The position is in the frame of a national work program funded by the French National Research Agency. Consortium is made up of an academic laboratory (M2P2, Aix-Marseille Université) and ENGIE Lab CRIGEN (Centre de Recherche et Innovation Gaz et Energies Nouvelles), the ENGIE Group's centre for research and operational expertise dedicated to gas, new energies and emerging technologies. The aim of the TIGRE project is to develop effective methods for full-scale modelling of the behavior of inorganic compounds in gasification reactors, taking into account the hydrodynamics of the system, heat transfer and the chemical nature of the various phases. You will be integrated in a pluri-disciplinary team with experts in the field of gasification and solid characterization. The project fits with the need to reduce dependence on fossil fuels and thus to the decrease of the environmental footprint of energy sector which is of major importance.

The thermal gasification of waste represents a promising avenue for sustainable energy production and waste valorization. However, the formation of unwanted by-products coming from the inorganics elements originally present in feedstock constitutes a significant hurdle for process design and optimization. Addressing these scientific bottlenecks requires a combination of experimental research and advanced modeling techniques to enhance gasification efficiency and improve the quality of the resulting syngas. Indeed, the syngas quality is directly correlated to the non-content of compounds such as sulfur or chlorine. A large bench of analytical apparatus has been deployed for understanding behaviors and interactions of mineral matter during gasification. This includes the characterization and the definition of the initial feed, and the characterization of all mineral phase formed during the process.

During pyro-gasification, the inorganic components of biomass undergo diverse transformations depending on whether they are naturally embedded within the biomass matrix (autogenic origin) or externally introduced (technogenic origin or contaminants). In this context, the fluidized bed material is considered part of the externally added inorganic matter. Owing to its elemental composition and catalytic behavior, it can sometimes exhibit higher reactivity than other forms of debris or technogenic materials, thereby influencing the evolution of both the organic and inorganic fractions during gasification. The progression of these changes in the inorganic fraction remains unknown.

A portion of the inherent inorganic matter may volatilize during devolatilization, later condensing as fine particulates or reacting with external inorganic phases—whether solid or molten—to form slag or agglomerated structures. Some of the native inorganic elements that do not volatilize immediately may be transferred into the gas or vapor phases during rapid pyrolysis and gasification. These transitions are enhanced by reactions involving oxidants, syngas, char, and tar. Simultaneously, structural changes in the organic matrix facilitate the migration and proximity of certain inorganic species, allowing them to interact and produce either low-melting compounds or chemically stable phases. As gasification consumes the organic matrix, these transformations culminate in ash formation. The ash, through interactions with both molten and solid phases of the endogenous and exogenous mineral matter, can contribute further to agglomeration.

The position is in the frame of a national work program funded by the French National Research Agency. Consortium is made up of an academic laboratory (M2P2, Aix-Marseille Université) and ENGIE Lab CRIGEN (Centre de Recherche et Innovation Gaz et Energies Nouvelles), the ENGIE Group's center for research and operational expertise dedicated to gas, new energies and emerging technologies. The aim of the TIGRE project is to develop effective methods for full-scale modelling of the behavior of inorganic compounds in gasification reactors, considering the hydrodynamics of the system, heat transfer and the chemical nature of the various phases. You will be in charge to lead experimental work on a continuous gasifier. You will be integrated in a multidisciplinary team of experts in the field of gasification.

The thermal gasification of waste represents a promising avenue for sustainable energy production and waste valorization. However, the formation of unwanted by-products coming from the inorganics elements originally present in feedstock constitutes a significant hurdle for process design and optimization. Addressing these scientific bottlenecks requires a combination of experimental research and advanced modeling techniques to enhance gasification efficiency and improve the quality of the resulting syngas. It is in this context that an experimental setup was developed to study the performance of a bubbling fluidized bed at low fluidization velocity. The experimental setup is a continuous pilot of some kg/hours with gas cleaning and sampling facilities (gas and solids) allowing gasification to be performed under a vast set of atmospheres. This experimental procedure provides complete temperature, gas composition and flow rate data for balance and efficiency calculation. Experimental tests and associated analyses are conducted to establish possible synergy between different feedstocks to expand the possible applicable feedstocks. The final objective is to develop a comprehensive modeling of inorganics behavior.

The innovation of this work is then the application of different feedstock management strategies and

 controlled operating conditions and the consequence of those strategies on the resulting outflows of the process. In the first six months, you ‘ll work on several biomass and waste such as received to collect data and trained on the experimental pilot by exploring a range of operating conditions. The study of the physico-chemical interactions of raw materials with the fluidizing medium and the gasification atmosphere is a key point for this period. In a second time, in collaboration with the team, you’ll contribute to the design of a dedicated experimental plan and tests specifications to optimize inorganics recovery. The team is composed of 10 researchers. Among them you will have to specifically work daily with two PhD students.

You may contribute to the development and comparison of gas sampling and analysis methods. Depending on experimental results, you may also contribute to the Improvement of the experimental pilot design. The project fits perfectly with the need to reduce dependence on fossil fuels and thus to the decrease of the environmental footprint of energy sector which is of major importance to meet the objectives of the European Union.

- An autonomous person with a strong sense of initiative

- PhD in Process Engineering with skills in experimental works on thermal processing

- Skills Data processing and analysis

- Skills for kinetic modeling

- Writing reports and scientific publications.

As a manager, you’ll have to supervise interns and PhD students. Presentation of results at international conferences are welcome.

You will be based in Stains closed to Paris, easily accessible from Paris center by public transportation. A monthly travel to Aix-en-Provence (southern France) for discussions is also to be planned.

The mathematical and numerical modelling of multi-phase flows is never ending challenge for the academia (astrophysics, geophysics, meteorology, etc.) and industry (combustion, nuclear, health etc.). This modelling often involves dispersed multiple phases (liquid, gas, solid, and their combinations) and/or components (individual particles, droplets, bubbles, etc.). The extreme complexity and variety of mixed phases interactions, such as pressure gradients, flow speeds, material properties often limits multi-phase oriented research to simplified or ideal cases while numerous importance physical phenomena have to be addressed, even if in approximate ways, such as bubbles and slugs in pipes, nuclear reactor safety, cavitation, dust combustion and explosions and many more. 

One of the most used approaches to describe such flows is multiphase or multi-fluid modelling based on a time, space or ensemble phase-conditioning average. A large variety of models exists based on the phases characteristics, geometries of dispersion, flow regimes, dissipation strategies, source terms, boundary conditions etc. However, all multifluid models are reduced to Euler-like fluid equations for mass, momentum and energy involving transport and pressure terms only when the dissipation effects are neglected. This is referred to as a ”backbone model”.

Apart of the model choice, the numerical discretization of multi-fluid equations is a constant challenge due to variety of reasons: (i) the pressure couplings often cause the non-conservative form of equations, (ii) strong contrast of fluid characteristics yields to the presence of stiff terms, (iii) possible ellipticity of the system for certain flows (with subsonic inter-fluid drift velocities, for instance), (iv) the loss of the thermodynamic consistency resulted by pressure calculations inconsistency. Thus, an appropriate numerical scheme is required in order to address these difficulties. To this extend, a novel and efficient multi-fluid numerical scheme for discretizing the ”backbone” equations over a moving grid (ALE or Arbitrary Lagrangian–Eulerian) has been developed through a “Geometry, Energy, and Entropy Compatible” mimicking procedure (GEEC) [1–4]. Starting from the discretized density fields, energy fields, and transport operators, the procedure yields the discrete evolution equations in a practically univocal way. With arbitrarily moving grids, number of fluids, contrasts of volume fractions and equations of state, the resulting scheme is fully conservative in masses, momentum, and energy, preserves isentropic behaviour to the scheme order, and ensures per-fluid thermodynamic consistency. Noticeably, optimal isentropic behaviour is obtained thanks to a non-standard downwind form of pressure gradient. This has been validated in an ”in-house” developped 1D/2D code on a classic set of academic validation problems.