CFD Online Logo CFD Online URL
Home > Jobs > Job Record #15448

CFD Jobs Database - Job Record #15448

Job Record #15448
TitlePostdoc in Numerical simulations of multiphase flows
CategoryJob in Academia
EmployerBarcelona Supercomputing Center
LocationSpain, Barcelona
InternationalYes, international applications are welcome
Closure DateFriday, November 30, 2018
Postdoctoral Position in Numerical simulations of multiphase flows

Research project
Aeronautical on-board fire suppression systems, e.g. the one found in the APU
compartment, are based on the interruption of the propagation of chain reactions
typically found in aeronautical fuels. These fire suppression systems
historically used hydrofluorocarbons (HFCs) as a fire protection fluid. These
fluids with halogen gases, like Fluor are well known to be inhibitors of the
aforementioned chain reactions. Even small concentrations of these fluids in the
air are sufficient to stop the reaction. The most well-known and used one has
been Halon (R13B1, CFBr3), however due to their high global working potentials
(GWPs), the global regulatory phase-down under the Montreal Protocol and the
availability of proven, more sustainable alternatives, industry has been pushed
towards more environmentally friendly alternatives.
The main objective of the project is to develop a methodology to simulate the
penetration of a two-phase flow and to model the phase transitions. The
developed procedure should be valid to perform a parametric study relevant for
the aircraft fire suppression system. The project includes a combined
theoretical and experimental comprehensive study in order to obtain further
comprehension of the phenomena.

The candidate will be focused on the development of a multiphase flow solver
based on both Eulerian and Lagrangian approaches in the context of RANS and LES.
The work includes the development and application of advance Eulerian and
Lagrangian approaches for dispersed multiphase flow at atmospheric conditions.
The Lagrangian approach will be based on transporting group of particles with a
specific vaporization model, while the Eulerian approach will be based on
interface tracking methods as the conservative level set.

Research group description 
The research team that the applicant will be involved is the High-Performance
Computational Mechanics Group at CASE Department of BSC. The team is a
multidisciplinary group with more than 30 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 based at BSC, but will also
interact with the project partners: Universidad Politécnica de Madrid (UPM) and
CMT-Motores Térmicos (UPV).

Job position description
The offered position is a Postdoctoral position for two years to contribute to
the development and application of an Eulerian/Lagrangian multiphase approach to
predict flow atomization and vaporization of a rapidly depressurised mist.
The work conducted in the project will be performed with the parallel
multiphysics code Alya, which is an inhouse 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 a PhD in Aerospace,
Aeronautics or Mechanical Engineering degree with concentration on turbulence
and multiphase flows. General knowledge on fluid mechanics, LES, numerical
methods, interface tracking (volume of fluid, level set, …) is expected.
Computational skills and parallel programming for HPC are not necessary, but
will be considered an asset.

Application should be submitted via the BSC website:
Contact Information:
Please mention the CFD Jobs Database, record #15448 when responding to this ad.
NameDaniel Mira
Email ApplicationNo
Record Data:
Last Modified14:49:30, Monday, November 05, 2018

[Tell a Friend About this Job Advertisement]

Go to top Go to top