Why don’t all clouds give rain – Understanding physics of vapour clouds through advanced simulations and data-driven engineering

Background: Condensation is dependent on the dynamics within clouds. Clouds are immensely complex (often turbulent) multiphase environments which have temperature and concentration gradients within them. This project concerns with particulate motion in clouds, especially vapour clouds. These could either be pollutants or simply liquid droplets as in rain-bearing clouds. It is also known that not all clouds (despite favourable thermodynamics) precipitate. Some clouds just don’t precipitate despite deliberate seeding to promote nucleation. Recently, it has been noticed that particulate motion in clouds can influence precipitation – but the underlying physics is still unclear. This is particularly important not only for atmospheric physics (precipitation predictions, pollution tracking) but also for industry, particularly for the design of condensation chambers. Condensation chambers are essential for cooling technologies both large scale (refrigeration systems) and small scale (microelectronic phase-change cooling). We have a successful track-record in tackling these complex problems and develop fundamental understanding (see below).

Project: We have recently developed and released a direct numerical simulation solver called Gerris Immersed Solid Solver (GISS) that exactly solves coupled fluid-solid motion equations and predicts 6 degree-of-freedom motion for the immersed solids. The solver was augmented by theoretical work led by Prof Rama Govindarajan has resulted in the discovery of a mathematical constraint explaining the tumbling motion of suspended spheroidal particles. These have been published recently in the flagship Journal of Fluid Mechanics. We are using this to understand how particles in vapour clouds interact. Within the context of this project, the plan is to further extend and optimise this code - to look at multi-solid interactions. In particular, we want to see whether particles track chaotic orbits within clouds and how these orbits respond to thermal changes. The ensuing data generated from pure physics-based simulators like GISS will be extracted using machine-learning algorithms towards developing simpler particle-interaction models. These models will help us understand how temperature gradients as in clouds can alter the particle motion in clouds. These eventually can help us design better condensation chambers.

Resources and Training: EPCC is supporting the School of Engineering on a recently awarded EPSRC project on nucleate boiling (EP/S019588/1). We have secured extensive facility time on ARCHER (the UK’s National Supercomputer) through this boiling project. The proposed PhD will be a subset of that project and will make use the ARCHER allocation too. EPCC will also help train the student to learn optimising GISS (or its variant) and handling such a large amount of data to extract meaningful models from the physics – through machine learning. In addition, the student will undergo standard (compulsory) skills training available for all Engineering PhD students. The student will have access to the courses and training opportunities offered by EPCC as part of its HPC and HPC with Data Science MSc programmes and wider national and international training.

Career Development/ Collaboration Opportunities for Student:
• Institutional and Peer Support: The potential student will benefit from an excellent supportive environment both within the Institute for Multiscale Thermofluids at the School of Engineering, EPCC and the Institute for Computing Systems Architecture at The University of Edinburgh.
• Teaching and Research Development: The student will have the opportunity (once trained and familiar with relevant materials) to become a teaching assistant for courses on both EPCC’s MSc programmes in HPC (High Performance Computing) and HPC with Data Science as well as those offered in the School of Engineering. There will also be opportunities to contribute to wider training and Outreach activities at EPCC.
• Industrial Collaboration: The student will also have the opportunity to interact with our industrial collaborators including Thermacore Europe, Alfa Laval, CALGAVIN, Oxford Nanosystems, Intrinsiq Materials, TMD Ltd, Oxford Lasers, Elvesys, Flow Capture AS and Cherry Biotech.
• International Secondments: This PhD also comes with an opportunity to conduct secondments with our partners under the ThermaSMART consortium (funded by the European Commission) either at University of Maryland USA, York University Toronto Canada, TIFR-ICTS India or at Kyushu University Japan.
• Impactful publications and dissemination: The student will also benefit from strong support towards publications in premier journals (including the Journal of Fluid Mechanics and Physical Review Fluids) and participation in major conferences (including the American Physical Society – Division of Fluid Dynamics Meetings and the International Heat Transfer Conference). Where possible, support will be provided to allow attendance.