Unlocking the potential of optimized vertical-axis wind turbine arrays via surrogate-modelling and topology optimization

About the Project

Supervisory team: Dr. Haris Moazam Sheikh

This project will develop a multi-scale optimization framework using surrogate modelling and topology morphing techniques to overcome the high cost of Vertical-axis wind turbines (VAWTs) design. It will create VAWTs optimized specifically for array performance, harnessing both lift and drag effects. This will significantly improve the viability of commercially viable urban wind farms.

The worsening energy crisis has focused commercial and academic interests on optimizing green-energy products. Vertical-axis wind turbines are a promising research direction due to their enhanced efficiencies when closely packed in arrays and their suitability for urban wind conditions. However, current research takes VAWTs optimized for standalone operation and packs them into arrays, rather than optimizing the VAWTs operating in the array.

An extensive exploration of novel wind turbine shapes working in an array is highly desirable to achieve major improvements over conventional designs. However, the flow around a VAWT is complex and strongly influenced by geometric and flow parameters. Accurately capturing the flow dynamics requires high-fidelity simulations or experiments, which are extremely expensive and limit the number of design evaluations possible. This high cost forces design engineers to narrow their focus and sacrifice exploration.

This project will seek to bridge this gap by developing an integrated, multi-scale framework to perform unbiased and sample-efficient shape optimization of VAWTs in an array configuration. You'll develop novel surrogate-modelling and topology morphing techniques to efficiently design VAWT arrays. Our optimization will produce hybrid VAWTs that harness both lift and drag effects for improved VAWT array performance. This project has the potential to significantly improve the viability of wind power and pave the way for commercially viable low-noise urban VAWT wind farms.

Entry requirements

You must have a UK 2:1 honours degree, or its international equivalent, in one of the following: mechanical engineering, mathematics, physics, computer sciences or a related field.

Essential skills:

• Proficiency in at least one high level scientific computing language such as MATLAB, Python, etc
• capability to conduct research independently and collaboratively
• Passion to explore new scientific idea, solving problems with scientific rigor and producing high-impact research

Fees and funding

Full scholarships include tuition fees, a tax-free stipend at the UKRI rate for up to 3.5 years (totalling £20,780 for 2025/26, rising annually). UK, EU and Horizon Europe students are eligible for scholarships. Chinese Scholarship Council funded students are eligible for fee waivers. Funding for other international applicants is very limited and highly competitive. Overseas students who have secured or are seeking external funding are welcome to apply.