Validation and Assessment of a Hybrid VOF-Lagrangian Numerical Methodology for Turbulent Liquid Fuel Jets in High-Speed Crossflow

Abstract For gas turbine combustors using liquid fuel injectors, introducing the spray into crossflowing air to achieve superior fuel-air mixing characteristics can improve performance and reduce emissions. Robust numerical design tools are needed to accelerate the development of low-emissions technologies. CFD models are used to assess the design, performance, and emissions of novel combustion systems. Atomization modelling is often facilitated by using the Lagrangian approach with breakup models rather than the more complex and computationally expensive higher-fidelity Volume-of-Fluid (VOF) approach. However, breakup models used in state-of-the-art CFD rely on empirical constants that have not yet been fully calibrated for jets in crossflow or for representative gas turbine conditions. Coupling the Lagrangian and VOF approaches could deliver a better compromise between accuracy and computational cost. Among the few studies conducted on the VOF-Lagrangian approach for jets in crossflow, validation was often limited to the near-field spray trajectory under low Weber numbers using either non-turbulent jets or water at ambient pressure. The predictive capabilities in the far-field region were only validated using deterministic breakup models and for non-turbulent jets under low pressure conditions. This study proposes and validates a novel numerical methodology for coupling the Lagrangian and VOF approaches using a Stochastic Secondary Droplet (SSD) breakup model with Adaptive Mesh Refinements (AMR) for turbulent liquid fuel jets in high-speed crossflow at more representative conditions. The predictions within both near and far-field breakup regions were validated using experimental datasets at high pressures (1–8 bar), Weber numbers (720–1172) and momentum flux ratios (6–33). The predictive capabilities and computational cost were also compared to the Lagrangian approach used with LES and used with an unsteady RANS numerical methodology previously developed and validated by the authors. The effects of different VOF-Lagrangian transition criteria on the computational cost were also assessed and recommendations have been provided for further improvements. The overall predictive capabilities of LES were significantly improved by the novel hybrid methodology proposed by the authors. Although it tends to underpredict the spray trajectory and Sauter Mean Diameter (SMD), it better captures the SMD in the wake region of the jet and the overall droplet velocities compared to the URANS methodology.

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