Editorial: Pressure Gain Combustion technologies for a Greener propulsion

This Research Topic was formulated to address some fundamental aspects of Rotating Detonation Combustor (RDC) performance and modelling strategies. Recently, great interest arose in developing novel cycles for gas turbines aimed at increasing overall efficiency and specific power. That effort is accompanied by the possibility of using hydrogen as fuel in Pressure Gain Combustion (PGC) cycles, thus decreasing the direct emission of CO2 (although NOx emissions are still an open topic) and exploiting its fast combustion properties. The actual performance of PGC-equipped gas turbines is highly debated, with the pressure rise in the combustor and the coupling with a turbine still under investigation by several research groups, including the ones to which the Editors of the Research Topic belong. The RDC exhibits complex aero-thermo-mechanical challenges that are difficult to evaluate experimentally due to the extremely high exhaust temperature, high Mach numbers and the high characteristic frequencies, preventing standard experimental approaches. A complete study of RDC performance is fundamental to appropriately design the turbine module, either subsonic or supersonic, aimed at fostering the manufacturing of enabling components for power generation or propulsion. The present Research Topic addresses the impact of the injectors’ geometry on mixing efficiency and the definition of strategies for their simulation. Le Naour et al. provide insights into some fundamental numerical and experimental aspects of RDC, with particular interest in the injection configurations. Sato et al. studied the impact of two different boundary conditions on the flow field development inside the RDC chamber using high-fidelity Computational Fluid Dynamics (CFD) compared to experimental findings. Finally, Hellard et al. apply a modeling strategy for the simulation of transitory injection in RDCs, thus providing information about the possibility of studying reactants mixing at low computational cost.