Sort by
Refine Your Search
-
Category
-
Employer
- Cranfield University
- ; The University of Manchester
- ;
- University of Sheffield
- ; Brunel University London
- ; Swansea University
- ; The University of Edinburgh
- ; University of Surrey
- ; Cranfield University
- ; University of Birmingham
- ; University of Oxford
- ; University of Sheffield
- University of Cambridge
- University of Nottingham
- 4 more »
- « less
-
Field
-
not fully capture the high-temperature, complex thermal-fluid interactions within the pebble-bed. This PhD project will focus on advancing porous media models for pebble-bed HTGRs by leveraging newly
-
research team. Good knowledge and experience in heat and mass transfer is essential and proficiency in the use of Computational Fluid Dynamics will be considered an advantage. The student will benefit from
-
Current modelling and simulations require either generic assumptions to be made for fluid dynamic based modelling leading to inaccuracies between modelled and experimental data or, intense
-
nanosheets, nanotubes, etc) or hybrid (e.g. boron carbon nitride). Similarly, while water is the most studied coolant liquid, realistic applications involve dielectric fluids (e.g. benzene, pentane). Molecular
-
fluid dynamics (CFD) simulations, Finite Element Analysis, manage and execute the procurement of the build, run the aerothermal testing and process and communicate the results. The skills, qualifications
-
fully funded four-year PhD scholarship is available in CDT of Engineering Hydrogen Net Zero at Cranfield University. The scholarship is sponsored by EPSRC and the industrial partner (Hydrogen Waves Ltd
-
Research theme: Dynamics How many positions: 1 This 4 year PhD project is open to home students. The successful applicant will be awarded a tax free annual stipend set at the UKRI rate (£19,237 for
-
fragmentation process. The steps include: Model Development: Develop a high-resolution numerical model based on the principles of thermodynamics, fluid dynamics, and ice nucleation physics. Input Parameters: Use
-
experience in numerical fluid dynamics is beneficial but not essential; determination, curiosity, and a willingness to learn are key attributes we value. Applicants with alternative qualifications, industry
-
formation. Complementing these experimental efforts, Computational Fluid Dynamics (CFD) simulation will be employed to interpret CRUD build-up measurements, identify key phenomena influencing CRUD deposition