Cerfacs Enter the world of high performance ...

🎓 PhD Defense: Thibault DURANTON

  Monday 17 June 2024From 14h00 at 18h00

  Phd Thesis       Cerfacs, Seminar room, Toulouse, France    

Advanced LES modelling of multiperforated plates for new generation aeronautic engines

In the field of aeronautical engineering, combustion chambers of airplane and helicopter engines endure extreme thermal constraints. Over time, various technologies have been developed to enhance the resilience of these chamber walls against such constraints. One of the most advanced and widely used technologies today is multiperforation, which involves laser-drilling thousands of small holes around the circumference of the chamber walls. Similar to a transpiration process, this technique allows fresh air to pass through the walls, forming a protective thermal layer. By producing a uniform and adherent layer, the walls are better shielded against thermal constraints.

To understand the multi-physics phenomena observed in a combustion chamber, large-scale simulation has become an essential tool. However, the large number and small size of the perforations make it difficult to simulate flow therein without significantly increasing computational and engineering costs. To address this issue, multiperforation models have been developed with the aim of reproducing the main dynamics of multiperforations at a lower cost. These models are based on the concept of bypassing the resolution of flow within the perforations by imposing sink and source terms to represent the suction and injection of cooling air in the domain, on either side of the wall.

Among these models, a homogeneous model has been advanced, which uniformly imposes the flow over the entire wall surface, thereby assimilating multiperforation to a porous wall. This initial model was then improved to account for the spatial discretisation of air jets. Based on a more localised injection of flow, this heterogeneous model has thus improved the representativeness of multiperforations while retaining an acceptable computational cost. These two models are however limited by the assumption of a stationary and uniformly distributed multiperforation mass flow rate, estimated by low-order methods. Indeed, these assumptions are inadequate in simulations involving complex geometries and highly unsteady flows, particularly when studying transient phenomena such as ignition or extinction, or in the presence of thermoacoustic phenomena. Therefore, the objective of this thesis is to overcome these limitations and enhance the representativeness of the multiperforation model. The studied approach aims at accurately reproducing the spatial and temporal distribution of the cooling mass flow rate, as observed in resolved multiperforations. In other words, the goal is to estimate the mass flow rate of each hole during the simulation and integrate it locally within the framework of the heterogeneous model. Preliminary studies have allowed for the analysis of the spatial and temporal behaviour of the multiperforation mass flow rate through industrial and academic configurations, and to assess the impact of mass flow rate heterogeneity on wall thermal behaviour. These results have led to the development of a mass flow rate model for multiperforations, with a focus on modelling the discharge coefficient. This model was then implemented in a large eddy simulation code to reproduce spatial and temporal heterogeneities based on local physical quantities within the framework of the heterogeneous model.

Jury

M. Vincent MOUREAU, Rapporteur, CORIA UMR6614

M. Antonio ANDREINI, Rapporteur, University of Florence | UNIFI · Dipartimento di Ingegneria Industriale DIEF

Mme Maria Vittoria SALVETTI, Examinatrice, University of Pisa

M. Guillaume BALARAC, Examinateur, Grenoble INP

M. Laurent GICQUEL, Directeur de thèse, Institut National Polytechnique de Toulouse

M. Franck NICOUD, Co-directeur de thèse, IMAG UMR 5149

CALENDAR

Monday

24

June

2024

Data assimilation

From Monday 24 June 2024 to Thursday 27 June 2024

  Training    

Monday

07

October

2024

Machine learning for data science

From Monday 7 October 2024 to Thursday 10 October 2024

  Training    

Monday

14

October

2024

Fundamentals to understand and analyse high fidelity compressible Large Eddy Simulations

From Monday 14 October 2024 to Wednesday 16 October 2024

  Training       Cerfacs, Toulouse, France    

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