Content

CS01: Fluid dynamics (11 ECTS)

Content:

Physics of fluids, micro-, meso- and macroscale, transport phenomena, constitutive equations, complex fluids, rheology, conservations laws (local and global), turbulence, boundary layer, RANS, LES, k-epsilon models, combustion and reactive flows, liquid-gas or liquid-vapor flows, flow regimes map and correlations, suspension flows 

This course includes an Introduction to CFD : 
Mesh-based methods (FDM, FVM, FEM), Particle-based methods, Explicit vs. Implicit solvers, CFL stability condition, algorithm, time stepping methods, visualization

Learning outcomes:

• explain the link between microscopic properties of a fluid and its rheological and thermal behaviour
• choose and implement the appropriate method for modelling turbulent flows
• explain the Finite Volume Method, write a toy code and critically 
• evaluate the influence of material properties and operating conditions on the flow regime
• discretize an EDP according to a given numerical scheme
• write a toy code to compute flow field on benchmark configuration
• use the different softwares on the chain (geometry, mesh generation, solver, visualization)
• know the main open-source and industrial codes

CS02: Physical chemistry (5.5 ECTS)

Content:
Transport phenomena (momentum, mass, heat), homogeneous reactors (CSTR, plug flow), heterogeneous reactors (catalytic or not), crystallization, germination, growth, agglomeration, reaction kinetics and thermodynamics

Learning outcomes:

• describe the main transport phenomena and propose their modelling equations
• write and solve equations to predict a concentration or temperature evolution in a reactor
• differentiate the different crystallization processes at play during precipitation or solid-state transformations

CS03: Experimental characterization methods of solids and fluids (5.5 ECTS)

Content:

Radiation-matter interaction, X-ray diffraction, Scanning and Transmission Electron Microscopy, Elementary surface analysis, specific surfaces, porosity, thermal stability,

Learning outcomes:

• understand the theory underlying the experimental characterization tools
• know the working principles and the limits of the main characterization methods of dispersed systems (solids, fluids)
• operate some of these instruments, in autonomy or under guidance

CS04: Particulate Science and Technology (6 ECTS)

Content:
Physics of granular matter, mechanical, thermal and chemical transformations, size reduction (grinding, abrasion, attrition) and enlargement (agglomeration, granulation, caking), compaction and sintering, pneumatic transport and fluidization, ..

Event driven, soft sphere and hard sphere approaches, algorithmic implementation for soft spheres, contact laws and calibration, scale-up, coarse graining and homogeneization

Learning outcomes:

• choose the appropriate sequence of unit operations to handle and transform powders and grains
• describe the main phenomena at play in these devices/reactors
• design some reactor properties and operating conditions to handle a particular granular matter
• critically identify the advantages and drawbacks of a unit operation
• write a toy code implementing the basic physical laws
• use a highly parallelised research code and/or an industrial one
• propose a method to calibrate the numerical parameters and guarantee the validity of the simulation outputs
• customize an existing code to take into account new phenomena

CT01: Technology for renewable energy sources (8 ECTS)

Content:

Impact of sustainability of anthropogenic activities, multiphase production systems, optimization matter and energy consumption, use of renewable materials, Energy Sustainability Index (ESI), Energy Return On Investment (EROI) and Energy Payback Time

Learning outcomes:

• design of new approaches for the development of sustainable production processes
• assess the interaction between natural cycles and anthropic activities
• perform analysis on energy and production processes sustainability e.g. Life Cycle Analysis (LCA).

CT02: Fixation and recycle of CO2 for Green House Gas mitigation (6 ECTS)

Content:

Carbon cycle, main greenhouse gases, CO2 sequestration and conversion processes, synthesis of urea, dry reforming, conversion of CO2 into inorganic carbonates, power-to-X, photo-catalytic, electro-catalytic and photo- synthetic processes

Learning outcomes:

• nature and chemistry of the natural carbon cycle on the planet 
• properties of the CO2 molecule and the consequent poor chemical reactivity
• CO2 capture processes, chemical reactivation through the use of renewable energy and H2, CO2 entrapment in "end-of-life" compounds

CT03: Multiphase chemical reactors for sustainable processes(8 ECTS)

Content:
Gas-liquid and liquid-liquid reactors, catalytic heterogeneous reactors, porous catalysts, modelling of multiphase chemical reactors, three-phase chemical reactors, mixing and scale-up
Learning outcomes:

• master and control mixing in multiphase chemical reactors
• design multiphase chemical reactors with optimal mass, momentum and energy transfer
• design multiphase chemical reactors for sustainable engineering applications

CT04: Hydrogen for sustainable energy(3 ECTS)

Content:
Energy transition, hydrogen economy, production, storage and use of H2 through electrolysers and fuel cells. Basic theory on electrochemistry. Momentum, mass, heat, charge transport phenomena.

Learning outcomes:

• explain the basic fundamental aspects of electrochemistry
• understand the working principles, advantages and drawbacks of electrolysers and fuel cells (mainly PEMFC and SOFC)
• use models to evaluate the influence of the materials on electro- catalytic properties

CT05: Population balances (3 ECTS)

Content:
Definition of population balances, application of population balances to multiphase systems for sustainable engineering applications, solution methods and coupling with CFD

Learning outcomes:

• ability to formulate and solve a population balance
• numerical solution of population balances with different methods
• coupling of population balances with CFD

CM01: Multiscale modelling (5 ECTS)

Content:
Systematic overview of the developments and challenges in multiscale modeling with emphasis on fundamental principles and overaching issues

Learning outcomes:

• master numerical models from scale-separation analysis
• ability to compute coarse-grained (CG) models for molecular dynamics
• use CG models for general applications in science and engineering

CM02: Mathematical modelling of materials (5 ECTS)

Content:
Linear FEM for elasticity with volume locking, error estimators and non-linear analysis, discussion of limits for phase transition and fracture problems

Learning outcomes:

• understand and apply linear and nonlinear FEM
• apply FEM using advanced software packages
• master FEM for continuum mechanics, phase transitions and fracture mechanics

CM03: Probability Theory and Uncertainty Quantification (5 ECTS)

Content:
Knowledge of fundamental methods in uncertainty quantification problems, ability to represent
and quantify mathematically uncertainty in order to optimize technical systems. Uncertainty propagation,
Uncertainty back-propagation, Design in the presence of uncertainties

Learning outcomes:

• have knowledge of fundamental challenges in uncertainty quantification problems
• become familiar with the state-of-the-art in terms of numerical techniques for a range of model problems
• learn how to represent mathematically uncertainty in the parameters of physical models
• be capable of performing model calibration and validation tasks for a wide-range of mathematical models
• be capable of propagating parametric uncertainty through physical models to quantify the induced uncertainty on quantities of interest
• be capable of carrying out optimization tasks in a wide-range of engineering systems in the presence of uncertainties
• develop a probabilistic thinking in carrying out analysis and design tasks in engineering simulation

CM04: Particle-simulation methods for Fluid Dynamics (3 ECTS)

Content:
Introduction on theoretical basics of Particle- Simulation Methods for Fluid Dynamics ranging from
molecular dynamics (MD), Monte-Carlo methods (MC) over Lattice-Gas automata (LGA)/Lattice-Boltzmann
methods (LBM) to continuum methods (Navier-Stokes)

Learning outcomes:

• understand basics and principles of microscopic methods (MD, MC)
• understand basics and principles of mesoscopic methods (LGA, LBM, DSMC, DPD)
• understand basics and principles of macroscopic methods (Navier- Stokes, SPH, PIC)

CM05: Practical course (4 ECTS)

Content: Four (4) ECTS must come from the following list of modules. The Education Committee regularly
updates the Practical Courses catalog.  

List of available modules (may evolve): 

• MW2134, Computational Thermo-Fluid Dynamics
• ED140016, Computational Methods for Operator-based analysis
•  MW1277, Simulation of Thermofluids with Open-Source Tools
•  MW2451, Hands-on Deep Learning

CM06: Multiphase flows CFD (5 ECTS)

Content:
Introduction to state-of-the-art numerical methods for multiphase flow simulations using sharpand diffuse-interface models

Learning outcomes:

• understand multiphase systems and their challenges on numerical methods
• use diffuse-interface (vof) and sharp-interface (level-set) methods for compressible and incompressible flow problems
• critically assess validity, efficiency and accuracy of opposed methods in different flow configurations

The Internship will last 5 months, during which the student will work on his/her Master Thesis. It is the opportunity for
the students to apply the knowledge and know-how delivered during the 3 first semesters of the MULTIPHASE master
to a challenge which is both involving a multiphase system and an application oriented towards sustainable
engineering.

Students will have the choice to join an academic laboratory, especially among the full partners and the
academic Associated Partners, or to go for an internship in an industrial environment.