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A new geo-inspired mixer (W/M))

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Date Limite Candidature : mercredi 15 décembre 2021

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General information

Reference : UMR7342-ELINAR-004
Workplace : MARSEILLE 13
Date of publication : Thursday, November 25, 2021
Scientific Responsible name : Patrice Meunier
Type of Contract : PhD Student contract / Thesis offer
Contract Period : 36 months
Start date of the thesis : 1 December 2021
Proportion of work : Full time
Remuneration : 2852,72 euros/month

Description of the thesis topic

Objectives: Characterize the mixing in a flexible mixer to maximize transport while minimizing shear.

Expected Results:
The large-scale growth of biological cells is challenging because cells require a large oxygen supply (hence large mixing rates) but are killed by large shear stresses. Thus, bioreactors require efficient yet very gentle mixing. Such a "gentle mixer", inspired by the Earth's precession, has recently been proposed in a patent, which is currently being tested for algae growth by a local start-up.
The bioreactor consists of a cylindrical vessel slowly rotating around its axis. The flow is forced by the movement of the free surface relative to the cylinder due to the small angle between the axis and the vertical. This generates a strong resonance of the flow leading to a strong increase of the scalar transport while decreasing the small scale shear. The goal of the project is to improve the fundamental understanding of mixing in this simple configuration which can be tuned to generate laminar or turbulent flow in 3D. The mixing characteristics (stirring law, mixing time, concentration distributions) of the soft mixer will be studied using Laser-Induced Fluorescence measurements. In parallel, the flow will be characterized by PIV measurements (mean velocity and shear, PDF of velocity and shear) and described analytically using the eigenmodes of rotating fluids. The mixing properties will then be recovered using a new numerical technique based on diffusive Lagrangian tracers.

Background/Benefits: This Ph.D. work is part of the innovative CoPerMix training network (grant number 956457) on control, prediction, and learning in mixing processes, funded by the European Union, Marie Skloday, and the European Commission.
by the Marie Sklodowska-Curie program of the European Union. The objective of the network is to develop a unified vision, numerical tools, and experimental techniques for the fundamental description and quantification of mixing processes in complex flows covering a wide range of applications.

Website: www.copermix-itn.eu

Work Context

Ph.D. position at the IRPHE laboratory for 36 months.

Constraints and risks

Lighting hazards

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