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Predicting urban particulate flows using AI-enhanced turbulence models


Institute for Future Transport and Cities

Dr Humberto Medina Thursday, May 06, 2021 Funded PhD Project (Students Worldwide)
Coventry United Kingdom Computational Chemistry Fluid Mechanics Machine Learning

About the Project

Coventry University (CU) is inviting applications from suitably-qualified graduates for a fully-funded PhD studentship 

Increasing urbanisation of developing countries means that most communities suffer from air pollution. According to WHO, "An estimated 4.2 million premature deaths globally are linked to ambient air pollution" [1]. Tackling air quality is a complex task involving research of sources of pollution, effect of different pollutants on human health, and finding pollution mitigation solutions. Furthermore, the recent classification of airborne particles as carcinogenic to humans (IARC Group 1 carcinogenic) by the International Agency for Research on Cancer [2] has prompted a renewed interest in gaining a better understanding of particulate matter generation and spread in cities. Therefore, city authorities and planners are showing a keen interest (UN SDP Goal 11) in having access to modelling tools that will help them make informed decisions regarding the control and reduce of particulates from a range of sources (vehicle emissions, car and bicycle tyres, manufacturing, etc.). Currently predictive tools for particulate flows cannot be readily used at city-scales to help inform planning decision. Meso-scale models exist but are inherently computationally costly. This project will develop a new modelling technology for multi-scale prediction of particulate flow distributions using cost-efficient state-of-the-art turbulence models (developed at CU) enhanced within an artificial intelligence framework.

[1]     World Health Organisation. www.who.int/airpollution/ambient/health-impacts/en/

[2]           International Agency for Research on Cancer - https://www.iarc.fr/wp-content/uploads/2018/07/pr221_E.pdf

Training and Development

The successful candidate will receive comprehensive research training including technical, personal and professional skills.

All researchers at Coventry University (from PhD to Professor) are part of the Doctoral College and Centre for Research Capability and Development, which provides support with high-quality training and career development activities. 

Entry criteria for applicants to PHD 

·      A minimum of a 2:1 first degree in a relevant discipline/subject area with a minimum 60% mark in the project element or equivalent with a minimum 60% overall module average. 

PLUS 

the potential to engage in innovative research and to complete the PhD within a 3.5 years

·      a minimum of English language proficiency (IELTS overall minimum score of 7.0 with a minimum of 6.5 in each component)

For further details see: https://www.coventry.ac.uk/research/research-students/making-an-application/

How to Apply

To find out more about the project please contact Dr Humberto Medina at .

To apply on line please visit: https://pgrplus.coventry.ac.uk/ 

All applications require full supporting documentation, and a covering letter – plus the following

For pre-determined (named) projects an up-to 2000 word supporting statement is required showing how the applicant’s expertise and interests are relevant to the project. 

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