IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i8p3654-d1637312.html
   My bibliography  Save this article

Artificial Intelligence as Enabler for Adoption of Sustainable Nuclear-Powered Maritime Ships: Challenges and Opportunities

Author

Listed:
  • Miltiadis Alamaniotis

    (Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX 78249, USA)

  • Konstantinos Ipiotis

    (SWECO UK Limited, Leeds LS7 4DN, UK)

Abstract

Decarbonization stands as one of humanity’s most pressing challenges, demanding collective efforts from multiple sectors to meet established goals. The transportation industry plays a pivotal role in this endeavor, with the maritime sector offering significant potential to reduce emissions. As a cornerstone of global goods and commodity transport, the maritime industry is uniquely positioned to contribute meaningfully to the global drive for lower carbon emissions. Artificial intelligence (AI), with its profound influence across diverse domains, is anticipated to play a vital role in supporting the nuclear shipping industry on its path to a decarbonized future. Specifically, AI provides tools to make nuclear power on ships a more economically viable solution while enhancing the safety and security of nuclear systems. This paper explores AI tools as an enabler for adopting nuclear-powered ships, delving into the challenges and opportunities associated with their implementation. Ultimately, it highlights AI’s role in fostering sustainable nuclear-powered maritime solutions, which align with and contribute to achieving global decarbonization goals.

Suggested Citation

  • Miltiadis Alamaniotis & Konstantinos Ipiotis, 2025. "Artificial Intelligence as Enabler for Adoption of Sustainable Nuclear-Powered Maritime Ships: Challenges and Opportunities," Sustainability, MDPI, vol. 17(8), pages 1-21, April.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:8:p:3654-:d:1637312
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/8/3654/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/8/3654/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Juhyang Lee & Jeongon Eom & Jumi Park & Jisung Jo & Sewon Kim, 2024. "The Development of a Machine Learning-Based Carbon Emission Prediction Method for a Multi-Fuel-Propelled Smart Ship by Using Onboard Measurement Data," Sustainability, MDPI, vol. 16(6), pages 1-22, March.
    2. Wenshuo Tang & Darius Roman & Ross Dickie & Valentin Robu & David Flynn, 2020. "Prognostics and Health Management for the Optimization of Marine Hybrid Energy Systems," Energies, MDPI, vol. 13(18), pages 1-29, September.
    3. Li, Huanhuan & Yang, Zaili, 2023. "Towards safe navigation environment: The imminent role of spatio-temporal pattern mining in maritime piracy incidents analysis," Reliability Engineering and System Safety, Elsevier, vol. 238(C).
    4. Qiuwen Wang & Hu Zhang & Puxin Zhu, 2023. "Using Nuclear Energy for Maritime Decarbonization and Related Environmental Challenges: Existing Regulatory Shortcomings and Improvements," IJERPH, MDPI, vol. 20(4), pages 1-23, February.
    5. Athanasios Ioannis Arvanitidis & Vivek Agarwal & Miltiadis Alamaniotis, 2023. "Nuclear-Driven Integrated Energy Systems: A State-of-the-Art Review," Energies, MDPI, vol. 16(11), pages 1-23, May.
    6. Ben Qi & Jingang Liang & Jiejuan Tong, 2023. "Fault Diagnosis Techniques for Nuclear Power Plants: A Review from the Artificial Intelligence Perspective," Energies, MDPI, vol. 16(4), pages 1-27, February.
    7. Jun Jian & Zheng Sun & Kai Sun, 2024. "An Intelligent Automatic Sea Forecasting System Targeting Specific Areas on Sailing Routes," Sustainability, MDPI, vol. 16(3), pages 1-20, January.
    8. Hossam A. Gabbar & Md. Ibrahim Adham & Muhammad R. Abdussami, 2021. "Optimal Planning of Integrated Nuclear-Renewable Energy System for Marine Ships Using Artificial Intelligence Algorithm," Energies, MDPI, vol. 14(11), pages 1-39, May.
    9. Yi Zhang & Dapeng Zhang & Haoyu Jiang, 2023. "A Review of Artificial Intelligence-Based Optimization Applications in Traditional Active Maritime Collision Avoidance," Sustainability, MDPI, vol. 15(18), pages 1-20, September.
    10. Athanasios Ioannis Arvanitidis & Miltiadis Alamaniotis, 2024. "Integrating an Ensemble Reward System into an Off-Policy Reinforcement Learning Algorithm for the Economic Dispatch of Small Modular Reactor-Based Energy Systems," Energies, MDPI, vol. 17(9), pages 1-21, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Riasad Amin & Deepika Mathur & David Ompong & Kerstin K. Zander, 2024. "Integrating Social Aspects into Energy System Modelling Through the Lens of Public Perspectives: A Review," Energies, MDPI, vol. 17(23), pages 1-33, November.
    2. Hui Xiang & Xiaolei Li & Xiao Liao & Wei Cui & Fengkai Liu & Donghe Li, 2025. "Artificial Intelligence in Renewable Energy Systems: Applications and Security Challenges," Energies, MDPI, vol. 18(8), pages 1-24, April.
    3. Bruce Stephen, 2022. "Machine Learning Applications in Power System Condition Monitoring," Energies, MDPI, vol. 15(5), pages 1-2, March.
    4. Seyedeh Azadeh Alavi-Borazjani & Shahzada Adeel & Valentina Chkoniya, 2025. "Hydrogen as a Sustainable Fuel: Transforming Maritime Logistics," Energies, MDPI, vol. 18(5), pages 1-36, March.
    5. Pablo Fernández-Arias & Diego Vergara & Álvaro Antón-Sancho, 2023. "Bibliometric Review and Technical Summary of PWR Small Modular Reactors," Energies, MDPI, vol. 16(13), pages 1-15, July.
    6. Tsoumpris, Charalampos & Theotokatos, Gerasimos, 2023. "A decision-making approach for the health-aware energy management of ship hybrid power plants," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    7. Chenyang Lai & Ibrahim Ahmed & Enrico Zio & Wei Li & Yiwang Zhang & Wenqing Yao & Juan Chen, 2024. "A Multistage Physics-Informed Neural Network for Fault Detection in Regulating Valves of Nuclear Power Plants," Energies, MDPI, vol. 17(11), pages 1-23, May.
    8. Lefeng Cheng & Mengya Zhang & Pengrong Huang & Wentian Lu, 2024. "Game-Theoretic Approaches for Power-Generation Companies’ Decision-Making in the Emerging Green Certificate Market," Sustainability, MDPI, vol. 17(1), pages 1-53, December.
    9. Dong-Ping Song, 2024. "A Literature Review of Seaport Decarbonisation: Solution Measures and Roadmap to Net Zero," Sustainability, MDPI, vol. 16(4), pages 1-32, February.
    10. Saurabh Saxena & Darius Roman & Valentin Robu & David Flynn & Michael Pecht, 2021. "Battery Stress Factor Ranking for Accelerated Degradation Test Planning Using Machine Learning," Energies, MDPI, vol. 14(3), pages 1-17, January.
    11. Seyed Majid Bigonah Ghalehsari & Jiaming Wang & Tianyi Zhao, 2025. "A Review of the Evaluation, Simulation, and Control of the Air Conditioning System in a Nuclear Power Plant," Energies, MDPI, vol. 18(7), pages 1-15, March.
    12. Huseyin Emre Sahin & Harun Kemal Ozturk, 2025. "A Novel Model for U-Tube Steam Generators for Pressurized Water Reactors," Energies, MDPI, vol. 18(6), pages 1-19, March.
    13. Zhou, Kaiwen & Xing, Wenbin & Wang, Jingbo & Li, Huanhuan & Yang, Zaili, 2024. "A data-driven risk model for maritime casualty analysis: A global perspective," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    14. Xingyu Xiao & Jingang Liang & Jiejuan Tong & Haitao Wang, 2024. "Emergency Decision Support Techniques for Nuclear Power Plants: Current State, Challenges, and Future Trends," Energies, MDPI, vol. 17(10), pages 1-35, May.
    15. Ramazan Ozkan Yildiz & Elif Koc & Oguzhan Der & Murat Aymelek, 2024. "Unveiling the Contemporary Research Direction and Current Business Management Strategies for Port Decarbonization Through a Systematic Review," Sustainability, MDPI, vol. 16(24), pages 1-38, December.
    16. Liang, Maohan & Li, Huanhuan & Liu, Ryan Wen & Lam, Jasmine Siu Lee & Yang, Zaili, 2024. "PiracyAnalyzer: Spatial temporal patterns analysis of global piracy incidents," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    17. Zhang, Qian & Qi, Jingwen & Zhen, Lu, 2023. "Optimization of integrated energy system considering multi-energy collaboration in carbon-free hydrogen port," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 180(C).
    18. Yordan Garbatov & Petar Georgiev, 2024. "Advances in the Prevention of Shipping-Related Air Pollution," Energies, MDPI, vol. 17(23), pages 1-21, November.
    19. Zhiqiang Peng & Jichong Lei & Zining Ni & Tao Yu & Jinsen Xie & Jun Hong & Hong Hu, 2024. "Research on Data-Driven Methods for Solving High-Dimensional Neutron Transport Equations," Energies, MDPI, vol. 17(16), pages 1-11, August.
    20. Xingyu Xiao & Ben Qi & Jingang Liang & Jiejuan Tong & Qing Deng & Peng Chen, 2023. "Enhancing LOCA Breach Size Diagnosis with Fundamental Deep Learning Models and Optimized Dataset Construction," Energies, MDPI, vol. 17(1), pages 1-20, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:17:y:2025:i:8:p:3654-:d:1637312. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.