PhD Studentship: Real time 4D Imaging System for Turbulent Multiphase Flows

UK only

This 3.5-year project is funded by the Department of Mechanical, Aerospace and Civil Engineering. Tuition fees will be paid (at home rate) and you will receive a tax-free stipend set at the UKRI rate (£20,780 for 2025/26). We expect the stipend to increase each year.

Multiphase flows are common in natural and industrial processes, such as volcanic flows, bubbles in electrolysers, and blood flows. In many applications, these flows often exhibit transient behaviour, which requires meticulous characterisation simultaneously in 3D space and time (4D imaging). Although traditional high-speed cameras can achieve 4D imaging, their high data rates limit their use in real-time applications. As a result, the available benchmark data for developing numerical models to predict transient multiphase flows is limited.

This project aims to develop and demonstrate a breakthrough concept for a real-time 4D imaging system by integrating recent advancements in event-based (EB) and plenoptic imaging techniques. For the first time, the proposed system will enable single-shot, real-time 4D Imaging, going beyond the current state of the art. This project will focus on three main steps: 1. Developing real-time tomographic 4D imaging using multiple event-based cameras; 2. Developing a real-time 4D imaging with a single event camera by incorporating the plenoptic technique; 3. Developing the first-ever AI/ML algorithm to predict the transition in real time. This will be implemented in benchmark transient multiphase flows, such as bubbly flows, turbulent liquid jet breakup, etc. The implementation of 4D imaging in such flows will bring the first-ever unique insights into bubble-turbulence interactions, collision, and coalescence dynamics.

Furthermore, real-time 4D imaging enables the integration of AI/ML models for prediction and the development of early warning systems before the onset of transition. Subsequently, this enables the development of more accurate computational models for various industrial processes. The experimental methods developed in this project will directly contribute to a better understanding of multiphase flows in a wide range of engineering and medical applications.

Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline.

Applicants must have: A strong foundation in fluid mechanics; Knowledge of experimental techniques is preferred but not mandatory; Basic programming skills in any language; Strong written and verbal communication skills.

To apply, please contact the main supervisor, Dr Kuppuraj Rajamanickam - kuppuraj.rajamanickam@manchester.ac.uk. Please include details of your current level of study, academic background and any relevant experience and include a paragraph about your motivation to study this PhD project.