Postdoc position onOrientation of spheroids in near wall flows and rebound on surfaces: direct simulations and stochastic models, INRIA, Nice Sophia Anitpolis (France)

2021-04005 - Post-Doctoral Research Visit F/M Calisto- POSTDOC2021: Orientation of spheroids in near wall flows and rebound on surfaces: direct simulations and stochastic models 

Level of qualifications required : PhD or equivalent Fonction : Post-Doctoral Research Visit 

Context 

Host Team 

The postdoc position is offered within Team CaliSto at Inria Sophia Antipolis Méditerranée. The team is working on the stochastic modeling applied to single-phase and multiphase flows through complex stochastic differential equations. This is done in collaborations with researchers that share interest in environmental applications (including meteorologists, hydro-physicists, physicists specialized in turbulence and two-phase flows modeling). 

General context: Particles are omnipresent in the environment. 

Particles are indeed found in atmospheric flows (e.g. volcanic cloud and ash fallout, droplet growth in clouds, aerosol & pollutant dispersion) and marine systems (e.g. silt deposition in delta rivers, plastic pollution in oceans and rivers, plankton sedimentation in oceans). The presence of particles suspended in a flow also impacts a large range of industrial processes, from energy production facilities (fouling of heat exchangers by iron oxides), to automotive (soot deposition in combustion engines) through oil transportation (use of polymers to modify the fluid rheology). Besides, particle suspensions is a matter of concern in medical applications (e.g. pollutant dispersion in urban areas, contaminant release from the floor in hospitals). 

A multi-scale and pluri-disciplinary topic. 

This brief overview shows that the particles encountered are complex and are driven by intricate mechanisms: particles have indeed various origins (either natural or emitted by human activities); particles have various nature (e.g. inorganic, organic, biologic); particles are polydisperse (with sizes ranging from a few nanometers up to a few millimeters); particles have any shape (e.g. spherical, spheroidal, elongated or flat); particles display a range of mechanical properties (e.g. hard solids, deformable or flexible particles); particles can collide together in the fluid and form larger agglomerates; they have complex interactions with surfaces, on which they can deposit and later be resuspended again; they can even modify the very nature of the flow (i.e. polymeric flows). Particle- laden flows is thus a highly multi-disciplinary topic (with issues related to fluid mechanics, interface chemistry, surface and material science). Besides, it spans a wide range of temporal and spatial scales (from the nanometer scale up to geological scales). Understanding the evolution of the particle characteristics, of their trajectories and their effect on the fluid is key to the design of optimal industrial processes or environmental solutions. 

Shortcomings of predictive tools. 

Research institutes and companies are increasingly relying on numerical models and simulations to address the issues related to fluid dynamics and multiphase flows. This led to the development of Computational Fluid Dynamics (CFD) codes to solve the Navier-Stokes equations, which describe the fluid motion. Currently, a range of methods are available, from direct numerical simulations (DNS), which explicitly solve all the scales, to macroscopic turbulence models, such as Reynolds-Averaged Navier-Stokes (RANS) approaches which provide information only on the mean and fluctuating components of the fluid velocity. Despite tremendous advances in the accuracy and efficiency of CFD codes for single-phase flows, simulations of multiphase flows still suffer from several drawbacks. At the theoretical/fundamental level, most CFD codes for particle-laden flows oversimplify the microscopic-scale phenomena (e.g. particles are open assumed to be spherical and not deformable). At the modelling level, the challenges are related to the multi-disciplinary aspects of multiphase flow, which require the coupling of phenomena occurring at various scales (e.g. adhesion acting at the nanometer range and transport over scales larger than a few millimeters). 

Assignment 

For a better knowledge of the proposed research subject: 

The candidates are invited to have a look at the following scientific references:
[1] Henry, C., Minier, J. P., & Lefèvre, G. (2012). Towards a description of particulate fouling: From single 

particle deposition to clogging. Advances in colloid and interface science, 185, 34-76.
[2] Henry, C., & Minier, J. P. (2014). Progress in particle resuspension from rough surfaces by turbulent 

flows. Progress in Energy and Combustion Science, 45,1-53. 

[3] Jeffery, G. B. (1922). The motion of ellipsoidal particles immersed in a viscous fluid. Proceedings of the Royal Society of London. Series A, Containing papers of a mathematical and physical character, 102(715), 161-179. 

[4] Lambert, B., Weynans, L., & Bergmann, M. (2020). Methodology for numerical simulations of ellipsoidal particle-laden flows. International Journal for Numerical Methods in Fluids, 92(8), 855-873. 

[5] Quintero, B., Lain, S., & Sommerfeld, M. (2021).Derivation and validation of a hard-body particle- wall collision model for non-spherical particles of arbitrary shape. Powder Technology, 380, 526-538. 

[6] Minier, J. P., & Pozorski, J. (1999). Wall-boundary conditions in probability density function methods and application to a turbulent channel flow. Physics of Fluids, 11(9), 2632-2644. 

Collaboration: 

The recruited person will be in connection with Christophe Henry and Mireille Bossy from Team CaliSto in Sophia Antipolis Méditerranée. 

Main activities 

Objectives: 

The aim of this post-doctoral research topic is to develop a new stochastic model for the orientation of spheroidal particles in a near-wall turbulent flow, when the impact of a particle with the surface becomes a probable event with a non-trivial influence on its trajectory and orientation. This project draws on the recent development of a stochastic model for the orientation of spheroidal particles in a turbulent flow. It has already been validated by comparing the results to direct numerical simulations of spheroids orientation in a channel flow. The current project follows the same approach with the objective to focus more specifically on near-wall behavior: first, microscopic simulations will be used to understand and characterize the orientation of spheroids after their impact with a surface; second, these results will be translated in a macroscopic stochastic models (compatible with standard CFD codes) to accurately reproduces the orientation statistics of such spheroids in the near-wall region while accounting for the effect of rebounds. 

Main activities: 

More precisely, the post-doctoral project includes the following activities: 

The development of an algorithm for the detection and treatment of collisions between a spheroidal particle and a surface: 

The idea here is to use the microscopic simulation available within the CaliSto Team, which couples Direct Numerical Simulation of the turbulent channel flow and Jeffery's equation [3] for the translational and rotational motion of spheroidal particles. The algorithm for the detection of the collision will be inspired by recent works on non-spherical particles [4]. The treatment of the collision (including the effect of elastic or inelastic collisions) will be treated following a recent paper that included such aspects in a more general formulations of arbitrary shaped particles [5]. 

The development of a stochastic model for the orientation of spheroids near the surface: 

The idea here is to extend the existing approach that describes the change in position and momentum of spherical particles in the near-wall turbulent region [6]. It includes a modification of the position of particles (accounting for elastic/inelastic effects) while changing the particle velocity accounting for the exchange of momentum with the near- wall turbulent flow. A similar procedure is required to include the effect of the collision on the spheroid orientation as well as to include the effect of near-wall turbulence on the spheroid orientation as it travels near the surface. The model will be validated by comparing the results obtained with the macroscopic model to statistical information extracted from the microscopic simulations. 

Skills 

Optional competences/skills: 

The following additional skills will be greatly appreciated: 

Knowledge in fluid mechanics,
Knowledge in statistical physics,
Knowledge in turbulence,
Experience in High Performance Computing (HPC). 

To apply 

Interested candidates are required to include a CV, a motivation letter, a summary of their PhD research, and at least one recommendation letter in their application. 

Benefits package 

Subsidized meals
Partial reimbursement of public transport costs
Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
Possibility of teleworking (after 6 months of employment) and flexible organization of working hours
Professional equipment available (videoconferencing, loan of computer equipment, etc.) Social, cultural and sports events and activities
Access to vocational training
Social security coverage 

General Information 

Theme/Domain : Stochastic approaches Scientific computing (BAP E)
Town/city : Sophia Antipolis
Inria Center : CRI Sophia Antipolis - Méditerranée 

About Inria 

Inria is the French national research institute dedicated to digital science and technology. It employs 2,600 people. Its 200 agile project teams, generally run jointly with academic partners, include more than 3,500 scientists and engineers working to meet the challenges of digital technology, at the interface with other disciplines. The Institute also employs numerous talents in over forty different professions. 900 research support staff contribute to the preparation and development of scientific and entrepreneurial projects that have a worldwide impact. 

The keys to success 

Profile of the candidates: 

The candidate should hold a PhD thesis in applied mathematics, scientific computation or modeling. The candidate is expected to have experience in one or more of the following topics: 

particle-laden flows
stochastic analysis and/or modelling statistics 

We are looking for outstanding candidates with strong competences and taste for code development (especially with python/ C / C++ programming languages). 

Instruction to apply 

Defence Security : 

This position is likely to be situated in a restricted area (ZRR), as defined in Decree No. 2011-1425 relating to the protection of national scientific and technical potential (PPST).Authorisation to enter an area is granted by the director of the unit, following a favourable Ministerial decision, as defined in the decree of 3 July 2012 relating to the PPST. An unfavourable Ministerial decision in respect of a position situated in a ZRR would result in the cancellation of the appointment. 

Recruitment Policy : 

As part of its diversity policy, all Inria positions are accessible to people with disabilities.