The study of ship motions and stability in waves has long been a cornerstone of naval architecture and ocean engineering. Seakeeping performance and dynamic stability directly affect operational safety, efficiency, and environmental sustainability across a wide range of vessels, including conventional merchant ships, high-speed patrol craft, naval vessels, and offshore floating platforms.
Initially, assessments of stability and safety relied heavily on simplified theoretical frameworks and potential flow analyses, which provided valuable but limited insights into highly nonlinear wave–ship interactions []. While foundational, these early approaches often struggled to capture dynamic phenomena such as parametric rolling, broaching, surf-riding, and capsize in realistic sea states [,]. With advances in computational power, recent decades have witnessed a paradigm shift toward computational fluid dynamics (CFD), enabling high-fidelity simulations of nonlinear seakeeping and dynamic stability phenomena. Unlike linear or weakly nonlinear potential flow methods, CFD allows direct modeling of viscous effects, vortex shedding, green-water impacts, and coupled wind–wave–current interactions. Comparative studies have further clarified the complementary strengths of potential flow and CFD in seakeeping and added resistance analysis, while CFD-modified potential methods have been shown to improve predictive capability without prohibitive cost [,]. These developments have significantly improved the reliability of extreme response predictions and helped bridge the gap between model-scale experiments and full-scale operational conditions.
Nevertheless, challenges remain. CFD simulations are still computationally demanding, particularly when addressing stochastic seas, multi-body interactions, or long-duration time histories. To overcome these limitations, hybrid frameworks that couple the efficiency of potential flow methods with the accuracy of CFD for localized nonlinear phenomena have been actively explored []. At the same time, data-driven strategies leveraging onboard measurements and machine learning are emerging as powerful complements to physics-based simulations, offering promising new tools for predicting wave-induced motions, seakeeping performance, and stability failures in real time [].
The growing use of liquefied natural gas (LNG) and liquid hydrogen as eco-friendly energy carriers, along with rapid advances in autonomous ship operations, has further amplified the demand for accurate assessments of wave-induced motions and stability failures. Environmentally friendly design has also underscored the importance of sustainable approaches in marine engineering []. Against this background, the aim of this Special Issue was to highlight recent advances in dynamic stability and ship safety in waves, spanning fundamental hydrodynamic phenomena, nonlinear instabilities, and engineering applications. Five high-quality contributions were published, each offering new insights into the challenge of ensuring safety in rough seas.
In contribution 1, Heo and Koo investigated optimizing submerged breakwaters to improve the performance of point-absorber wave energy converters using Bragg resonance. Their systematic numerical simulations showed how the configuration and positioning of submerged breakwaters could be adjusted to increase resonance effects and improve energy conversion efficiency. While this contribution was primarily aimed at renewable ocean energy, it also informs broader wave–structure interaction problems relevant to offshore safety and marine operations. The contribution highlights the interdisciplinary nature of marine hydrodynamics, where advances in one area can benefit others.
In contribution 2, Liu and Park explored the influence of wavelength on turbine performance and vortical wake flows at various submersion depths. Through systematic CFD simulations, the study revealed that turbine efficiency and wake dynamics are strongly affected by wavelength conditions and immersion levels. These findings provide valuable design implications for marine energy systems, in which stability, efficiency and wake interactions are critical considerations. This work broadens the scope of the Special Issue by linking ship and offshore hydrodynamics with renewable energy applications.
In contribution 3, Nam et al. examined the seakeeping performance of a barge using a CFD-modified potential (CMP) model. By combining the potential flow method with CFD-based corrections, the authors sought to balance computational efficiency and accuracy. Numerical simulations showed improved agreement with experimental data compared to conventional potential models, particularly with regard to predicting nonlinear wave loads and motions. This hybrid CMP approach demonstrates the potential for improving the practicality of seakeeping predictions for engineering applications.
Contribution 4, presented by Zeng et al., provided a comparative evaluation of CFD and potential flow methods for analyzing pure stability loss in following waves. The Office of Naval Research (ONR) tumblehome ship was used as a case study. The CFD approach incorporated rudders and propellers using overlapping grids, providing a more realistic representation of nonlinear flow interactions. In contrast, the potential flow method was based on advanced strip theory. The results showed that the CFD approach captured the mechanisms of instability and capsize trends more accurately, while the potential flow method offered computational efficiency, but was limited in nonlinear regimes. This study provides valuable insights for the International Maritime Organization’s (IMO) next-generation intact stability criteria, which emphasize direct assessment.
Finally, contribution 5 by Park et al. presents a rigorous investigation into the low-frequency pitch motion characteristics of the Korea Research Institute of Ships and Ocean Engineering (KRISO) standard offshore structure (K-Semi) moored with a truncated mooring system. A 1/50 scale model was used in free-decay, regular-wave and irregular-wave experiments, complemented by numerical simulations to capture nonlinear pitch–surge coupling. The findings revealed that truncated mooring arrangements can induce excessive low-frequency pitch motions due to second-order effects, with significant implications for experimental modeling in limited basin depths. This contribution highlights the importance of properly accounting for mooring truncation in physical and numerical studies of semi-submersible stability.
Taken together, the five contributions to this Special Issue advance our understanding of ship dynamics, nonlinear instabilities, and hydrodynamic safety in waves. They highlight the importance of integrating experiments, CFD, potential flow models, and optimization strategies to address real-world challenges. Recent developments in intact stability assessment [] and perspectives on the future of ship stability [] illustrate the ongoing evolution of safety criteria. In parallel, comparative studies between potential flow and CFD methods have highlighted their complementary strengths, while CFD-modified potential simulations and hybrid numerical frameworks have been proposed to overcome computational limitations and better capture nonlinear phenomena [,,]. Hybrid modelling strategies for motion prediction [] and seakeeping risk evaluation [] provide additional evidence of progress in this field. Looking ahead, emerging approaches such as data-driven prediction and machine learning are expected to play an increasingly important role. Recent studies have demonstrated the potential of machine learning not only for predicting ship motions [,], but also for evaluating seakeeping performance [] and assessing stability failure probabilities []. Moreover, hybrid approaches that combine physics-based models with machine learning corrections are gaining momentum, showing promise for enhancing the robustness and generalizability of motion prediction frameworks [,]. Together, these developments underscore the growing importance of integrating computational hydrodynamics with data-driven insights to ensure reliable, efficient, and forward-looking evaluations of ship safety.
Funding
This study was supported by research fund from Chosun University, 2023.
Acknowledgments
The Guest Editors wish to thank all the authors for their valuable contributions and the reviewers for their constructive comments, which ensured the scientific quality of this Special Issue. Special appreciation is extended to the JMSE editorial staff for their continuous support throughout the editorial process.
Conflicts of Interest
The authors declare no conflicts of interest.
List of Contributions
- Heo, S.; Koo, W. Optimization of Submerged Breakwaters for Maximum Power of a Point-Absorber Wave Energy Converter Using Bragg Resonance. J. Mar. Sci. Eng. 2024, 12, 1107. https://doi.org/10.3390/jmse12071107.
- Liu, B.; Park, S. Effect of Wavelength on Turbine Performances and Vortical Wake Flows for Various Submersion Depths. J. Mar. Sci. Eng. 2024, 12, 560. https://doi.org/10.3390/jmse12040560.
- Nam, S.; Park, J.-C.; Park, J.-B.; Yoon, H.K. Numerical Simulation of Seakeeping Performance of a Barge Using Computational Fluid Dynamics (CFD)-Modified Potential (CMP) Model. J. Mar. Sci. Eng. 2024, 12, 369. https://doi.org/10.3390/jmse12030369.
- Zeng, K.; Lu, J.; Gu, M.; Yang, C. A Comparative Analysis of CFD and the Potential Flow Method for the Pure Loss of Stability in Following Waves. J. Mar. Sci. Eng. 2023, 11, 2135. https://doi.org/10.3390/jmse11112135.
- Park, B.; Jung, S.; Seo, M.-G.; Kim, J.; Sung, H.G.; Park, J.-C. Investigation of Low-Frequency Pitch Motion Characteristics for KRISO Standard Offshore Structure (K-Semi) Moored with a Truncation Mooring System. J. Mar. Sci. Eng. 2023, 11, 1842. https://doi.org/10.3390/jmse11101842.
References
- Faltinsen, O.M. Sea Loads on Ships and Offshore Structures; Cambridge University Press: Cambridge, UK, 1990. [Google Scholar]
- Spyrou, K.J. Dynamic instability in quartering seas: The behavior of a ship during broaching. J. Ship Res. 1996, 40, 46–59. [Google Scholar] [CrossRef]
- Francescutto, A. Intact stability criteria of ships—Past, present and future. Ocean Eng. 2016, 120, 312–317. [Google Scholar] [CrossRef]
- Sulovsky, I.; de Hauteclocque, G.; Greco, M.; Prpić-Oršić, J. Comparative Study of Potential Flow and CFD in the Assessment of Seakeeping and Added Resistance of Ships. J. Mar. Sci. Eng. 2023, 11, 641. [Google Scholar] [CrossRef]
- Nam, S.; Park, J.-C.; Park, J.-B.; Yoon, H.K. CFD-Modified Potential Simulation on Seakeeping Performance of a Barge. Water 2022, 14, 3271. [Google Scholar] [CrossRef]
- Yu, Z.; Kim, J.; Zhang, C. A Hybrid Numerical Framework of Potential and Viscous Simulations for a Free-Running Surface Ship in Waves. Ocean Eng. 2024, 283, 115229. [Google Scholar] [CrossRef]
- Zhang, D.; Li, H.; Wang, Y.; Zhou, X.; Xie, S.; Peng, Y. A Data-Driven Method for Multi-Step Prediction of Ship Roll Motion in High Sea States. Ocean Eng. 2023, 276, 114230. [Google Scholar] [CrossRef]
- Jeong, S.-M.; Son, B.-H.; Lee, C.-Y. Estimation of the Motion Performance of a Light Buoy Adopting Ecofriendly and Lightweight Materials in Waves. J. Mar. Sci. Eng. 2020, 8, 139. [Google Scholar] [CrossRef]
- Petacco, N.; Campanile, A.; Gualeni, P.; Piscopo, V. Evaluation by a Quantitative Index about Intact Stability in Waves. J. Mar. Sci. Eng. 2023, 11, 814. [Google Scholar] [CrossRef]
- Angelou, M.; Hirdaris, S.; Bačkalov, I.; Themelis, N. Future of ship stability. In Proceedings of the 2nd International Conference on the Stability and Safety of Ships and Ocean Vehicles, Wuxi, China, 13–18 October 2024. [Google Scholar]
- Zhang, Z.; Jiang, X. A rapid motion predicting strategy for ships in waves using seakeeping and maneuvering modules. SSRN Electron. J. 2023. [Google Scholar] [CrossRef]
- Jiang, C.; El Moctar, O.; Zhang, G. Seakeeping criteria of a moored and articulated multibody floating platform in head seas. Front. Mar. Sci. 2023, 10, 1138235. [Google Scholar] [CrossRef]
- Ahn, Y.; Lee, J.-H.; Kim, Y. Application of Machine Learning for Prediction of Wave-Induced Ship Motion. In Proceedings of the ISOPE International Ocean and Polar Engineering Conference (ISOPE), Shanghai, China, 5–10 June 2022; p. ISOPE–I-22-270. [Google Scholar] [CrossRef]
- Romero-Tello, P.; Gutiérrez-Romero, J.E.; Serván-Camas, B. Predicting seakeeping of conventional monohull vessels with forward speed using artificial neural networks. J. Ocean Eng. Mar. Energy 2025, 11, 701–732. [Google Scholar] [CrossRef]
- Jiang, C.; Xiang, X.; Xiang, G. A joint multi-model machine learning prediction approach based on confidence for ship stability. Complex Intell. Syst. 2024, 10, 3873–3890. [Google Scholar] [CrossRef]
- Marlantes, K.E.; Maki, K.J. A hybrid data-driven model of ship roll. Ocean Eng. 2024, 303, 117821. [Google Scholar] [CrossRef]
- Marlantes, K.E.; Bandyk, P.J.; Maki, K.J. Predicting ship responses in different seaways using a generalizable force correcting machine learning method. Ocean Eng. 2024, 312, 119110. [Google Scholar] [CrossRef]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).