In this context, the simulator is often used less as a place to refine precise ship‑handling techniques and more as a realistic bridge environment serving as a stage for team operations.
(Source: MOL Maritex Co., Ltd.)
Ship handling simulators are also used in maritime consulting services. Maritime consulting involves the technical evaluation and assessment of port and route safety. For example, to determine whether a large vessel can safely enter a newly developed port, simulations are conducted under recreated conditions based on on‑site surveys. The results are used in safety review committees to discuss and determine operational criteria —such as maximum allowable wind speeds and wave heights— based on objective evidence.
Kato:
This is a point that is often misunderstood. What is required in maritime consulting is not perfect replication of reality but rather providing a sound basis for informed decision‑making. Our role is to ensure the quality needed to support such decisions.
There is a phrase I once heard from a professor during a committee discussion that resonated deeply with me:
“The ship in a simulator is a replica. But it is an evidence‑based replica.”
Perfectly reproducing reality is something no one can do, at least not at present. Consider a harbor maneuvering scenario: a vessel entering at six knots, receiving winds of 12 meters per second from the forward quarter, one‑meter waves approaching at an offset angle, an opposing current, tugboats pulling astern, the rudder applied while the engine is stopped. There is almost no systematically usable real‑world data that captures exactly how a ship behaves under such complex combined conditions.
Some discrepancy between simulation and reality is inevitable. What matters is clearly identifying what evidence is used in the simulation and creating a shared foundation for discussion. The key technology that enables this is ship motion modeling.
A video introducing the ship handling simulator developed by MOL Maritex Co., Ltd. (Source: MOL official YouTube channel)
Kato:
In simple terms, it is a technology that describes how a ship moves using mathematical equations. Forces generated by the vessel itself include propeller thrust, lateral forces caused by water flow acting on the rudder, and forces from thrusters used for lateral movement. By contrast, the ship is also subject to external forces such as wind, waves, currents, increased resistance in shallow water (shallow-water effects), as well as pushing or pulling forces from tugboats. While aircraft are affected by wind, ships are submerged in water, which significantly increases the number of variables that must be considered.
(Source: MOL Maritex Co., Ltd.)
The fundamental principle of a ship motion model lies in combining all these forces and solving the equations of motion to calculate vessel behavior, including acceleration, deceleration, turning, drifting, and stopping. The mathematical structure of these equations is well established. What truly matters is how the coefficients used in the equations are determined.
Kato:
Deriving coefficients specific to an individual vessel requires extensive investigation. At shipyard research centers, scale models may be tested in towing tanks using sensors to determine vessel‑specific coefficients. However, this process is costly and can take more than six months, making it impractical for each consulting project.
In practice, we rely on coefficients that have been socially authorized through past research and academic papers. There are established reference ranges indicating what values are appropriate for a given ship type and size. Before proceeding, the committee agrees in advance on which coefficients will be used, ensuring that sources—such as specific academic papers—can be clearly cited when questions arise.
However, selecting the references does not mean the process ends there. Adjusting those coefficients to better reflect the actual vessel, within feasible limits, is the core of this work.
Kato:
A good analogy is a Rubik’s Cube. When you try to align one face, another that was previously aligned often falls apart. The same thing frequently happens during coefficient tuning.
For example, in theory, it is generally understood that “a vessel with a small turning radius tends to have difficulty stopping its turning motion, whereas a vessel with a large turning radius tends to stop turning more easily.” In practice, however, there are many cases where actual vessel behavior does not follow these simple calculations—for instance, a vessel may be highly maneuverable yet its turning motion may stop quickly.
When we attempt to reproduce such behavior by adjusting coefficients, new issues arise.
Rudder-related coefficients are largely fixed and difficult to change, while modifying hull moment coefficients can disrupt the reproduction of turning performance. In this way, correcting one aspect often throws another out of balance. We address these discrepancies one by one, patiently fine-tuning the model.
(AI‑generated image)
Matching the model with sea trial results is also far from straightforward. Because sea trials are conducted under actual sea conditions, the compiled results, although corrected, reflect a combination of wind, waves, and currents. In contrast, model verification is carried out under completely calm conditions, with no wind or waves.
In addition, loading conditions during trials often differ from those during actual operation, making it unrealistic to expect the two to match perfectly. Determining how closely they should be aligned, and making that judgment, is itself one of the skills required in this work.
Kato:
One major challenge is the limited availability of reference data. Ship motion models are particularly critical during harbor maneuvering, such as berthing and unberthing operations involving tugboats. Compared with open-sea navigation, technological progress in this area has been very slow, and the accumulation of data has also been limited.
Research into ship behavior in open waters has advanced steadily, largely because it is closely linked to the development of energy-saving technologies and therefore has strong demand. By contrast, harbor maneuvering has not benefited from the same momentum.
For example, when it comes to resistance characteristics in shallow water—where vessel motion becomes more sluggish as water depth decreases—the industry still widely relies on test results from a tanker named ESSO OSAKA, conducted in the Gulf of Mexico in the 1970s. Since then, there have been almost no systematically planned experiments using full-scale vessels. Although the data was collected at a time when measurement technologies were far less advanced than they are today, full-scale empirical data remains so rare and difficult to obtain that it continues to be used as a reference across the industry.
(Source: Mitsui O.S.K. Lines)
Kato:
We are exploring the use of AI, but a common misunderstanding is the expectation that simply applying AI will suddenly make simulators more realistic. In reality, the data AI can draw on are the same limited body of academic papers and sea trial results that we rely on. What we expect from AI is not a dramatic leap in realism, but improvements in how evidence can be explained and reused. For example, it could help visualize why certain coefficients were selected, clearly showing which studies were referenced, making workflows more efficient and making it easier to compare new models with those developed in the past.
Rather than harbor maneuvering models rapidly becoming much closer to reality, I believe what truly matters in this field is steadily enhancing the reliability and efficiency of the model development process itself, step by step.
Kato:
Solving the puzzle is always enjoyable. But what is especially rewarding is when a simulation we contributed to helps a consulting committee conclude that “these conditions are acceptable,” and that conclusion leads to real-world safe operations.
Seeing news that an actual vessel has entered a port we evaluated is truly gratifying. Even though the ship in the simulator is virtual, its results can open real sea routes. That is where I find the true significance of this work.
(Source: MOL Maritex Co., Ltd.)
MOL Maritex Co., Ltd. was established on 1 April 2025, following the integration of three MOL Group companies: MOL Marine & Engineering Co., Ltd., MOL Ocean Expert Co., Ltd., and MOL Ship Tech Inc. This newly formed entity brings together a wealth of expertise in maritime technology, positioning itself as a specialized group of professionals dedicated to advancements in the industry. The name “Maritex” reflects the fusion of Marine and Technology, while also embodying the pride and ambition of Experts committed to shaping the future. The “X” in Maritex symbolizes both the synergy of the three companies and the spirit of exploration into the unknown.
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