The post-doc position is integrated in the I-Street project funded by ADEME. 
The bitumen binders stored as packing granular product at ambient temperature
seems very promising for road industry creating healthy work environment while
decreasing energy impact. By considering the energy cost equal to 400 MJ the ton
of the produced asphalt materials, the energy cost between the USA (~4 MTep) and
Europe (~ 2.83 MTep) corresponding to about 0.15% of the world's annual oil
production. Currently, the road materials are produced in a mixing plant to get
a viscoelastic materials at a temperature ranged between 90 ° C and 160 ° C.
Primarily, the bituminous binder is maintained into a tank at a temperature near
of its melting point (~100°C) before to be introduced in the mixing process. In
that temperature range, the rheological behavior of Newtonian type is valuable
for the coating of the aggregates from the bituminous binder. 
The influence of the mixing process between a bituminous binder stored as
packing granular product and the hot materials would result on a partial final
coating constituting the main barrier of that innovation. This last point is
related to the mixing, melting and diffusion issues. In that context, the work
of the post-doctoral fellow will be mainly devoted to the characterization of
the thermal dispersion of a granular medium thermally segregated at the initial
state.
The candidate should be based on modeling tools of continuous and/or discrete
type to carry out co-simulation works in order to reduce computation time. The
work of the post-doctoral fellow will be mainly devoted to simulation and
numerical modelling, which will focus more specially on:

1.	The assessment of the kinematics of the multiphasic system representative of
the processes. As a first approximation, monodisperse spherical grains at
ambient temperature will be chosen in a model geometry containing a bed of
materials at manufacturing temperature. 

2.	The numerical simulations to characterize the thermal homogenization time of
granular materials by considering their thermophysical parameters in an
elementary volume representative of the studied system. 

3.	Prepare the implementation of a suitable continuous physical model 

The present postdoc position is open in the framework of the project
“high-fidelity exPerimental and numERIcal study for daTa-drIven modeliNg of
rEalistic turbuleNt separaTed flows” (PERTINENT).
Turbulent separated flows (TSF) are of capital importance for a plethora of
applications, including the Aerodynamics of road vehicles, wind turbines and
helicopter rotors. These flows represent a challenge for traditional models in
Computational Fluid Dynamics (CFD), relying on the solution of the
Reynolds-Averaged Navier-Stokes (RANS) equations supplemented by a turbulence model.
Given the urgent need for greener automotive, transport and energy production
solutions for the sustainable growth of our society, it is then clear that
next-generation models are required for the efficient design, control and
optimization of TSF. 
The Institut Aérotechnique (IAT) and the Aerodynamics and Aeroacoustics (AERO2)
group of the DynFluid Laboratory aim at contributing to a novel simulation
paradigm for turbulent separated flows of interest in aeronautics, wind and
automotive engineering, based on the augmentation of RANS turbulence models by
means of Statistical Learning and Uncertainty Quantification techniques
integrating high-fidelity experiments. Such data-augmented models leverage
knowledge from specifically tailored high-fidelity experimental and numerical
databases and combine this with sound physical constraints derived from
mathematical physics, while automatically identifying regions of possible high
uncertainty of the model. To achieve its goals, the project will create a
multi-disciplinary synergy between advanced experimental techniques and
facilities available at IAT and the long-term expertise in both high and
low-fidelity turbulence modelling of AERO2, leading to radically improved CFD
models with the potential to further disseminate to a number of other applications.
The DAM models developed in PERTINENT will be trained and assessed against novel
high-fidelity experimental and numerical databases obtained during the project
and specifically tailored for the target applications in wind turbine and
automotive aerodynamics.

The research team of PERTINENT is urgently looking for a postdoctoral researcher
in applied aerodynamics with skills in high-fidelity numerical simulations
(Large Eddy and Direct Numerical Simulations), in advanced methods for the
analysis of data from experiments and numerical simulations (modal
decomposition, modal reduction, Fourier analysis…), and data assimilation
techniques. A background in uncertainty quantification and/or machine learning
techniques is appreciated.

Contract duration & Salary
24 months appointment, starting June 1, 2019.
Approximately 3080 €/month gross salary.

Contact
For more information and to send your application (Resume, Motivation letter,
the names of two person susceptible to write a recommendation letter):

Prof. Francesco Grasso, francesco.grasso@cnam.fr 
Prof. Paola Cinnella, paola.cinnella@ensam.eu

Plasma-assisted ignition of future combustion systems with low environmental impact


Research context

In car engines, the technical guidelines adopted to reduce the carbon footprint of spark-ignition engines lead 
to the use of diluted combustion concepts, either by air or by the recirculation of exhaust gases. For high rate 
of dilution, the combustion becomes unstable, causing the loss of all the expected benefit. The quality of the 
ignition, which is a strong contribution to combustion stability, must then be improved. 

An innovative solution to improve the ignition of a reactive mixture is to generate high voltage electrical 
discharges between two electrodes, located near the flame reaction zone. A plasma is generated locally, 
which interacts with combustion. The advantages of plasma-assisted combustion have been observed in 
laboratory burners by Pilla et al (2006) under the action of nanosecond repetitive pulse (NRP) discharges.  
The principle of flame stabilization by NRP discharges is illustrated in Fig. 1 (left). PNR discharges are 
generated by the application of a high voltage electrical pulse (about 10kv) for about 10 ns between two 
electrodes at a repetition frequency of about 10kHz. These generate active species (such as the O radical), 
electrons and sufficient local heating to initiate the combustion of very poor fuel/air mixtures. NRP discharges 
have also stabilized premixed poor flames on several laboratory burners (Pilla et al., 2006, Bak et al., 2013) 
and recently in more turbulent applications (Barbosa et al., 2015) with a plasma power that remains below 1% 
of the power released by the flame.

The NRP ignition concept is a promising way to facilitate and strengthen the ignition of homogeneous ultra-
poor (richness = 0.5) or highly diluted mixture with burnt gas. To develop this technology, however, the 
fundamental mechanisms of flame core ignition by NRP discharges must be understood. The objective of the 
thesis is to study this phenomenon through high-fidelity numerical simulations. In particular, the thermal and 
chemical contributions of an NRP discharge ignition will be modelled on the development and growth of the 
"baby flame" observed during the ignition cycle of a reactive medium, taking into account the high levels of 
dilution, low richness and comparing the results to a conventional ignition.


Scientific challenges

The simulation of plasma-stabilized turbulent flames is a complex multi-physical problem because it involves 
many interacting phenomena: flow turbulence, combustion chemistry and plasma kinetics. All these physical 
phenomena cover a wide range of time and length scales.

Several numerical simulations have recently been carried out to understand the influence of NRP landfills on 
combustion. A first approach is to simultaneously solve the equations describing discharge, plasma, flow and 
combustion kinetics. For example, Bak et al (2012) simulated the plasma-assisted stabilization of a 
methane/air laminar flame. Tholin et al (2014) conducted a numerical study of the ignition by NRP discharges 
of preheated mixtures of H2 and air. These simulations provide initial answers regarding the impact of a 
plasma on combustion. However, due to their high calculation cost, detailed simulations are limited to 1-D or 
even 2-D configurations under laminar flow conditions. The computational domains, which are also limited to 
the vicinity of the plasma discharge, are too small to capture all the scales involved in a turbulent combustion 
chamber. There is a need to develop a low-cost CPU plasma-assisted combustion model that reproduces the 
thermal and chemical contributions of the plasma.

The second issue is the computational cost of coupling the plasma model with the complex chemical kinetics 
of ignition. Indeed, hydrocarbon chemistry involves hundreds of chemical species that react through 
thousands of elementary reactions. Combustion kinetic mechanisms are known but they must be reduced for 
use in 3-D CFDs (Fiorina et al., 2015).

Finally, the third issue concerns the modelling of interactions between plasma, combustion chemistry and 
flow turbulence. Large-scale simulations (LES) are well adapted to the unsteady phenomena characteristic of 
turbulent flames (Poinsot & Veynante, 2011). However, sub-grid scale models must be developed to apply 
LES to plasma stabilized flames. 


PhD objectives


a. Development of an NRP discharge model for the numerical study of ignition.

The EM2C laboratory, through the recent work of Castela et al (2016) and Bechane et al (2019), has 
developed a simplified plasma description model to conduct 3D simulations of reactive turbulent flow in 
complex geometries. The originality of this model is to capture the thermal and chemical contributions of 
plasma at ultra-fast (ns) and slow (ms) time scales. This model was recently implemented by Bechane et al 
(2019) in a low Mach LES code to study the stabilization of a lean flame by NRP discharges. Since 
compressible phenomena have been neglected, this strategy cannot be used to study ignition in an engine 
configuration. The doctoral student's first mission will be to implement the Castela model in the AVBP 
compressible LES code. The doctoral student will validate this method by simulating the ignition of the 
MINIPAC burner under lean conditions, studied experimentally at the EM2C laboratory (Pilla et al., 2006). The 
analysis of the simulation results will identify the fundamental mechanisms of NRP discharge ignition.

b. Development of a reduced kinetic scheme for plasma-assisted combustion. 

In a second step, the doctoral student will develop a reduced kinetic scheme that takes into account both 
thermal and chemical effects of a plasma on ignition. The work will be based on the virtual chemistry method 
recently developed at the EM2C laboratory (Cailler et al. 2017). This method consists in optimizing reduced 
kinetic schemes composed of virtual species and virtual elementary reactions. Virtual species will be 
introduced and optimized to model the impact of plasma on ignition kinetics. 

c. Simulation of an internal combustion engine based on Turbulent Jet Ignition concept

The last phase of the thesis will be devoted to the simulation of NRP discharge ignition under real internal 
combustion engine conditions. After adapting the subgrid scale models to plasma-assisted combustion, LES 
under very lean turbulent homogeneous conditions will be performed. The PhD student will study in particular 
the growth of the "baby-flame" in high Karlovitz combustion conditions in order to conclude on the relevance 
of the NRP concept.

5- Skills

- Specific knowledge :

Energy, automotive engines, fluid mechanics simulation, plasma. A first experience in modeling and simulating 
reactive media would be an advantage.

- Desired training:

Engineering school and/or Master's degree in research

6- Host laboratory


Laboratoire EM2C, Centrale Supélec
PhD advisor : Benoît Fiorina

7- Application

Send CV, transcripts, letter(s) of recommendation and cover letter to :

benoit.fiorina@centralesupelec.fr


8- References


M. S. Bak, H. Do, M. G. Mungal, M. A. Cappelli. Combustion and Flame 159 3128–3137 (2012)
M. S. Bak, S. Im, M. G. Mungal, M. A. Cappelli. Comb. Flame, 160 (11), 2396-2403 (2013)
Y. Bechane, N. Darabiha, V. Moureau, C. Laux and B. Fiorina. 57th AIAA Aerospace Sciences Meeting, 
SCITECH, San Diego, USA. (2019).

S. Barbosa, G.Pilla, D.A. Lacoste, P.Scouflaire, S. Ducruix, C.O. Laux and D. Veynante, Phil. Trans. R. Soc. A. 
373: 20140335  (2015) 
M. Cailler, N. Darabiha, D. Veynante and B. Fiorina. Proc. Combust. Inst. 36 (1), pp 1251-1258 (2017)
M. Castela, B. Fiorina, A. Coussement, O. Gicquel, N. Darabiha and C.O. Laux. Comb. Flame. Vol 166 pp 133-
147. (2016)
B. Fiorina, D. Veynante and S. Candel. Flow Turb. and Combustion. Vol 94, Issue 1, pp3-42 (2015)
T. Poinsot & D. Veynante. Theoretical and Numerical Combustion, third Edition. (2011)
F. Tholin, D.A. Lacoste,  A. Bourdon, Combustion and Flame 161 1235– 1246 (2014)

Sunrise Systems is expanding its technical team in order to meet the demands of
its international success.  Our software product PIPENET is the No.1 tool for
fluid flow analysis and is an international standard in the oil & gas, power and
shipbuilding industries.

Responsibilities 
• Participate in the design and development of a brand new GUI
• Keeping the GUI up to date 
• Working with a team in developing a brand new product

Requirements of candidates
• Knowledge and experience of Object Orientated Programming.
• Experience of languages such as C# and/or C++.
• Some software design experience.
• Knowledge of engineering applications would be an advantage.
• Aptitude for technical software development 

Benefits 
• Competitive salary
• Private health insurance and ample free parking included
• Independent and creative work in a highly successful international company 
• Focused and supportive team environment

How to apply
Please email your CV to recruitment@sunrise-sys.com

We are looking for an experienced CFD-Engineer that is highly skilled in 
OpenFOAM. The task of the candidate is to conduct the CFD related research in 
the EU-funded research project ProNoVi (www.pronovi.eu). 

The goal of this sub-task in the project is to simulate a specific propeller 
behind a given ship hull and evaluate the acoustics in the near field on the 
ship hull and the underwater radiated noise in the far field in model and full 
scale and subsequently compare with corresponding measurements until mid of 
2021.

Currently our favored approach is to utilize implicit LES with the Schnerr-
Sauer cavitation model and FWH method in the Farassat 1A permeable surface 
formulation. 

For this, the candidate should fulfill the following requirements:
-Solid background with OpenFOAM, having worked within the source code and 
implemented and modified models
-Extensive knowledge of turbulence modelling, preferably with LES
-Experience in two-phase flow simulations, ideally regarding cavitation 
modelling
-Previous work with acoustics would be an advantage
-Understanding the principles of a marine propeller is mandatory, general 
shipbuilding could be beneficial
-Scripting with Python is an asset, but not required
-German language proficiency would be appreciated, but is not necessary

For further Information please check https://career.schottel.de/jobs-bei-
schottel/stellenangebote/

Project: Advanced Lattice-Boltzmann Understandings for Multiphysics 
Simulations (ALBUMS) funded by Airbus, Safran, Renault and the French National
Research Agency (ANR)


Description 

Fluid dynamics simulations play now a crucial role in aeronautics and automotive
industry with the ambition to predict accurately quantities of engineering
interest for turbulent flows developing inside or over full scale real-world
objects. The key of the success is the development of high-fidelity simulations
based on accurate and efficient discretization methods and algorithms working in
the HPC framework. This is required by the several millions of degrees of
freedom induced by the very large range of spatio-temporal scales as well as by
the complex geometry to discretize.

The intrinsic properties of the Lattice Boltzman method coupled with the
immersed boundary method presents a great potential to predict complex flows in
realistic conditions. This is already assessed by successful simulations carried
out by the M2P2 team for the automotive and aeronautic industry. However, some
key issues have been already clearly identified to push forward the reliability
and the accuracy of such simulations with LBM and immersed boundary method. 

In this context, a one-year renewable post-doct position is opened at the M2P2
laboratory in Marseilles (Aix-Marseille Univ, CNRS, Ecole Centrale) to focus on
the modelling of solid wall and turbulent boundary layer, which is a key issue
to accurately predict aerodynamic forces and heat transfer in complex full-scale
industrial configurations. The post-doc will aim at developing an improved
no-slip boundary condition with an increased physical accuracy and numerical
stability. The work will have to prevent mass leakage through solid walls, and
to guarantee the symmetry preservation of solid wall condition, i.e. by
developing a (nearly) fully isotropic condition without large directional error.
A part of the work will concern the development of advanced interpolation
schemes needed by the combined use of uniform grids and IBM. In the case of
turbulent flows, in which the no-slip boundary condition is not relevant, the
use of improved explicit algebraic wall models based on turbulent velocity
profile models will be considered. 

This post-doct fellowship is part of the ALBUMS chair (Advanced
Lattice-Boltzmann Understandings for Multiphysics Simulations, 2019-2023)
recently granted by the ANR and three worldwide industrial companies AIRBUS,
SAFRAN and RENAULT for 4 years to deal with the development of efficient Lattice
Boltzmann Methods (LBM) for the simulations of flows in realistic industrial
applications in the field of aerodynamics, aeroacoustics and heat transfer.


Expected profile of the candidate 
The candidate will hold a PhD with a solid background in computational fluid
dynamics and fluid mechanics. The numerical developments required will involve
team-working skills to interact frequently with other post-docs/PhD working on
the same numerical code, software engineers, associated industrials and
supervisors. 

Research team
The post-doc will be part of the ALBUMS (Advanced Lattice-Boltzmann
Understandings for Multiphysics Simulations) project at the M2P2 lab, in
Marseille. Funding is assured by the national research agency (ANR), Airbus,
Renault and Safran.
Supervision of the research work will be assured by Eric Serre, renowned CFD
specialist, and Pierre Sagaut, renowned scientist on turbulence modeling, LBM
and ALBUMS Chair holder. 

How to apply 
Send an application to: eric.serre@univ-amu.fr and pierre.sagaut@univ-amu.fr
including:
- A detailed CV 

- A cover letter 


Starting date: September to February 2020

Contract duration: 1 year (renewable every year)

Deadline to apply: 20/01/2020

The environmental fluid mechanics group at the University of Houston has an open Ph.D. 
position in computational fluid dynamics/fluid mechanics to start in Fall 2019 or Spring 2020. 
The position will be fully-funded including tuition and a stipend.

The Ph.D. student will be responsible to conduct state-of-the-art large eddy simulations of 
turbulent environmental flows with various urban, coastal, and energy applications. 
Furthermore, the Ph.D. is expected to perform postprocessing of big environmental data and 
derive simplified analytical or statistical models to describe different fluid dynamics 
phenomena.

Required qualifications:
-	A BS or MS degree in engineering, mathematics, physics, or other closely related fields
-	A strong background in numerical methods, mathematical modeling (especially 
differential equations), and fluid dynamics
-	Experience in developing numerical models and computational algorithms
-	Strong hands-on experience with programming in Fortran, C/C++, Python, MATLAB, or 
other languages
-	Strong motivation to perform cutting-edge research and to publish high-impact papers. 

Preferred qualifications:
-	Experience with parallel computing (e.g. MPI) 
-	Experience with machine learning in Python or other languages.
-	Proficiency in Linux computing environment
-	In-depth knowledge of turbulence, hydraulics, and dynamics
-	Publication in an internationally recognized journal

Experience with OpenFoam/Fluent or conducting meteorological measurements will be 
a plus.

The position is available for Sept. 2019/Jan. 2020. Interested candidates should send their CV, 
unofficial transcripts, unofficial English language test results (if applicable), and a short cover 
letter (max 1-page) to Dr.Mostafa Momen mmomen@central.uh.edu. Please note that the title 
of your email should start with "PhD-EFM-CFD". In the cover letter, please include relevant 
projects, your research interests, as well as your future career goals. The review of candidates 
will begin immediately and continue until the position is filled.

The civil engineering program at the University of Houston is ranked #62 in the USA 
according to the 2019 U.S. News and World Report rankings. In addition, the civil engineering 
program is ranked 101-150 in the world according to the 2018 Shanghai Ranking. The 
University of Houston is located in a park-like campus a few minutes from downtown 
Houston. Houston is the fourth largest city in the U.S. and is the “energy capital of the world”. 
The greater Houston area offers state-of-the-art recreational facilities, world-class arts and 
cultural activities, and affordable housing.

The Medical Imaging Lab at the University of Louisville is seeking a highly motivated doctoral 
student and a postdoctoral Fellow to work on cardiovascular Flow MRI as part of an NIH funded 
study 

Doctoral applicants need to have completed an MS in engineering  with coursework in image 
processing,  medical imaging, and/or fluid mechanics with strong programming skills. Competitive 
GRE scores (typically > 310) and for international students, TOEFL scores (typically > 100) required. 

Postdoctoral fellow applicants need to have a strong record of publications in one or more of the 
following areas: computational fluid dynamics for biological flows, cardiac MRI, image processing. 
Please send your statement of background and  interest, CV and copies of recent publications to 
amir.amini@louisville.edu

High Fidelity Computational Tools for Swimming Hydrodynamics

A PhD position is available immediately in the area of computational 
hydrodynamics in the school of Mechanical and Aerospace Engineering. The 
researcher will develop/modify in-house codes based on OpenFOAM for complex 
body motions using a combination of immersed boundary and overset mesh 
methods.


Required Qualifications:
- At least an upper second class (2.1) degree in engineering or science or 
equivalent
- Evidence of published research articles(Journal or conferences)
- Basic programming knowledge


Preferred Qualifications:
- OpenFOAM programming and parallel computing using MPI
- Good understanding of basic fluid dynamics

Interested candidates should contact me via email at: d [dot] 
chandar@qub.ac.uk with the subject : "PhD-Swimming-2019". However 
applications should be made electronically through the
Queen’s online application portal provided below


Queen’s University Belfast is a diverse and international institution which 
is strongly committed to equality and diversity, and to selection on merit. 
Currently women are underrepresented in research positions in the School and 
accordingly applications from women are particularly welcome.