RANS simulations for contrail formation modelling

Condensation trails (contrails) are ice clouds formed at high altitudes as a result of water-vapour condensing and freezing on soot particles and sulphate aerosols which are present in the aircraft engine plumes (case of soot-rich combustion with kerosene [1]). Under favourable atmospheric conditions such as ice supersaturated regions, i.e., low temperatures and high humidities with respect to ice, these contrails can persist for up to several hours while covering large areas. The latter is especially important when considering the climate impacts of the aviation emissions as the radiative forcing from persistent contrails and contrail-cirrus is one of the major contributors [2]. 

Therefore, improving the understanding of the underlying physics of contrail is of utmost importance for the development of mitigation solutions. The process of formation and early evolution of the ice crystals occurs within the first few seconds which is often referred to as the jet phase. As such, Computational Fluid Dynamics (CFD) serves as an important tool in studying the near-field wake of the aircraft. In this study, we use a Reynolds-Averaged Navier Stokes (RANS) CFD solver, named FLUSEPA [3], to simulate the exhaust of the Common Research Model (CRM) [4] engine up to 500 m behind the engine (focusing on the mixing of the plume and not the ice crystal formation). FLUSEPA is a solver developed by Ariane Group for launcher propulsion. Furthermore, we consider an engine powered by hydrogen combustion consequently emitting about 2.6 times more water-vapour mass than a kerosene-powered engine. Note that for a hydrogen-powered engine, depending on the design choices, ice crystals would most likely form on a combination of ambient aerosols and/or soluble NOx particles. 

 

The RANS solver is used to simulate an idealised configuration of an isolated engine. This allows us to validate the dynamics of the jet in the axial direction. We briefly describe the methodologies used so as to obtain the plume’s dilution as a function of the axial position which can then be used by an offline microphysics model to simulate ice crystal formation. Finally, we vary physical and numerical parameters relevant to contrail formation to identify their role on the dilution factor. 

 

References

 

[1]  Yu, Fangqun, et al. "Revisiting contrail ice formation: Impact of primary soot particle sizes and contribution of volatile particles." Environmental Science & Technology 58.40 (2024): 17650-17660.

[2] Lee, David S., et al. "The contribution of global aviation to anthropogenic climate forcing for 2000 to 2018." Atmospheric environment 244 (2021): 117834.

[3] Pont, Grégoire, and Pierre Brenner. "High order finite volume scheme and conservative grid overlapping technique for complex industrial applications." Finite Volumes for Complex Applications VIII-Hyperbolic, Elliptic and Parabolic Problems: FVCA 8, Lille, France, June 2017 8. Springer International Publishing, 2017.

[4] Vassberg, John, et al. "Development of a common research model for applied CFD validation studies." 26th AIAA applied aerodynamics conference. 2008.