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CFD Jobs Database - Job Record #16538

Job Record #16538
TitleSoot formation in aeroengines
CategoryPhD Studentship
EmployerBarcelona Supercomputing Center
LocationSpain
InternationalYes, international applications are welcome
Closure DateMonday, June 01, 2020
Description:
#Research project
The design of modern combustion systems needs to address challenges in aspects related to global 
efficiency, reduction of pollutant emissions, major flexibility of operation and reduction of thermo-acoustic 
instabilities. The use of numerical simulations as a tool for design is growing in the last decade as more 
computing power is becoming available. The proposed project is focused on the development of physical 
models and advance numerical simulations of turbulent flames under conditions of interest for gas turbines. 
The main objective of the project is to develop a modelling strategy using CFD simulations for the prediction 
of soot in terms of chemical evolution and particle formation in conditions relevant to aero engine operation. 
The model developments are based on the use of detailed chemical kinetics for kerosene surrogates, and 
advanced combustion and spray models validated with reference experiments. It includes the development of 
efficient algorithms for the coupling of soot particles with gas phase dynamics allowing the use of large-scale 
applications with high computational efficiency.

The candidate will be focused on the study of soot formation from DNS and LES perspectives, and the 
integration of the soot models in the context of flamelet methods. The work departs from the validation of the 
turbulent combustion model at conditions representative of aero engine operation up to the simulation of 
spray flames with soot in complex geometries. The project is defined in order to use high-fidelity numerical 
simulations to predict complex fluid phenomena in modern and new generation combustion systems. It takes 
place in the context of a scientific and industrial framework aiming to enhance the accuracy, flexibility, user 
decision and applicability of numerical tools for industrial design.


#Research group description
The research team that the applicant will be involved is the Propulsion Technologies Group at CASE 
Department of BSC. The team is a multidisciplinary group with researchers from all disciplines and with 
strong background in Computational Fluid Dynamics (CFD). The team is involved in many EU and industrial 
projects related to this topic, where the successful activities and the publications on highly ranked scientific 
journals give the proved expertise. The applicant will be based at BSC, but will also interact with the project 
partners https://estimate-project.eu.

#Job position description 
The offered position is a full PhD position to investigate the of soot formation in aero engine combustors at 
engine-relevant conditions.

The work conducted in the project will be performed with the parallel multiphysics code Alya, which is an in-
house finite-element solver developed at BSC. The applicant is expected to get familiar with the code running 
benchmarking cases, and developing physical models that will be integrated in the multiphysics platform of 
Alya. The candidate should hold an Engineering Degree in Aerospace, Aeronautics or Mechanical Engineering 
with interest in turbulence and combustion. General knowledge on fluid mechanics, LES, numerical methods, 
soot, combustion chemistry are expected. Computational skills and parallel programming for HPC are not 
necessary, but will be considered an asset. 

#Application
The application should include:
•	CV english, motivation letter and 2 support letters
•	Starting date: 01/06/2020 - 01/08/2020
•	Deadline: 01/06/2020 
•	The applications should be submitted to the portal:  https://www.bsc.es/join-
us/fellowships/9320caseptr1


Contact Information:
Please mention the CFD Jobs Database, record #16538 when responding to this ad.
NameDanie Mira
Emaildaniel.mira@bsc.es
Email ApplicationYes
URLhttps://www.bsc.es/join-us/fellowships/9320caseptr1
Record Data:
Last Modified23:57:10, Wednesday, April 08, 2020

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