Population balance modelling of liquid-liquid extraction

IFP Energies nouvelles - Lyon; Solaize; In loco; EUR 12.000 - 14.000; Part-time

Vantaggi offerti da questo lavoro

Paid internship 1150€/month

Descrizione del lavoro

IFP Energies nouvelles - Lyon invites applications for a 6-month internship focused on population balance modeling of liquid-liquid extraction. You will study coalescence and breakup kernels, implement a 0D/1D PBM in Python, and validate results against literature or IFPEN data.

The role requires a chemical engineering background, modelling acumen, and proficiency in Python for scientific computing. Workplace is Lyon, with a paid internship of 1150€/month gross.

Competenze

• Chemical engineering background and strong modelling skills.
• Experience in scientific programming and Python is required.
• 1) Internship duration is 6 months. 2) Paid internship details provided.

Mansioni

• Literature review on coalescence and breakup models for PBM.
• Develop a 0D/1D population balance model in Python.
• Validate the model against published or IFPEN experiments.

Conoscenze

Chemical engineering

Modelling

Python

Scientific programming

Formazione

Chemical engineering degree

Strumenti

Python

Descrizione del lavoro

Population balance modelling of liquid-liquid extraction

The liquid-liquid extraction (LLE) process is widely used to separate the components of a liquid phase, particularly when such separation is not feasible via distillation. In general, the LLE consists of dispersing one liquid phase as droplets in another liquid phase, so that one or some target solutes transfer from one phase to the other.

The design and scale-up of the LLE requires knowledge of the mass transfer between phases, which in turn depends on the physicochemical properties of the phases, flow hydrodynamics in the contact system, and the droplet size distribution (DSD).

In this internship, we will focus on the prediction of the DSD by the population balance modelling.

Description

Population balance modeling (PBM) is a promising tool to describe the evolution of dispersed phases in multiphase flows. In the context of LLE, the PBM can be used to describe the coalescence and breakup of droplets, which determine the droplet size distribution (DSD).

The main goal of this internship is to develop a 0D/1D population balance model in Python and to study different coalescence and breakup kernels that are either available in literature or developed at IFPEN.

The work will be divided into the following tasks:

• Conducting a literature review on the state of the art for the coalescence and breakup models
• Developing a general 0D/1D population balance model for multiphase flows in Python
• Validating the model against experiments from the literature or available at IFPEN

Required profile

Chemical engineering, modelling, scientific programming, Python

Additional information

• Duration of the internship: 6 months
• Workplace: IFPEN Lyon, Rond-point de l'échangeur de Solaize, 69360 Solaize
• Transport: public transportation / personal vehicle
• Paid internship 1150€/month (gross)