Data-driven 3D chemical species tomography for instantaneous imaging of reactive flows

CST uses infrared absorption spectroscopy [9] in a manner analogous to X-ray Computed Tomography, with the difference that, for incident light at an appropriately selected wavelength, the absorption measurements enable the reconstruction of the unknown spatial distribution of concentration of the target molecule. As a sensitive, fast-response and cost-effective sensing modality, CST is one of the most promising technology to apply on flow diagnosis in practical operating conditions. Most of the state-of-the-art CST focus on 2D sensing, missing the out-of-plane characterization of the reactive flow with 3D nature.

The objectives of this PhD projects are:

  1. Develop data-driven 3D CST imaging algorithm.
  2. Physically informed prediction of the reactive flow nature aided by deep learning algorithms.
  3. Experimental validation of the proposed algorithm on lab-scale industrial applications.

During the project, the PhD candidate will be trained to develop novel data-driven 3D CST imaging algorithms and predict the 3D nature of the reactive flow. In collaboration with academic and industrial partners, the developed data-driven algorithms will be finally employed for reactive flow imaging. The candidate should also be confident with trouble-shooting and collaborating with academic and industrial partners in the experiment tests.

In addition, the successful candidate will have the opportunity to work closely with industrial and academic partners, to present innovative results in international conferences, to publish high-impact journal papers, and, eventually, to deliver advanced laser-based technology.

Technical Queries directed to Dr Chang Liu on C.Liu@ed.ac.uk

Further Information: 

The University of Edinburgh is committed to equality of opportunity for all its staff and students, and promotes a culture of inclusivity. Please see details here: https://www.ed.ac.uk/equality-diversity

Closing Date: 

Tuesday, May 31, 2022

Principal Supervisor: 

Assistant Supervisor: 

Eligibility: 

Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants.

Funding: 

Applications are welcomed from self-funded students, or students who are applying for scholarships from the University of Edinburgh or elsewhere.

Further information and other funding options.

Informal Enquiries: