Martí i Franquès MSCA-COFUND DP. Call for 1 PhD candidate within the project "Numerical simulations...
Universitat Rovira i Virgili
Tarragona, Spain
hace 4 días
source : Euraxess

Overview

The Martí i Franquès COFUND Doctoral Fellowships Programme (MFP) is a redesign of the existing MF programme, offering 100 doctoral contracts (in four editions : 2017, 2018 and 2020, 2021) at the Universitat Rovira i Virgili (URV).

The programme is uniquely shaped to offer the best training stemming from the "triple i" principles of the Marie Sklodowska-Curie Actions : international, interdisciplinary and intersectoral.

In order to achieve these goals, we combine leading research groups at URV with scientific partners from world-class institutions, such that the candidates are be exposed to interdisciplinary training as well as mentoring from the industrial sector.

Through MFP, URV is in a unique position to offer the best conditions for doctoral training, based on the principles of the and the Code of Conduct for the Recruitment of Researchers (guaranteed by the HR award that URV has received in 2014), as well as the .

Description of the research project (reference : 2020MFP-COFUND-7)

Simulations and experiments of two-phase and / or three-phase flows in multiphase reactors are important for many industrial instance, the chemical, biochemical, or environmental industries.

One of the most primitive, but nevertheless often used, reactor types for multiphase reactions are bubble columns. This kind of reactors have advantageous characteristics in mass and heat transfers and cause only low operation and maintenance costs due to absence of moving parts.

In bubble column reactors, the gas phase is dispersed in the form of tiny bubbles in a continuous liquid phase using a gas distribution device.

The complex interplay between operating conditions, the gas-liquid interfacial area, turbulence in the liquid phase, and bubble-bubble interactions lead to extensive range of flow regimes and complex flow structures.

Besides, the liquid turbulence causes macro- and micromixing of the liquid reactants the dissolved gas, the solvent or already dissolved species), whose local distributions are in turn decisive for the reaction rates.

Several experimental of these types of flows have been carried out by using different measurement techniques depending on the considered configuration, pressure sensors, oxygen probes, or velocity measurements.

New simulation models incorporte the turbulence of the liquid phase through the Reynold-Averaged Navier-Stokes (RANS) models or Large-eddy simulactions (LES) models.

However, the exacts mechanism and mixing phenomena are sill unclear due to the lack of models and experimental information.

Especially, the effects of physicochemical properties of the liquid phase like viscosity and surface tensions are poorly investigated.

The main idea of the current investigation is close related to our proposal for a national project to be funded by the ministry of science and innovation, where an experimental set up is suggested to analyze absorption of CO2 in water in pipeline systems.

It consists on an experimental setup of a bubble column reactor in our labs in Tarragona, which allow us the application of visualization and local measurement techniques available in our labs to obtain readily experimental information and, it will facilitate the analysis of the effect of a distributed gas inlet in the hydrodynamics and the associated mass transfer rates and chemical reactions.

Further studies on fluid with different viscosities and surface tensions could increase our databank size. Additionally, numerical simulations could provide better knowledge of the flow structure and acting physical phenomena.

Finally, this setup can be used to analyze and measure dissolution rates of gas (CO2) bubbles.

Required Research Experiences

  • RESEARCH FIELD Engineering
  • YEARS OF RESEARCH EXPERIENCE 1 - 4
  • Offer Requirements

  • REQUIRED EDUCATION LEVEL Engineering : Master Degree or equivalent
  • REQUIRED LANGUAGES ENGLISH : Excellent
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