Special Issue "New Insights into Safety of Ships and Offshore Structures"

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Coastal Engineering".

Deadline for manuscript submissions: 1 February 2024 | Viewed by 916

Special Issue Editors

School of Navigation, Wuhan University of Technology, Wuhan, China
Interests: autonomous ships; formation control; cooperative waterborne transport systems; coordinated scheduling; multi-agent systems
SINTEF Ocean AS, Department of Ships and Ocean Structures, SINTEF Ocean, Postboks 4762 Torgard, N-7465 Trondheim, Norway
Interests: hydrodynamics; stability; seakeeping; dynamics of offshore structures; offshore renewable energy; potential flow
Special Issues, Collections and Topics in MDPI journals
Ocean College, Zhejiang University, Hangzhou, China
Interests: model predictive control; ocean robotics; distributed control and coordination with applications to waterborne networked systems
Special Issues, Collections and Topics in MDPI journals
Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, The Netherlands
Interests: AIS data analysis; ship behavior recognition; maritime traffic modeling; collision avoidance behavior of ships; maritime traffic organization in ports and waterways

Special Issue Information

Dear Colleagues,

The safety of ships and offshore structures is the most interesting and important aspect. Recently, new techniques, such as machine learning, artificial intelligence, and metaverse systems (e.g., digital twins, ICT, and IoT), have been applied to improve the safety of ships and offshore structures. The utilization of new techniques also introduces new challenges. For example, the shore-based control of a ship contains new safety aspects, and an interesting question will be the interaction of manned and unmanned ships in the same traffic area. Thus, new insights into the safety of ships and offshore structures are needed.

This Special Issue covers both ships and offshore structures (floating and fixed offshore platforms, offshore infrastructure, and subsea facilities) with a strong emphasis on the application of new techniques and their impacts on safety. High-quality papers directly related to various aspects, including but not limited to the following, are encouraged for publication:

  • Safety of ships
    • Stability and structural safety of ships;
    • Situation awareness, path planning, and collision avoidance;
    • Autonomous ships;
    • Risk assessment for shipping accidents;
    • Cyber security challenges for ships.
  • Safety of offshore structures
    • Hydrodynamic analysis of offshore structures;
    • Structural design and analysis of offshore structures;
    • Risk- and reliability-based approaches applied to offshore structures;
    • Safety management of offshore structures;
    • Fatigue.
  • Interactions between ships and offshore structures
    • Transportation and installation analysis of offshore structures;
    • Ship–structure collisions;
    • Task allocation, scheduling, and operation of offshore support vessels.

Dr. Linying Chen
Dr. José Miguel Rodrigues
Dr. Huarong Zheng
Dr. Yang Zhou
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • safety analysis
  • risk assessment
  • maritime safety
  • autonomous ships
  • offshore structures
  • structural safety and reliability
  • cyber security

Published Papers (1 paper)

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Ship Trajectory Prediction: An Integrated Approach Using ConvLSTM-Based Sequence-to-Sequence Model
J. Mar. Sci. Eng. 2023, 11(8), 1484; https://doi.org/10.3390/jmse11081484 - 25 Jul 2023
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Maritime transportation is one of the major contributors to the development of the global economy. To ensure its safety and reduce the occurrence of a maritime accident, intelligent maritime monitoring and ship behavior identification have been drawing much attention from industry and academia, [...] Read more.
Maritime transportation is one of the major contributors to the development of the global economy. To ensure its safety and reduce the occurrence of a maritime accident, intelligent maritime monitoring and ship behavior identification have been drawing much attention from industry and academia, among which, the accurate prediction of ship trajectory is one of the key questions. This paper proposed a trajectory prediction model integrating the Convolutional LSTM (ConvLSTM) and Sequence to Sequence (Seq2Seq) models to facilitate simultaneous extraction of temporal and spatial features of ship trajectories, thereby enhancing the accuracy of prediction. Firstly, the trajectories are preprocessed using kinematic-based anomaly removal and Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) to improve the data quality for the training process of trajectory prediction. Secondly, the ConvLSTM-based Seq2seq model is designed to extract temporal and spatial features of the ship trajectory and improve the performance of long-time prediction. Finally, by using real AIS data, the proposed model is compared with the Seq2Seq and Bidirectional LSTM based on attention mechanism (Bi-Attention-LSTM) models to verify its effectiveness. The experimental results demonstrate that the proposed model achieves excellent performance in predicting turning trajectories, good predictive accuracy on straight line motions, and greater improvement in prediction accuracy compared to the other two benchmark models. Overall, the proposed model represents a promising contribution to improving ship trajectory prediction accuracy and may enhance the safety and quality of ship navigation in complex and volatile marine environments. Full article
(This article belongs to the Special Issue New Insights into Safety of Ships and Offshore Structures)
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