About the project
This project will develop a multi-scale surrogate modeling framework to optimize passive surface textures (like dimples) for maximum fluid drag reduction. By enabling efficient shape optimization and identifying critical flow parameters, this research seeks to resolve conflicting results and advance the theoretical understanding and practical application of cost-effective flow control in transportation.
To achieve zero-carbon targets and comply with emission reduction regulations in transportation, the development of effective fluid drag-reducing technologies has become crucial in recent years. Passive flow modulation using engineered surface textures, such as dimples, have gained significant attention for their manufacturing simplicity, and cost-effectiveness in both air and sea transportation. These textures can affect the turbulent boundary layer to reduce skin friction, without requiring any active input. However, the underlying physics governing the spatially evolving turbulent boundary layer is not well understood, and there are contrasting views on the flow mechanisms involved in drag reduction.
Although several studies have examined textured surfaces, there is significant disparity among the results. Many experimental works observe drag reduction for certain dimple geometries and flow conditions, whereas others only report drag increase and flow separation. Identifying and exploring the range of crimodeling approach that can perform unbiased sample-efficient shape optimization.
This project will identify key parameters influencing fluid drag over textured surfaces, and provide a comprehensive understanding of the underlying physical mechanisms that affect fluid drag. Ultimately, this investigation will enable engineers to develop textured surfaces that significantly reduce drag, advancing both theoretical understanding and practical applications.
You will be joining a collaborative group dedicated to addressing complex real-world engineering problems. The group is focused on conceptualizing cutting-edge data-driven topology and optimization methodologies. These techniques are specifically developed with the aim of solving real-world engineering challenges such as fluid structures, turbo-machinery, metamaterials, etc.
The University of Southampton boasts extensive high-performance computing (HPC) and experimental facilities making this a unique opportunity to conduct high fidelity, multi-disciplinary research and collaborate with world-class researchers.
The School of Engineering is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.
