PhD Studentship: Multi-dimensional Optimal Order Detection Techniques for Arbitrary Lagrangian Eulerian
1 month ago
Location: Cranfield University
Funding for: UK Students
Funding amount: A bursary will be provided of up to £25,000 tax-free plus fees for four years
Closes: 19/06/2025
Supervisors: Dr Panagiotis Tsoutsanis & Dr Ahmed Al-Shabab
A fully funded PhD studentship with a bursary of £25,000 p.a. (tax-free) plus UK Home student fees for four years in the Centre of Computational Engineering Sciences at Cranfield University.
This is a great opportunity to work closely with AWE, for advancing state-of-the-art mathematical models and simulation capabilities. We are looking for an enthusiastic and motivated researcher with a strong interest in computational fluid dynamics (CFD), to join a diverse and inclusive research group. The Advanced Numerical Methods (ANM) Group specialises in cutting-edge research and consulting services focused on pioneering methods for CFD.
This exciting research seeks to evolve the forefront of computational fluid dynamics (CFD) methods for compressible flows in the emerging Exascale High-Performance Computing (HPC) landscape. The aim is to achieve high-order of accuracy but also to obtain physically meaningful results that can advance the landscape of engineering simulations.
The choice of the best numerical method, governing equations, and framework is far from obvious and unique. Employing a MOOD-style algorithm that continuously scrutinises every facet of the numerical solution, ensuring adherence to both physical and numerical admissible criteria.
Cranfield University’s Computational Engineering Sciences Centre and Advanced Numerical Methods Group will host this project, benefiting from a proven track record in pioneering and implementing cutting-edge methodologies across the entire spectrum of computational fluid dynamics and close collaborations with other research groups around the globe. AWE will serve as the industry sponsor for this project, providing valuable support by computational physics specialists.
The results of this project will contribute to an improved understanding of the possibilities and limitations of high-order MOOD methods for ALE schemes of compressible flows. The developed tools and methods will be implemented in massively parallel open-source CFD software and demonstrate best practices for method/equations/formulation selection for emerging architectures of Exascale High Performance Computing (HPC) facilities.
The student involved in this project will acquire valuable skills through several experiences including attending modules from our MSc in CFD, attending workshops for Exascale HPC in national facilities, visiting several European research groups that the centre is in close collaboration for enhancing the depth and breadth of their research methods and growing their network, and close collaboration with our partner, AWE. The student will be supported to present in international conferences, and workshops and further enrich their skillset.
Entry Requirements
Applicants should have an equivalent of a first or second-class UK honours degree in mathematics, physics, engineering or other closely background. The candidate should have advanced programming skills in any of the following programming languages (Fortran,C++, C, Python). Successful applicant will carry out research activities in the aforementioned area and disseminate research outputs through scientific publications, software development, seminars and conference presentations.
To be eligible for this funding, applicants must be UK national.
Funding & Sponsorship
Sponsored by EPSRC, AWE and Cranfield University, this DTP studentship will provide a bursary of up to £25,000 (tax free) plus fees* for four years.
£25,000 tax-free plus fees for four years
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