Flame response inference from pressure-only data via physics-informed neural networks
This study presents a physics-informed neural network framework to reconstruct spatio-temporal acoustic pressure fields and hidden quantities—namely, velocity and heat-release-rate fluctuations—in axial combustors using only sparse pressure measurements. By embedding the linearized Euler equations into the training pro...