This 8-week internship is part of the University of Manchester Student Experience Internship scheme. Applicants must be penultimate year undergraduates at the University of Manchester.
About this role
Background: Lung oscillometry is a technology for measuring the flow impedance of a person’s lungs. It has a range of potential uses in clinical research as it can sensitively detect blockages or constrictions in the small airways of the lung. A motivating example is in the diagnosis of asthma, which involves measuring a change in lung function after a bronchial challenge. The current standard is to use spirometry, which is insensitive to changes in the small airways, and so has the potential to miss patients with mild asthma and detect the disease early1.
The method involves a device that induces a low amplitude pressure wave (usually via a loudspeaker) at the person’s mouth while they breathe normally through the mouthpiece. The pressure and flow rate at the mouth are monitored continuously and the resulting amplitude difference and phase shift between them is used to calculate the effective flow impedance of the respiratory system2.
Indices derived by oscillometry are informed by mathematical modelling. Typically, these use an electrical circuit analogy to model the system, and so then the entire system of airways can be treated as a network of inductors3,4. The impedance of each airway is approximated by Womersley flow5,6, which assumes steady oscillatory flow in a long tube. These underlying assumptions mean that in some cases this will be a poor approximation to the fluid dynamics in real lung airways, where even at moderate Reynolds number the bifurcations linking airways can have a significant effect on the flow7. Therefore, we propose to use computational fluid dynamics methods to simulate flow profiles in realistic airway bifurcation geometries to validate and/or improve these models.
The intern will work within the interdisciplinary lung modelling group, as well as the biomechanics group in the Department of Mathematics, providing a great opportunity to work alongside other researchers including PhD students and academics.
Last years' interns wrote a blog about their time in the SEI programme, please click here to read about their journey.
References:
Kaminsky, D. A. et al. European Respiratory Review 31, (2022).
King, G. G. et al. European Respiratory Journal 55, (2020).
Bhatawadekar, S. A., Leary, D. & Maksym, G. N. Can. J. Physiol. Pharmacol. 93, 207–214 (2015).
Foy, B. H. & Kay, D. Respir. Physiol. Neurobiol. 240, 61–69 (2017).
Thurston, G. B. The Journal of the Acoustical Society of America 24, 653–656 (1952).
Womersley, J. R. J Physiol 127, 553–563 (1955).
Pedley, T. J., Schroter, R. C. & Sudlow, M. F. Respir. Physiol. 9, 387–405 (1970).
Key aims, objectives and duties:
Aims
To characterise oscillatory flows in realistic airway bifurcation geometries
To identify parameter regimes where Womersley flow provides an (in)adequate assumption
To derive alternative expressions to approximate impedance in a whole-lung model
Duties
Formulation and non-dimensionalisation of the mathematical problem to be solved
Carrying out computational fluid mechanics simulations (either in open access software or University licensed software). The student will be provided with all the necessary equipment to carry out the project, such as a workspace and access to computing facilities, including a specialised workstation dedicated to the Lung Modelling Group.
Analysis, interpretation and write-up of the simulation results into a project report. A related project was completed in 2024 so the student will benefit also from the experience and findings of the previous year’s internship.
Presentation of the results to the wider biomechanics group at the end of the project, which will develop the student’s project management and presentation skills
As an equal opportunities employer, the university welcomes applications from all suitably qualified persons and all appointments will be made on merit. We particularly welcome applications from groups under-represented in Higher Education. For further information please see The University of Manchester's Widening Participation page.
Qualifications
To apply you must be a penultimate year undergraduate, i.e. in your second year of a three year course or your third year of a four year course.
Please note, this internship would particularly suit students from the following Departments/Schools:
Computer Science
MACE
Mathematics
Physics
Skills
Essential skills & attributes
A strong mathematical background with knowledge of concepts in fluid mechanics.
Experience in computational fluid dynamics modelling OR experience in C++ programming.
Enthusiasm for research at the interface of mathematics and life sciences.
Ability to work independently and good time management.
Good English communication and writing skills.
Desirable skills & attributes
Knowledge of lung anatomy and physiology