Fourier Neural Operator (FNO) augmented 2D Fluid simulations of High-Power Microwave (HPM) breakdown

HPM breakdown in high-pressure environments has the potential to significantly enhance plasma-assisted combustion essential for advancing next-generation green combustion technologies. Traditional simulation of HPM breakdown, a multiscale phenomenon, is computationally expensive and requires solving Maxwell's equations (EM solver) coupled with a plasma continuity equation (plasma solver). In this work, we present a hybrid modeling approach that combines the accuracy of a differential equation-based plasma fluid solver with the computational efficiency of FNO for the EM solver. Trained on data from an in-house FDTD-based plasma-fluid solver, the FNO replaces computationally expensive EM field updates, while the plasma solver governs the dynamic plasma response. The hybrid model is validated on microwave streamer formation in a 2D scenario for unseen incident electric fields corresponding to entirely new plasma streamer simulations not included in model training, showing excellent agreement with FDTD-based fluid simulations in terms of streamer shape, velocity, and temporal evolution. This hybrid FNO based strategy delivers significant acceleration of the order of 50X compared to traditional simulations and offers a promising and efficient alternative for exploring the computationally demanding multiscale and multiphysics simulations involved in HPM breakdown.