Back to search results

PhD Studentship: Using Physics-informed Neural Networks and Data Assimilation to Predict and Improve Urban Air Quality

University of Southampton

Qualification Type: PhD
Location: Southampton
Funding amount: Funding for tuition fees and a living stipend are available on a competitive basis. Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.
Hours: Full Time
Placed On: 1st December 2023
Closes: 31st August 2024
 

Project title: Using physics-informed neural networks and data assimilation to predict and improve urban air quality  

Supervisory Team: Sean Symon and Christina Vanderwel

Project description

The aim of this project is to use physics-informed neural networks (PINN’s) and data assimilation techniques to convert limited measurements of urban fluid dynamics into highly accurate models of pollutant dispersion in urban settings. These models are crucial for environmental management, public health and urban planning so that authorities can assess and mitigate the impact of pollutants on air quality and the well-being of city residents.

The project will initially tackle low Reynolds number problems around simplified models of urban environments which include buildings, streets or uneven terrain. The PINN’s will be trained on high-fidelity simulation data and will identify unknown closure terms in the governing equations, most notably the scalar flux which is typically modelled in simulations. Furthermore, the optimal training points and network hyperparameters will be identified.

The second phase of the project will consider experimental velocity and concentration fields at higher Reynolds numbers that are obtained using particle image velocimetry and planar laser-induce fluorescence. The PINN will use either existing experimental data or new measurements from the water tunnel depending on the problem of interest. Since the passive scalar can be measured at very high resolutions compared to the velocity, the PINN can predict the velocity field more accurately than possible without passive scalar measurements. This offers an exciting prospect for being able to improve state-of-the-art experimental techniques without the need for more hardware.

The final phase of the project will aim to predict unsteady flow structures and their frequencies using the reconstructed flow fields from PINN’s. The latter are inputs to the linearised equations of motion which reveal the most amplified structures in the flow. 

We aim to build a diverse and inclusive team to tackle challenging problems where we develop new skills and expertise in our team members. You will have a unique opportunity to work alongside other team members (PhD students and postdoctoral researchers) with different backgrounds and experience. You will the unique opportunity to be trained in using state-of-the-art machine learning algorithms and advanced data-analysis methods that will enable you to pursue a career in academia or industry. Finally, you will be able to travel to international conferences to present your work and develop new collaborations with research groups around the world.

Further information on the type of projects carried out in our lab as well as information on current lab members can be found on our website (https://sites.google.com/view/seansymon/home).

Entry Requirements

A very good undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent) in Engineering with the motivation to do experimental work

Closing date: 31 August 2024.

Funding: Funding for tuition fees and a living stipend are available on a competitive basis. Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.

How To Apply

Apply online: Search for a Postgraduate Programme of Study (soton.ac.uk). Select programme type (Research), 2024/25, Faculty of Engineering and Physical Sciences, next page select “PhD Engineering & Environment (Full time)”. In Section 2 of the application form you should insert the name of the supervisor Bharathram Ganapathisubramani

Applications should include:

Curriculum Vitae

Two reference letters

Degree Transcripts/Certificates to date

Email: feps-pgr-apply@soton.ac.uk

We value your feedback on the quality of our adverts. If you have a comment to make about the overall quality of this advert, or its categorisation then please send us your feedback
Advert information

Type / Role:

Subject Area(s):

Location(s):

PhD tools
 

PhD Alert Created

Job Alert Created

Your PhD alert has been successfully created for this search.

Your job alert has been successfully created for this search.

Ok Ok

PhD Alert Created

Job Alert Created

Your PhD alert has been successfully created for this search.

Your job alert has been successfully created for this search.

Manage your job alerts Manage your job alerts

Account Verification Missing

In order to create multiple job alerts, you must first verify your email address to complete your account creation

Request verification email Request verification email

jobs.ac.uk Account Required

In order to create multiple alerts, you must create a jobs.ac.uk jobseeker account

Create Account Create Account

Alert Creation Failed

Unfortunately, your account is currently blocked. Please login to unblock your account.

Email Address Blocked

We received a delivery failure message when attempting to send you an email and therefore your email address has been blocked. You will not receive job alerts until your email address is unblocked. To do so, please choose from one of the two options below.

Max Alerts Reached

A maximum of 5 Job Alerts can be created against your account. Please remove an existing alert in order to create this new Job Alert

Manage your job alerts Manage your job alerts

Creation Failed

Unfortunately, your alert was not created at this time. Please try again.

Ok Ok

Create PhD Alert

Create Job Alert

When you create this PhD alert we will email you a selection of PhDs matching your criteria.When you create this job alert we will email you a selection of jobs matching your criteria. Our Terms and Conditions and Privacy Policy apply to this service. Any personal data you provide in setting up this alert is processed in accordance with our Privacy Notice

Create PhD Alert

Create Job Alert

When you create this PhD alert we will email you a selection of PhDs matching your criteria.When you create this job alert we will email you a selection of jobs matching your criteria. Our Terms and Conditions and Privacy Policy apply to this service. Any personal data you provide in setting up this alert is processed in accordance with our Privacy Notice

 
 
 
More PhDs from University of Southampton

Show all PhDs for this organisation …

More PhDs like this
Join in and follow us

Browser Upgrade Recommended

jobs.ac.uk has been optimised for the latest browsers.

For the best user experience, we recommend viewing jobs.ac.uk on one of the following:

Google Chrome Firefox Microsoft Edge