CFD Jobs Database - Job Record #16881
Job Record #16881 |
Title | PhD in Machine Learning and Flow in Porous Media |
Category | PhD Studentship |
Employer | The University of Manchester |
Location | United Kingdom, Manchester |
International | Yes, international applications are welcome |
Closure Date | Monday, March 29, 2021 |
Description: |
The use of porous materials (i.e. solid medium permeated by a network of pores), in particular, for
passive control of flow and thermal purposes has received considerable academic and industrial
attention over the past five decades. Examples include transpiration cooling, packed bed energy
storage and battery and LED cooling, as well as noise control for aerospace and wind turbine
applications. In such applications, fundamental understanding of interaction between the fluid flow
and the porous medium at the pore-scale is deterministic for an efficient thermal and flow/noise
control using porous materials.
In this 3-year PhD programme we will investigate the flow and thermal control using porous
materials for application to aerospace and renewable energy systems. The study performs
fundamental analysis of fluid flow and heat transfer in porous materials with the aim of achieving an
in-depth understanding of the flow features at the pore-scale deploying machine learning technique.
The project will be conducted in collaboration with the University of Bristol for experimental
measurements on the velocity field. The PhD student has the opportunity to visit University of Bristol
for data collection. The PhD student will work closely with the industrial partners (BL Refrigeration
and Air Conditioning Ltd. and Glen Dimplex Heating & Ventilation Ltd). The student will join an active
research team including three academics and four postdoctoral and PhD students working on
different aspects of porous materials for thermal management application.
Applicants must have an undergraduate or Master’s degree with a background in Mechanical,
Aerospace Engineering, Physics, Applied Mathematics, or a related discipline. Applicants with an
interest in machine learning and turbulent flow analysis will be considered. Experience in using CFD
software such as Fluent and OpenFoam is an advantage.
Enquirers are welcome to contact Dr Yasser Mahmoudi with queries or expressions of interest at
yasser.mahmoudi@manchester.ac.uk
|
Contact Information: |
Please mention the CFD Jobs Database, record #16881 when responding to this ad. |
Name | Dr Yasser Mahmoudi Larimi |
Email | yasser.mahmoudi@manchester.ac.uk |
Email Application | No |
Record Data: |
Last Modified | 16:51:01, Sunday, December 06, 2020 |
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