Large high-speed electric catamaran hull optimisation using Artificial Intelligence and Computational Fluid Dynamics

About the research project

Electric catamarans represent a critical pathway toward zero-emission maritime transport, particularly for high-speed passenger vessels. However, their operational range is fundamentally constrained by onboard battery capacity, making hydrodynamic efficiency a key limiting factor. This project aims to address this challenge by developing advanced methods to minimise hull resistance through the integration of Computational Fluid Dynamics (CFD) and Artificial Intelligence (AI), enabling more efficient and practical electric vessel designs.

The research will focus on creating a coupled CFD-AI optimisation framework for catamaran hull design. Existing experimental data from a 2.5 m model-scale catamaran will be used alongside full-scale sea trials shaft power data to determine resistance characteristics across scales. These datasets will inform and train Physics-Informed AI models within Simcenter STAR-CCM+, enabling improved prediction of hydrodynamic performance while maintaining physical consistency. High-fidelity CFD simulations will be conducted to validate resistance at model scale and to ensure alignment between model-scale predictions and full-scale performance.

Building on this foundation, the project will employ generative AI techniques to explore a wide design space, enabling the rapid evaluation of hundreds of novel hull configurations. This approach moves beyond traditional parametric optimisation by allowing the discovery of unconventional yet highly efficient geometries. The combined CFD-AI framework will then be used to systematically identify optimal hull forms for given operating conditions, such as speed, displacement, and range requirements.

The expected outcomes include the development of a validated optimisation methodology, new low-resistance hull designs tailored for electric propulsion, and demonstrable improvements in vessel energy efficiency and operational range. Importantly, the project will also deliver a scalable design process that can be adopted by industry to accelerate innovation in ship design.

This research has strong relevance to the maritime industry and aligns with global efforts to decarbonise shipping. The outcomes are expected to directly benefit high-speed vessel manufacturers, including Incat, and contribute to maintaining Australia’s leadership in advanced marine engineering. By combining physics-based modelling with AI-driven design exploration, the project will establish a new benchmark for efficient and sustainable vessel design.

Primary supervisor

Meet Doctor Jason Ali-Lavroff

Funding

Applicants will be considered for a Research Training Program (RTP) scholarship or Tasmania Graduate Research Scholarship (TGRS) which, if successful, provides:

• a living allowance stipend funded by University of Tasmania of $34,315 per annum for 3.5 years
• a relocation allowance of up to $2,000
• a tuition fees offset covering the cost of tuition fees for up to four years (domestic applicants only)

A tuition fee offset may be offered to eligible international applicants following competitive assessment 

As part of the application process you may indicate if you do not wish to be considered for scholarship funding.

Other funding opportunities and fees

For further information regarding other scholarships on offer, and the various fees for undertaking a research degree, please visit our Scholarships and fees on research degrees page.

Eligibility

Applicants should review the Higher Degree by Research minimum entry requirements.

Ensure your eligibility for the scholarship round by referring to our Key Dates.

Additional eligibility criteria specific to this project/scholarship:

• First class honours in Mechanical Engineering or Naval Architecture.

Selection criteria

The project is competitively assessed and awarded. Selection is based on academic merit and suitability to the project as determined by the College.

Additional essential selection criteria specific to this project:

• First class honours in Mechanical Engineering or Naval Architecture.

Additional desirable selection criteria specific to this project:

• Experience in high-speed craft and CFD.

Application process

1. Select your project, and check that you meet the eligibility and selection criteria, including citizenship;
2. Contact Doctor Jason Ali-Lavroff to discuss your suitability and the project's requirements; and
3. In your application:
   • Copy and paste the title of the project from this advertisement into your application. If you don’t correctly do this your application may be rejected.
   • Submit a signed supervisory support form, a CV including contact details of 2 referees and your project research proposal.
4. Apply prior to 1 October 2026.

Full details of the application process can be found under the ' How to apply ' section of the Research Degrees website.

Following the closing date applications will be assessed within the College. Applicants should expect to receive notification of the outcome by email by the advertised outcome date.

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