About the project
This project combines cutting-edge 3D particle tracking, machine learning and fluid mechanics to measure and predict urban airflow around buildings. The research will support safer, healthier and lower-carbon urban environments while providing world-class experimental and computational training.
Engineering net-zero cities requires better methods for predicting wind loading, designing ventilation, ensuring pedestrian comfort and mitigating pollutant dispersion in complex urban environments. Current high-fidelity computational fluid dynamics (CFD) methods can provide detailed flow information but are often too computationally expensive for design and planning. This project addresses the challenge of obtaining accurate flow and pressure data around buildings using a combination of advanced experiments, physics-informed machine learning and data assimilation.
You'll develop novel object-aware 3D Particle Tracking Velocimetry (PTV) methods based on retroreflective shadowgraph imaging, enabling flow measurements in complex urban geometries with significant visual occlusions. These measurements will be combined with state-of-the-art data assimilation techniques, such as our PIGLET framework, to reconstruct velocity and pressure fields while enforcing known flow physics and quantifying uncertainty. An extension will investigate reduced-order models for predicting unsteady flow and pollutant dispersion using resolvent analysis and Gaussian process regression.
The measurements will be validated against large eddy simulations of urban flows and applied to problems including pedestrian-level wind comfort, natural ventilation and structural wind loading. Improved prediction capability could support reduced embodied carbon in buildings through less conservative wind-loading estimates, improved passive ventilation strategies, and safer, more liveable urban environments.
You'll join a thriving research community of over 50 PhDs, postdoctoral researchers and academics within the Aerodynamics and Flight Mechanics Group. You'll have access to our world-class Centre for Experimental Fluid Mechanics laboratories equipped with state-of-the-art flow diagnostics, which are complemented by our IRIDIS high-performance computing facilities.
You'll receive comprehensive, hands-on training in advanced experimental and computational techniques for fluid mechanics, including 3D particle tracking velocimetry and large eddy simulation. You'll also develop expertise in data-driven analysis, scientific computing, and the application of machine learning to large datasets. In addition to technical training, you'll have access to the University’s doctoral college professional development programme, offering workshops including research communication, high performance computing, and academic writing.
You'll be supported to publish your research, present at international conferences, and collaborate with academic and industrial partners, gaining valuable professional experience. This training will equip you with a highly sought-after skill set, spanning experimental aerodynamics, CFD, data science, and physics-based modelling, that will prepare you for careers in academia, research and development, or industry.
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.
