Risk Assessment and Prediction of Marine Equipment

Dear Colleagues,

As marine exploration, offshore energy development, and maritime transportation surge globally, marine equipment—from deep-sea drilling rigs to autonomous underwater vehicles—faces unprecedented challenges. Harsh conditions like corrosive seawater, extreme storms, and subsea geological instability escalate failure risks, leading to catastrophic economic losses, environmental spills, and threats to human life. Recent high-profile incidents, such as offshore platform collapses and subsea pipeline leaks, underscore the critical need for advanced risk assessment and prediction tools to safeguard operations and sustain ocean development.​

This Special Issue aims to unite global experts to talk about marine equipment risk assessment and prediction. We focus on risk identification, predictive modeling, and mitigation strategies across all marine assets: offshore structures, renewable energy devices, naval vessels, and monitoring systems. Topics span corrosion, structural fatigue, cyber threats, and climate-driven risks, and we welcome interdisciplinary approaches that bridge engineering, data science, and marine ecology.​

The field has evolved dramatically, from mid-20th-century qualitative risk checklists for early offshore projects to 21st-century digital transformation. The 1980s introduced quantitative risk assessment; the 2000s integrated sensor networks; today, AI and digital twins revolutionize predictive capabilities. Each of these breakthroughs were driven by pioneering research; your work could be part of taking the next leap.​

New innovations and advances are reshaping the landscape of the risk assessment and prediction field: artificial intelligence and machine learning models now predict equipment degradation with a good accuracy using real-time sensor data; digital twins simulate decades of wear in virtual environments; and Internet of Things-enabled systems enable predictive maintenance, slashing downtime. Resilience engineering and corrosion-resistant smart materials further push boundaries, offering new ways to mitigate risks in a changing climate.​

We seek the submission of original research papers, comprehensive reviews, and practical case studies that drive progress in marine equipment risk assessment and prediction. This includes studies focused on innovative artificial intelligence and machine learning algorithms for failure mode forecasting, development and validation of digital twin frameworks for risk simulation, strategies to integrate Internet of Things sensor data into real-time risk assessment models, and applications of resilience engineering in enhancing equipment durability. We also welcome the submission of research focused on corrosion-resistant material performance evaluation under marine conditions, quantitative analysis of climate change impacts on equipment risk, and effective risk mitigation strategies tailored to specific marine equipment and operational scenarios. Join us to showcase your breakthroughs, whether novel risk algorithms, digital twin applications, or real-world case studies. Your research will reach leading engineers, policymakers, and industry leaders, driving tangible change in marine safety. Submit your work to be part of the solution!

Dr. Xiaoming Huang
Guest Editor

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.

• risk assessment
• risk prediction
• marine equipment
• artificial intelligence
• sensor
• digital twin