Research in cryogenic fluid flow conditions is becoming increasingly urgent as interest in hydrogen fuel dispensing, among other energy carriers, grows rapidly. Understanding how to effectively maintain cryogenic conditions during fluid transfers can help optimise energy consumption by hydrogen dispensing stations, focusing on minimising dispensed cost. Gaining a fundamental understanding of flow and phase change for cryogenic fluids such as liquefied natural gas (LNG) and hydrogen (LH2) has the potential to improve safety, reliability and efficiency.
This PhD project aims to provide new understanding of cryogenic fluids used as energy vectors, by co-optimising the fluid dynamics, heat transfer and injector design. This will be achieved using advanced optical diagnostic and measurement techniques, and through the investigation of the influence of fluid physical properties, injection strategies and injector design on the flow of cryogenic liquids. Spray development will be captured using ultra-high speed video imaging. Droplet sizes, shapes and velocities will be measured using high-resolution microscopy, and the team will also attempt to measure droplet temperature and evaporation rates using novel laser diagnostic techniques. These new measurements will aim to provide new fundamental understanding of cryogenic flows, and high-precision data for the validation of numerical and data-driven models. This will develop new knowledge on heat and mass transfer to help deliver an important net-zero carbon technology for the energy sector.
The project offers a unique opportunity for the successful applicant to develop their independent research and innovation path under the guidance of an internationally recognised research team. The successful candidate will be joining a team of multidisciplinary researchers in our Advanced Engineering Centre, and will work in close collaboration with the industry project partner (BP), and our academic partner at the University of Oxford who will use these new measurements to develop new numerical models.
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