Assessment Overview: You’ll develop a research proposal for applying digital twin technology to the design of an autonomous surface vessel (ASV), drawing from case studies like those in North Sea monitoring or port logistics.

Assessment Overview: You’ll develop a research proposal for applying digital twin technology to the design of an autonomous surface vessel (ASV), drawing from case studies like those in North Sea monitoring or port logistics. This echoes industry-led projects from places like the University of Southampton or Strathclyde, emphasising simulation-driven validation and IMO guidelines on MASS (Maritime Autonomous Surface Ships). It’s a stepping stone to your group design later in the module.

Learning Outcomes Addressed:

1. Evaluate digital twin frameworks for hydrodynamic and control system modelling in naval architecture.
2. Formulate research questions and methodologies for autonomous vehicle integration.
3. Assess ethical, regulatory, and operational challenges in simulated maritime environments.
4. Present a feasible proposal aligned with UK Maritime Autonomous Systems Regulatory Framework.

Task Instructions:

1. Introduction and Rationale (approx. 400 words): Outline the role of digital twins in ASV design (e.g., real-time fault prediction or route optimisation). Identify a specific challenge, such as collision avoidance in congested waters, and justify its relevance for a 500 GT ASV. Reference IMO’s 2025 MASS Code interim guidelines.
2. Literature Review (approx. 500 words): Survey 4-6 sources from 2019-2025 via Google Scholar or IEEE Xplore. Critically appraise applications in ship stability or propulsion control, highlighting gaps like data integration in harsh conditions.
3. Methodology and Feasibility (approx. 400 words): Propose a mixed-methods approach, e.g., MATLAB/Simulink for twin development and CFD for validation. Include timelines, resources (e.g., open-source datasets), and risk mitigation. Discuss alignment with UN SDG 9 (Industry, Innovation and Infrastructure).
4. Expected Outcomes and Impact (approx. 200 words): Predict contributions to safer autonomy and suggest scalability for fleet operations.

Support and Resources:

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We offer urgent delivery starting at 6 hours for focused research papers and 12 hours for complex marine science dissertations or navigation assessments. Our maritime writers maintain academic rigor under tight deadlines—ideal for last-minute research reports or thesis chapters.

• Fortnightly office hours (Wednesdays, 10am-12pm, via Zoom).
• Tools: Access to ANSYS Twin Builder trial and sample ASV models on Moodle.
• Reading pack: “Digital Twins for Maritime Autonomy” curated list. Feel free to bounce ideas off me – these proposals often evolve into standout final projects.

Marking Criteria (out of 100%):

Distinction (70%+) demands proactive insight; pass (40-69%) requires solid basics. Feedback within 20 working days on Moodle, including annotated proposal.

All the best with this – your proposals shape the module’s direction.

Warm regards, Professor Elena Hargrove Module Lead, Department of Naval Architecture & Ocean Engineering

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Every research paper, dissertation, or nautical assessment is crafted from scratch by a subject-matter expert in maritime studies. We use advanced plagiarism tools and provide a free originality report with every research report or navigation thesis, ensuring 100% authentic, publication-ready content.

Suggested References (Harvard Format)

These draw from recent peer-reviewed works on digital twins and autonomous marine systems, sourced via Google Scholar and MDPI/IEEE databases, to underpin your proposal’s literature review.

1. Negreiros, J., Santos, T.A. and Guedes Soares, C. (2023) ‘Digital Twins in the Marine Industry: A Review’, Electronics, 12(9), p. 2025.
2. Raptis, T.P., Faiella, G., Giallanella, L., Kyriakopoulos, G.L. and Kameas, A. (2022) ‘Ship’s Digital Twin—A Review of Modelling Challenges and Applications’, Journal of Marine Science and Engineering, 10(8), p. 1136.
3. Lee, S., Kim, N. and Han, S. (2024) ‘Review Digital twins enable shipbuilding: Applications, challenges, and future directions’, Alexandria Engineering Journal, 89, pp. 1-18.
4. Wang, J., Zhang, H., Liang, Y. and Zhang, Y. (2025) ‘The application and development of digital twin in the marine domain’, Ocean Engineering, 295, p. 116947.
5. Bolbot, V., Theotokatos, G., Bujorianu, L.M., Boulougouris, E. and Vassalos, D. (2020) ‘A novel method to evaluate the safety of autonomous marine systems through digital twin simulation series’, Safety, 6(4), p. 61.