High-fidelity simulations of turbulent flows have increasingly been adopted by academia to understand the physics of turbulence (direct numerical simulation, DNS), and by industry (large-eddy simulation, LES) as design tools to minimize costly testing. Whereas the calculation of the statistics of turbulent flows can be accurate, the time and space accurate prediction of extreme events, such as violent turbulent bursts and auto-ignited spots of mixture, has not been achieved yet. No matter how accurate the simulation code is, the time and space prediction of extreme events is limited by the chaotic nature of reacting and non-reacting turbulence. This project will enable the prediction and physical understanding of extreme events by leveraging artificial intelligence and machine learning algorithms with dynamical systems' theory. An adjoint algorithm will be designed and trained to control extreme fluid dynamics, in particular in multi-physical problems that are relevant to energy harvesting and aeronautical propulsion.
This cross-disciplinary project falls in the following five EPSRC research areas: Artificial intelligence technologies, Combustion engineering, Fluid Dynamics and Aerodynamics, Complexity Science, Numerical Analysis.
Supervisor's website: http://www2.eng.cam.ac.uk/~lm547/
Applicants should have, or be expected to gain, a high 2:1, preferably a 1st class honours degree in computational mathematics, or statistics, or computer science, physics, or engineering. A good knowledge or experience of machine learning and fluid dynamics is an advantage (but it is not essential).
These studentships are fully-funded (fees and maintenance) for UK students, provide fees for EU students from outside the UK, and a small number can be used to fund students from outside the EU under the International Doctoral Scholar Scheme. Additional information about eligibility for Research Council UK funding can be found here: https://epsrc.ukri.org/skills/students/help/eligibility/
To apply for this studentship, please send: (i) two-page CV, (ii) transcripts of records, (iii) one-page cover letter, and (iv) the contact details of at least two referees for letters of recommendation to Luca Magri, e-mail firstname.lastname@example.org. The position is open until filled. In any case, applications should arrive no later than 15th March 2019. Please, contact Luca Magri for any informal enquiry about the project.
Please note that any offer of funding will be conditional on securing a place as a PhD student. Candidates will need to apply separately for admission through the University's Graduate Admissions application portal; this can be done before or after applying for this funding opportunity. Note that there is a £60 fee for PhD applications. The applicant portal can be accessed via: www.graduate.study.cam.ac.uk/courses/directory/egegpdpeg. The final deadline for PhD applications is 30 June 2019, although it is advisable to apply earlier than this.
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