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Job Record #16552
TitleUQ analysis and model calibration for urban flows
CategoryPhD Studentship
LocationFrance, Rueil-Malmaison
InternationalYes, international applications are welcome
Closure Date* None *
Pollutant emissions related to transport applications have various origins. 
Measurements by sampling permit very localized estimates of concentrations 
and to have maps at an urban scale by using dispersion models. Present 
simulators use simplified representations of atmospheric turbulence that can 
be discussed when complex situations are considered (irregular buildings 
heights or dispositions generating strong 3D turbulent effects). There is a 
strong increase in the number of high frequency collected data that permits 
to bring much higher space and time resolution of pollutant sources 
estimates in relation with real driving emissions. In this context, the 
present PhD work aims at developing a high resolution approach, based on 
Lattice Boltzmann formalism, to describe the transport of pollutants at a 
local scale. The objective will be to qualify the predictivity of such 
approaches using uncertainty quantification techniques. These techniques 
will first serve to estimate and reduce uncertainties related to modeling 
parameters, to evaluate the residual uncertainties after fitting the model 
on well qualified test cases and then to propagate uncertainties related to 
some sources of emissions using the fitted simulator. From this, we will get 
a modeling tool that is capable to reconstruct 3D maps of pollutant 
concentrations at a highly resolved scale. To validate these developments we 
will rely on existing available test cases with an increasing complexity of 
the geometry up to the simulation of a realistic urban layout of buildings. 
A perspective of this work is to establish closure relations to improve the 
predictivity of complex simulators for operational services.

Academic requirements    University Master degree in Fluid Mechanics
Language requirements    Fluency in French or English, willingness to learn 
Other requirements    C/C++, Python

PhD location    Digital Sciences Division, Rueil-Malmaison, France   
Duration and start date    3 years, starting not earlier than September 2020
Employer    IFP Energies nouvelles, Rueil-Malmaison, France
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Record Data:
Last Modified14:24:51, Monday, April 27, 2020

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