2 papers
physics.flu-dyn2026
A convolutional autoencoder and neural ODE framework for surrogate modeling of transient counterflow flames
Mert Yakup Baykan, Weitao Liu, Thorsten Zirwes +3
A novel convolutional autoencoder neural ODE (CAE-NODE) framework is proposed for a reduced-order model (ROM) of transient 2D counterflow flames, as an extension of AE-NODE methods…
physics.flu-dyn2024
How "mixing" affects propagation and structure of intensely turbulent, lean, hydrogen-air premixed flames
Yuvraj, Hong G. Im, Swetaprovo Chaudhuri
Understanding how intrinsically fast hydrogen-air premixed flames can be rendered much faster in turbulence is crucial for systematically developing hydrogen-based gas turbines and…