A PINN-DeepONet framework for extracting turbulent combustion closure from multiscalar measurements
In this study, we develop a novel framework to extract turbulent combustion closure,
including closure for species chemical source terms, from multiscalar and velocity …
including closure for species chemical source terms, from multiscalar and velocity …
Physics-informed neural networks coupled with flamelet/progress variable model for solving combustion physics considering detailed reaction mechanism
In recent years, physics-informed neural networks (PINNs) have shown potential as a
method for solving combustion physics. However, current efforts using PINNs for the direct …
method for solving combustion physics. However, current efforts using PINNs for the direct …
FlamePINN-1D: Physics-informed neural networks to solve forward and inverse problems of 1D laminar flames
Given the existence of various forward and inverse problems in combustion studies and
applications that necessitate distinct methods for resolution, a framework to solve them in a …
applications that necessitate distinct methods for resolution, a framework to solve them in a …