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Job Record #16900
TitlePhD studentship: An integrated predictive tool
CategoryPhD Studentship
EmployerUniversity of Southampton
LocationUnited Kingdom, Southampton
InternationalYes, international applications are welcome
Closure DateThursday, July 01, 2021
An integrated predictive tool for City-scale CB Hazard dispersion and uncertainty quantification. We have now run into a fast evolving but more uncertain world. This includes fast developing urban environments where most of the population lives. It is crucial that we are able to predict in time street airflows, concentration of pollutants, chemicals and pathogens, to respond promptly and to be more resilient. It is well-known that accurately predicting the dispersion of materials within 1 km of the source is challenging and beyond the capability of the models typically used for operational response. Emergency response predictions typically have high uncertainties because details of the source are limited and because that the meteorological conditions are determined from a single nearby observation station or forecast grid point. This project will exploit recent advances in computational methods and facilities to enable statistical analyses to be conducted which address two of the most challenging issues in hazard prediction: 1. How is uncertainty in hazard prediction affected by changes in the meteorological conditions and simplified building geometries? 2. How should meteorological data be processed to define the inputs for dispersion simulations? Answers to these are required so that an assessment can be made as to whether current emergency response tools are ‘fit-for-purpose’, and to define the information and data preparation requirements necessary for accurate real-time high-fidelity dispersion simulations. You will join a large and flourishing aerodynamics group ( engaged in a wide range of experimental and numerical studies of turbulent flows. The project will benefit from close collaboration with other researchers and with colleagues in the collaborative project. You will be able to access the local and national supercomputers, and work closely with external industrial colleagues through placements and regular meetings. If you wish to discuss any details of the project informally, please contact Dr Zheng-Tong Xie, AFM Research Group, Email: Apply online:
Contact Information:
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NameProf Zheng-Tong Xie
Email ApplicationYes
AddressAeronautics and Astronautics, FEPS
Room 5057/Building 176
Boldrewood Innovation Campus
University of Southampton
SO16 7QF
Tel: +44(0)23 8059 4493
Record Data:
Last Modified22:19:32, Monday, January 18, 2021

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